Asymmetric Evolutionary Games

Science.gov (United States)

McAvoy, Alex; Hauert, Christoph

2015-01-01

Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner’s Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games. PMID:26308326

Mean-field approximations of fixation time distributions of evolutionary game dynamics on graphs

Science.gov (United States)

Ying, Li-Min; Zhou, Jie; Tang, Ming; Guan, Shu-Guang; Zou, Yong

2018-02-01

The mean fixation time is often not accurate for describing the timescales of fixation probabilities of evolutionary games taking place on complex networks. We simulate the game dynamics on top of complex network topologies and approximate the fixation time distributions using a mean-field approach. We assume that there are two absorbing states. Numerically, we show that the mean fixation time is sufficient in characterizing the evolutionary timescales when network structures are close to the well-mixing condition. In contrast, the mean fixation time shows large inaccuracies when networks become sparse. The approximation accuracy is determined by the network structure, and hence by the suitability of the mean-field approach. The numerical results show good agreement with the theoretical predictions.

Evolutionary potential games on lattices

Energy Technology Data Exchange (ETDEWEB)

Szabó, György, E-mail: szabo@mfa.kfki.hu; Borsos, István, E-mail: borsos@mfa.kfki.hu

2016-04-05

Game theory provides a general mathematical background to study the effect of pair interactions and evolutionary rules on the macroscopic behavior of multi-player games where players with a finite number of strategies may represent a wide scale of biological objects, human individuals, or even their associations. In these systems the interactions are characterized by matrices that can be decomposed into elementary matrices (games) and classified into four types. The concept of decomposition helps the identification of potential games and also the evaluation of the potential that plays a crucial role in the determination of the preferred Nash equilibrium, and defines the Boltzmann distribution towards which these systems evolve for suitable types of dynamical rules. This survey draws parallel between the potential games and the kinetic Ising type models which are investigated for a wide scale of connectivity structures. We discuss briefly the applicability of the tools and concepts of statistical physics and thermodynamics. Additionally the general features of ordering phenomena, phase transitions and slow relaxations are outlined and applied to evolutionary games. The discussion extends to games with three or more strategies. Finally we discuss what happens when the system is weakly driven out of the “equilibrium state” by adding non-potential components representing games of cyclic dominance.

Evolutionary potential games on lattices

International Nuclear Information System (INIS)

Szabó, György; Borsos, István

2016-01-01

Game theory provides a general mathematical background to study the effect of pair interactions and evolutionary rules on the macroscopic behavior of multi-player games where players with a finite number of strategies may represent a wide scale of biological objects, human individuals, or even their associations. In these systems the interactions are characterized by matrices that can be decomposed into elementary matrices (games) and classified into four types. The concept of decomposition helps the identification of potential games and also the evaluation of the potential that plays a crucial role in the determination of the preferred Nash equilibrium, and defines the Boltzmann distribution towards which these systems evolve for suitable types of dynamical rules. This survey draws parallel between the potential games and the kinetic Ising type models which are investigated for a wide scale of connectivity structures. We discuss briefly the applicability of the tools and concepts of statistical physics and thermodynamics. Additionally the general features of ordering phenomena, phase transitions and slow relaxations are outlined and applied to evolutionary games. The discussion extends to games with three or more strategies. Finally we discuss what happens when the system is weakly driven out of the “equilibrium state” by adding non-potential components representing games of cyclic dominance.

Evolutionary potential games on lattices

Science.gov (United States)

Szabó, György; Borsos, István

2016-04-01

Game theory provides a general mathematical background to study the effect of pair interactions and evolutionary rules on the macroscopic behavior of multi-player games where players with a finite number of strategies may represent a wide scale of biological objects, human individuals, or even their associations. In these systems the interactions are characterized by matrices that can be decomposed into elementary matrices (games) and classified into four types. The concept of decomposition helps the identification of potential games and also the evaluation of the potential that plays a crucial role in the determination of the preferred Nash equilibrium, and defines the Boltzmann distribution towards which these systems evolve for suitable types of dynamical rules. This survey draws parallel between the potential games and the kinetic Ising type models which are investigated for a wide scale of connectivity structures. We discuss briefly the applicability of the tools and concepts of statistical physics and thermodynamics. Additionally the general features of ordering phenomena, phase transitions and slow relaxations are outlined and applied to evolutionary games. The discussion extends to games with three or more strategies. Finally we discuss what happens when the system is weakly driven out of the "equilibrium state" by adding non-potential components representing games of cyclic dominance.

Evolutionary game theory and organizational ecology: The case of resource-partitioning theory

OpenAIRE

ZHOU, Chaohong; VAN WITTELOOSTUIJN, Arjen

2009-01-01

Abstract: In this paper, we construct a mathematical model that applies tools from evolutionary game theory to issues in organizational ecology. Evolutionary game theory shares the key feature of mathematical rigor with the industrial organization tradition, but is similar to organizational ecology by emphasizing evolutionary dynamics. Evolutionary game theory may well be a complementary modeling tool for the analytical study of organizational ecology issues, next to formal logic, standard ga...

Fixation times in evolutionary games under weak selection

International Nuclear Information System (INIS)

Altrock, Philipp M; Traulsen, Arne

2009-01-01

In evolutionary game dynamics, reproductive success increases with the performance in an evolutionary game. If strategy A performs better than strategy B, strategy A will spread in the population. Under stochastic dynamics, a single mutant will sooner or later take over the entire population or go extinct. We analyze the mean exit times (or average fixation times) associated with this process. We show analytically that these times depend on the payoff matrix of the game in an amazingly simple way under weak selection, i.e. strong stochasticity: the payoff difference Δπ is a linear function of the number of A individuals i, Δπ=u i+v. The unconditional mean exit time depends only on the constant term v. Given that a single A mutant takes over the population, the corresponding conditional mean exit time depends only on the density dependent term u. We demonstrate this finding for two commonly applied microscopic evolutionary processes.

Stochastic evolutionary dynamics in minimum-effort coordination games

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Li, Kun; Cong, Rui; Wang, Long

2016-08-01

The minimum-effort coordination game draws recently more attention for the fact that human behavior in this social dilemma is often inconsistent with the predictions of classical game theory. Here, we combine evolutionary game theory and coalescence theory to investigate this game in finite populations. Both analytic results and individual-based simulations show that effort costs play a key role in the evolution of contribution levels, which is in good agreement with those observed experimentally. Besides well-mixed populations, set structured populations have also been taken into consideration. Therein we find that large number of sets and moderate migration rate greatly promote effort levels, especially for high effort costs.

An application of evolutionary game theory to social dilemmas: the traveler's dilemma and the minimum effort coordination game.

Directory of Open Access Journals (Sweden)

Swami Iyer

Full Text Available The Traveler's Dilemma game and the Minimum Effort Coordination game are two social dilemmas that have attracted considerable attention due to the fact that the predictions of classical game theory are at odds with the results found when the games are studied experimentally. Moreover, a direct application of deterministic evolutionary game theory, as embodied in the replicator dynamics, to these games does not explain the observed behavior. In this work, we formulate natural variants of these two games as smoothed continuous-strategy games. We study the evolutionary dynamics of these continuous-strategy games, both analytically and through agent-based simulations, and show that the behavior predicted theoretically is in accord with that observed experimentally. Thus, these variants of the Traveler's Dilemma and the Minimum Effort Coordination games provide a simple resolution of the paradoxical behavior associated with the original games.

An application of evolutionary game theory to social dilemmas: the traveler's dilemma and the minimum effort coordination game.

Science.gov (United States)

Iyer, Swami; Reyes, Joshua; Killingback, Timothy

2014-01-01

The Traveler's Dilemma game and the Minimum Effort Coordination game are two social dilemmas that have attracted considerable attention due to the fact that the predictions of classical game theory are at odds with the results found when the games are studied experimentally. Moreover, a direct application of deterministic evolutionary game theory, as embodied in the replicator dynamics, to these games does not explain the observed behavior. In this work, we formulate natural variants of these two games as smoothed continuous-strategy games. We study the evolutionary dynamics of these continuous-strategy games, both analytically and through agent-based simulations, and show that the behavior predicted theoretically is in accord with that observed experimentally. Thus, these variants of the Traveler's Dilemma and the Minimum Effort Coordination games provide a simple resolution of the paradoxical behavior associated with the original games.

An Application of Evolutionary Game Theory to Social Dilemmas: The Traveler's Dilemma and the Minimum Effort Coordination Game

Science.gov (United States)

Iyer, Swami; Reyes, Joshua; Killingback, Timothy

2014-01-01

The Traveler's Dilemma game and the Minimum Effort Coordination game are two social dilemmas that have attracted considerable attention due to the fact that the predictions of classical game theory are at odds with the results found when the games are studied experimentally. Moreover, a direct application of deterministic evolutionary game theory, as embodied in the replicator dynamics, to these games does not explain the observed behavior. In this work, we formulate natural variants of these two games as smoothed continuous-strategy games. We study the evolutionary dynamics of these continuous-strategy games, both analytically and through agent-based simulations, and show that the behavior predicted theoretically is in accord with that observed experimentally. Thus, these variants of the Traveler's Dilemma and the Minimum Effort Coordination games provide a simple resolution of the paradoxical behavior associated with the original games. PMID:24709851

Game equilibrium models I evolution and game dynamics

CERN Document Server

1991-01-01

There are two main approaches towards the phenotypic analysis of frequency dependent natural selection. First, there is the approach of evolutionary game theory, which was introduced in 1973 by John Maynard Smith and George R. Price. In this theory, the dynamical process of natural selection is not modeled explicitly. Instead, the selective forces acting within a population are represented by a fitness function, which is then analysed according to the concept of an evolutionarily stable strategy or ESS. Later on, the static approach of evolutionary game theory has been complemented by a dynamic stability analysis of the replicator equations. Introduced by Peter D. Taylor and Leo B. Jonker in 1978, these equations specify a class of dynamical systems, which provide a simple dynamic description of a selection process. Usually, the investigation of the replicator dynamics centers around a stability analysis of their stationary solutions. Although evolutionary stability and dynamic stability both intend to charac...

Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games

Science.gov (United States)

Peña, Jorge; Rochat, Yannick

2012-01-01

By combining evolutionary game theory and graph theory, “games on graphs” study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner’s dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner’s dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures. PMID:22970237

Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations.

Science.gov (United States)

Liao, David; Tlsty, Thea D

2014-08-06

Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.

Statistical mechanics of spatial evolutionary games

International Nuclear Information System (INIS)

Miekisz, Jacek

2004-01-01

We discuss the long-run behaviour of stochastic dynamics of many interacting players in spatial evolutionary games. In particular, we investigate the effect of the number of players and the noise level on the stochastic stability of Nash equilibria. We discuss similarities and differences between systems of interacting players maximizing their individual payoffs and particles minimizing their interaction energy. We use concepts and techniques of statistical mechanics to study game-theoretic models. In order to obtain results in the case of the so-called potential games, we analyse the thermodynamic limit of the appropriate models of interacting particles

Eco-evolutionary feedback and the invasion of cooperation in prisoner's dilemma games.

Directory of Open Access Journals (Sweden)

Feng Zhang

Full Text Available Unveiling the origin and forms of cooperation in nature poses profound challenges in evolutionary ecology. The prisoner's dilemma game is an important metaphor for studying the evolution of cooperation. We here classified potential mechanisms for cooperation evolution into schemes of frequency- and density-dependent selection, and focused on the density-dependent selection in the ecological prisoner's dilemma games. We found that, although assortative encounter is still the necessary condition in ecological games for cooperation evolution, a harsh environment, indicated by a high mortality, can foster the invasion of cooperation. The Hamilton rule provides a fundamental condition for the evolution of cooperation by ensuring an enhanced relatedness between players in low-density populations. Incorporating ecological dynamics into evolutionary games opens up a much wider window for the evolution of cooperation, and exhibits a variety of complex behaviors of dynamics, such as limit and heteroclinic cycles. An alternative evolutionary, or rather succession, sequence was proposed that cooperation first appears in harsh environments, followed by the invasion of defection, which leads to a common catastrophe. The rise of cooperation (and altruism, thus, could be much easier in the density-dependent ecological games than in the classic frequency-dependent evolutionary games.

Co-Evolution of Opinion and Strategy in Persuasion Dynamics:. AN Evolutionary Game Theoretical Approach

Science.gov (United States)

Ding, Fei; Liu, Yun; Li, Yong

In this paper, a new model of opinion formation within the framework of evolutionary game theory is presented. The model simulates strategic situations when people are in opinion discussion. Heterogeneous agents adjust their behaviors to the environment during discussions, and their interacting strategies evolve together with opinions. In the proposed game, we take into account payoff discount to join a discussion, and the situation that people might drop out of an unpromising game. Analytical and emulational results show that evolution of opinion and strategy always tend to converge, with utility threshold, memory length, and decision uncertainty parameters influencing the convergence time. The model displays different dynamical regimes when we set differently the rule when people are at a loss in strategy.

Bridging the gap between Schumpeterian competition and evolutionary game theory

DEFF Research Database (Denmark)

Andersen, Esben Sloth

This paper suggests that the analysis of Schumpeterian competition within the Nelson-Winter model should be complemented with evolutionary game theory. This model and its limitations for density-dependent Schumpeterian strategies are presented in terms of the equations of evolutionary dynamics. F...

A dynamic parking charge optimal control model under perspective of commuters' evolutionary game behavior

Science.gov (United States)

Lin, XuXun; Yuan, PengCheng

2018-01-01

In this research we consider commuters' dynamic learning effect by modeling the trip mode choice behavior from a new perspective of dynamic evolutionary game theory. We explore the behavior pattern of different types of commuters and study the evolution path and equilibrium properties under different traffic conditions. We further establish a dynamic parking charge optimal control (referred to as DPCOC) model to alter commuters' trip mode choice while minimizing the total social cost. Numerical tests show. (1) Under fixed parking fee policy, the evolutionary results are completely decided by the travel time and the only method for public transit induction is to increase the parking charge price. (2) Compared with fixed parking fee policy, DPCOC policy proposed in this research has several advantages. Firstly, it can effectively turn the evolutionary path and evolutionary stable strategy to a better situation while minimizing the total social cost. Secondly, it can reduce the sensitivity of trip mode choice behavior to traffic congestion and improve the ability to resist interferences and emergencies. Thirdly, it is able to control the private car proportion to a stable state and make the trip behavior more predictable for the transportation management department. The research results can provide theoretical basis and decision-making references for commuters' mode choice prediction, dynamic setting of urban parking charge prices and public transit induction.

Large fluctuations and fixation in evolutionary games

International Nuclear Information System (INIS)

Assaf, Michael; Mobilia, Mauro

2010-01-01

We study large fluctuations in evolutionary games belonging to the coordination and anti-coordination classes. The dynamics of these games, modeling cooperation dilemmas, is characterized by a coexistence fixed point separating two absorbing states. We are particularly interested in the problem of fixation that refers to the possibility that a few mutants take over the entire population. Here, the fixation phenomenon is induced by large fluctuations and is investigated by a semiclassical WKB (Wentzel–Kramers–Brillouin) theory generalized to treat stochastic systems possessing multiple absorbing states. Importantly, this method allows us to analyze the combined influence of selection and random fluctuations on the evolutionary dynamics beyond the weak selection limit often considered in previous works. We accurately compute, including pre-exponential factors, the probability distribution function in the long-lived coexistence state and the mean fixation time necessary for a few mutants to take over the entire population in anti-coordination games, and also the fixation probability in the coordination class. Our analytical results compare excellently with extensive numerical simulations. Furthermore, we demonstrate that our treatment is superior to the Fokker–Planck approximation when the selection intensity is finite

On evolutionary ray-projection dynamics

NARCIS (Netherlands)

Joosten, Reinoud A.M.G.; Roorda, Berend

2011-01-01

We introduce the ray-projection dynamics in evolutionary game theory by employing a ray projection of the relative fitness (vector) function, i.e., a projection unto the unit simplex along a ray through the origin. Ray-projection dynamics are weakly compatible in the terminology of Friedman

Calculating evolutionary dynamics in structured populations.

Directory of Open Access Journals (Sweden)

Charles G Nathanson

2009-12-01

Full Text Available Evolution is shaping the world around us. At the core of every evolutionary process is a population of reproducing individuals. The outcome of an evolutionary process depends on population structure. Here we provide a general formula for calculating evolutionary dynamics in a wide class of structured populations. This class includes the recently introduced "games in phenotype space" and "evolutionary set theory." There can be local interactions for determining the relative fitness of individuals, but we require global updating, which means all individuals compete uniformly for reproduction. We study the competition of two strategies in the context of an evolutionary game and determine which strategy is favored in the limit of weak selection. We derive an intuitive formula for the structure coefficient, sigma, and provide a method for efficient numerical calculation.

Multiscale structure in eco-evolutionary dynamics

Science.gov (United States)

Stacey, Blake C.

In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.

Why Darwin would have loved evolutionary game theory.

Science.gov (United States)

Brown, Joel S

2016-09-14

Humans have marvelled at the fit of form and function, the way organisms' traits seem remarkably suited to their lifestyles and ecologies. While natural selection provides the scientific basis for the fit of form and function, Darwin found certain adaptations vexing or particularly intriguing: sex ratios, sexual selection and altruism. The logic behind these adaptations resides in frequency-dependent selection where the value of a given heritable phenotype (i.e. strategy) to an individual depends upon the strategies of others. Game theory is a branch of mathematics that is uniquely suited to solving such puzzles. While game theoretic thinking enters into Darwin's arguments and those of evolutionists through much of the twentieth century, the tools of evolutionary game theory were not available to Darwin or most evolutionists until the 1970s, and its full scope has only unfolded in the last three decades. As a consequence, game theory is applied and appreciated rather spottily. Game theory not only applies to matrix games and social games, it also applies to speciation, macroevolution and perhaps even to cancer. I assert that life and natural selection are a game, and that game theory is the appropriate logic for framing and understanding adaptations. Its scope can include behaviours within species, state-dependent strategies (such as male, female and so much more), speciation and coevolution, and expands beyond microevolution to macroevolution. Game theory clarifies aspects of ecological and evolutionary stability in ways useful to understanding eco-evolutionary dynamics, niche construction and ecosystem engineering. In short, I would like to think that Darwin would have found game theory uniquely useful for his theory of natural selection. Let us see why this is so. © 2016 The Author(s).

Adaptive Topographies and Equilibrium Selection in an Evolutionary Game

Science.gov (United States)

Osinga, Hinke M.; Marshall, James A. R.

2015-01-01

It has long been known in the field of population genetics that adaptive topographies, in which population equilibria maximise mean population fitness for a trait regardless of its genetic bases, do not exist. Whether one chooses to model selection acting on a single locus or multiple loci does matter. In evolutionary game theory, analysis of a simple and general game involving distinct roles for the two players has shown that whether strategies are modelled using a single ‘locus’ or one ‘locus’ for each role, the stable population equilibria are unchanged and correspond to the fitness-maximising evolutionary stable strategies of the game. This is curious given the aforementioned population genetical results on the importance of the genetic bases of traits. Here we present a dynamical systems analysis of the game with roles detailing how, while the stable equilibria in this game are unchanged by the number of ‘loci’ modelled, equilibrium selection may differ under the two modelling approaches. PMID:25706762

Ecological theatre and the evolutionary game: how environmental and demographic factors determine payoffs in evolutionary games.

Science.gov (United States)

Argasinski, K; Broom, M

2013-10-01

In the standard approach to evolutionary games and replicator dynamics, differences in fitness can be interpreted as an excess from the mean Malthusian growth rate in the population. In the underlying reasoning, related to an analysis of "costs" and "benefits", there is a silent assumption that fitness can be described in some type of units. However, in most cases these units of measure are not explicitly specified. Then the question arises: are these theories testable? How can we measure "benefit" or "cost"? A natural language, useful for describing and justifying comparisons of strategic "cost" versus "benefits", is the terminology of demography, because the basic events that shape the outcome of natural selection are births and deaths. In this paper, we present the consequences of an explicit analysis of births and deaths in an evolutionary game theoretic framework. We will investigate different types of mortality pressures, their combinations and the possibility of trade-offs between mortality and fertility. We will show that within this new approach it is possible to model how strictly ecological factors such as density dependence and additive background fitness, which seem neutral in classical theory, can affect the outcomes of the game. We consider the example of the Hawk-Dove game, and show that when reformulated in terms of our new approach new details and new biological predictions are produced.

Population Games, Stable Games, and Passivity

Directory of Open Access Journals (Sweden)

Michael J. Fox

2013-10-01

Full Text Available The class of “stable games”, introduced by Hofbauer and Sandholm in 2009, has the attractive property of admitting global convergence to equilibria under many evolutionary dynamics. We show that stable games can be identified as a special case of the feedback-system-theoretic notion of a “passive” dynamical system. Motivated by this observation, we develop a notion of passivity for evolutionary dynamics that complements the definition of the class of stable games. Since interconnections of passive dynamical systems exhibit stable behavior, we can make conclusions about passive evolutionary dynamics coupled with stable games. We show how established evolutionary dynamics qualify as passive dynamical systems. Moreover, we exploit the flexibility of the definition of passive dynamical systems to analyze generalizations of stable games and evolutionary dynamics that include forecasting heuristics as well as certain games with memory.

Research on Information Sharing Mechanism of Network Organization Based on Evolutionary Game

Science.gov (United States)

Wang, Lin; Liu, Gaozhi

2018-02-01

This article first elaborates the concept and effect of network organization, and the ability to share information is analyzed, secondly introduces the evolutionary game theory, network organization for information sharing all kinds of limitations, establishes the evolutionary game model, analyzes the dynamic evolution of network organization of information sharing, through reasoning and evolution. The network information sharing by the initial state and two sides of the game payoff matrix of excess profits and information is the information sharing of cost and risk sharing are the influence of network organization node information sharing decision.

Cyclic dominance in evolutionary games: a review

Science.gov (United States)

Szolnoki, Attila; Mobilia, Mauro; Jiang, Luo-Luo; Szczesny, Bartosz; Rucklidge, Alastair M.; Perc, Matjaž

2014-01-01

Rock is wrapped by paper, paper is cut by scissors and scissors are crushed by rock. This simple game is popular among children and adults to decide on trivial disputes that have no obvious winner, but cyclic dominance is also at the heart of predator–prey interactions, the mating strategy of side-blotched lizards, the overgrowth of marine sessile organisms and competition in microbial populations. Cyclical interactions also emerge spontaneously in evolutionary games entailing volunteering, reward, punishment, and in fact are common when the competing strategies are three or more, regardless of the particularities of the game. Here, we review recent advances on the rock–paper–scissors (RPS) and related evolutionary games, focusing, in particular, on pattern formation, the impact of mobility and the spontaneous emergence of cyclic dominance. We also review mean-field and zero-dimensional RPS models and the application of the complex Ginzburg–Landau equation, and we highlight the importance and usefulness of statistical physics for the successful study of large-scale ecological systems. Directions for future research, related, for example, to dynamical effects of coevolutionary rules and invasion reversals owing to multi-point interactions, are also outlined. PMID:25232048

A system dynamics model based on evolutionary game theory for green supply chain management diffusion among Chinese manufacturers

DEFF Research Database (Denmark)

Tian, Yihui; Govindan, Kannan; Zhu, Qinghua

2014-01-01

In this study, a system dynamics (SD) model is developed to guide the subsidy policies to promote the diffusion of green supply chain management (GSCM) in China. The relationships of stakeholders such as government, enterprises and consumers are analyzed through evolutionary game theory. Finally...

Aspiration dynamics of multi-player games in finite populations.

Science.gov (United States)

Du, Jinming; Wu, Bin; Altrock, Philipp M; Wang, Long

2014-05-06

On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics.

Heterogeneous update mechanisms in evolutionary games: Mixing innovative and imitative dynamics

Science.gov (United States)

Amaral, Marco Antonio; Javarone, Marco Alberto

2018-04-01

Innovation and evolution are two processes of paramount relevance for social and biological systems. In general, the former allows the introduction of elements of novelty, while the latter is responsible for the motion of a system in its phase space. Often, these processes are strongly related, since an innovation can trigger the evolution, and the latter can provide the optimal conditions for the emergence of innovations. Both processes can be studied by using the framework of evolutionary game theory, where evolution constitutes an intrinsic mechanism. At the same time, the concept of innovation requires an opportune mathematical representation. Notably, innovation can be modeled as a strategy, or it can constitute the underlying mechanism that allows agents to change strategy. Here, we analyze the second case, investigating the behavior of a heterogeneous population, composed of imitative and innovative agents. Imitative agents change strategy only by imitating that of their neighbors, whereas innovative ones change strategy without the need for a copying source. The proposed model is analyzed by means of analytical calculations and numerical simulations in different topologies. Remarkably, results indicate that the mixing of mechanisms can be detrimental to cooperation near phase transitions. In those regions, the spatial reciprocity from imitative mechanisms is destroyed by innovative agents, leading to the downfall of cooperation. Our investigation sheds some light on the complex dynamics emerging from the heterogeneity of strategy revision methods, highlighting the role of innovation in evolutionary games.

Unfair and Anomalous Evolutionary Dynamics from Fluctuating Payoffs

Science.gov (United States)

Stollmeier, Frank; Nagler, Jan

2018-02-01

Evolution occurs in populations of reproducing individuals. Reproduction depends on the payoff a strategy receives. The payoff depends on the environment that may change over time, on intrinsic uncertainties, and on other sources of randomness. These temporal variations in the payoffs can affect which traits evolve. Understanding evolutionary game dynamics that are affected by varying payoffs remains difficult. Here we study the impact of arbitrary amplitudes and covariances of temporally varying payoffs on the dynamics. The evolutionary dynamics may be "unfair," meaning that, on average, two coexisting strategies may persistently receive different payoffs. This mechanism can induce an anomalous coexistence of cooperators and defectors in the prisoner's dilemma, and an unexpected selection reversal in the hawk-dove game.

On economic applications of evolutionary game theory

OpenAIRE

Daniel Friedman

1998-01-01

Evolutionary games have considerable unrealized potential for modeling substantive economic issues. They promise richer predictions than orthodox game models but often require more extensive specifications. This paper exposits the specification of evolutionary game models and classifies the possible asymptotic behavior for one and two dimensional models.

A network growth model based on the evolutionary ultimatum game

International Nuclear Information System (INIS)

Deng, L L; Zhou, G G; Cai, J H; Wang, C; Tang, W S

2012-01-01

In this paper, we provide a network growth model with incorporation into the ultimatum game dynamics. The network grows on the basis of the payoff-oriented preferential attachment mechanism, where a new node is added into the network and attached preferentially to nodes with higher payoffs. The interplay between the network growth and the game dynamics gives rise to quite interesting dynamical behaviors. Simulation results show the emergence of altruistic behaviors in the ultimatum game, which is affected by the growing network structure. Compared with the static counterpart case, the levels of altruistic behaviors are promoted. The corresponding strategy distributions and wealth distributions are also presented to further demonstrate the strategy evolutionary dynamics. Subsequently, we turn to the topological properties of the evolved network, by virtue of some statistics. The most studied characteristic path length and the clustering coefficient of the network are shown to indicate their small-world effect. Then the degree distributions are analyzed to clarify the interplay of structure and evolutionary dynamics. In particular, the difference between our growth network and the static counterpart is revealed. To explain clearly the evolved networks, the rich-club ordering and the assortative mixing coefficient are exploited to reveal the degree correlation. (paper)

Dynamics in atomic signaling games

KAUST Repository

Fox, Michael J.

2015-04-08

We study an atomic signaling game under stochastic evolutionary dynamics. There are a finite number of players who repeatedly update from a finite number of available languages/signaling strategies. Players imitate the most fit agents with high probability or mutate with low probability. We analyze the long-run distribution of states and show that, for sufficiently small mutation probability, its support is limited to efficient communication systems. We find that this behavior is insensitive to the particular choice of evolutionary dynamic, a property that is due to the game having a potential structure with a potential function corresponding to average fitness. Consequently, the model supports conclusions similar to those found in the literature on language competition. That is, we show that efficient languages eventually predominate the society while reproducing the empirical phenomenon of linguistic drift. The emergence of efficiency in the atomic case can be contrasted with results for non-atomic signaling games that establish the non-negligible possibility of convergence, under replicator dynamics, to states of unbounded efficiency loss.

Dynamics in atomic signaling games

KAUST Repository

Fox, Michael J.; Touri, Behrouz; Shamma, Jeff S.

2015-01-01

We study an atomic signaling game under stochastic evolutionary dynamics. There are a finite number of players who repeatedly update from a finite number of available languages/signaling strategies. Players imitate the most fit agents with high probability or mutate with low probability. We analyze the long-run distribution of states and show that, for sufficiently small mutation probability, its support is limited to efficient communication systems. We find that this behavior is insensitive to the particular choice of evolutionary dynamic, a property that is due to the game having a potential structure with a potential function corresponding to average fitness. Consequently, the model supports conclusions similar to those found in the literature on language competition. That is, we show that efficient languages eventually predominate the society while reproducing the empirical phenomenon of linguistic drift. The emergence of efficiency in the atomic case can be contrasted with results for non-atomic signaling games that establish the non-negligible possibility of convergence, under replicator dynamics, to states of unbounded efficiency loss.

Evolutionary dynamics on graphs: Efficient method for weak selection

Science.gov (United States)

Fu, Feng; Wang, Long; Nowak, Martin A.; Hauert, Christoph

2009-04-01

Investigating the evolutionary dynamics of game theoretical interactions in populations where individuals are arranged on a graph can be challenging in terms of computation time. Here, we propose an efficient method to study any type of game on arbitrary graph structures for weak selection. In this limit, evolutionary game dynamics represents a first-order correction to neutral evolution. Spatial correlations can be empirically determined under neutral evolution and provide the basis for formulating the game dynamics as a discrete Markov process by incorporating a detailed description of the microscopic dynamics based on the neutral correlations. This framework is then applied to one of the most intriguing questions in evolutionary biology: the evolution of cooperation. We demonstrate that the degree heterogeneity of a graph impedes cooperation and that the success of tit for tat depends not only on the number of rounds but also on the degree of the graph. Moreover, considering the mutation-selection equilibrium shows that the symmetry of the stationary distribution of states under weak selection is skewed in favor of defectors for larger selection strengths. In particular, degree heterogeneity—a prominent feature of scale-free networks—generally results in a more pronounced increase in the critical benefit-to-cost ratio required for evolution to favor cooperation as compared to regular graphs. This conclusion is corroborated by an analysis of the effects of population structures on the fixation probabilities of strategies in general 2×2 games for different types of graphs. Computer simulations confirm the predictive power of our method and illustrate the improved accuracy as compared to previous studies.

Exploring social influence on evolutionary prisoner’s dilemma games in networks

Science.gov (United States)

Zong, Hengshan; Jia, Guozhu; Cheng, Yang

2015-11-01

Though numerous studies demonstrate the importance of social influence in deciding individual decision-making process in networks, little has been done to explore its impact on players’ behavioral patterns in evolutionary prisoner’s dilemma games (PDGs). This study investigates how social influenced strategy updating rules may affect the final equilibrium of game dynamics. The results show that weak social influence usually inhibits cooperation, while strong social influence has a mediating effect. The impacts of network structure and the existence of rebels in social influence scenarios are also tested. The paper provides a comprehensive interpretation on social influence effects on evolutionary PDGs in networks.

Evolutionary game theory: cells as players.

Science.gov (United States)

Hummert, Sabine; Bohl, Katrin; Basanta, David; Deutsch, Andreas; Werner, Sarah; Theissen, Günter; Schroeter, Anja; Schuster, Stefan

2014-12-01

In two papers we review game theory applications in biology below the level of cognitive living beings. It can be seen that evolution and natural selection replace the rationality of the actors appropriately. Even in these micro worlds, competing situations and cooperative relationships can be found and modeled by evolutionary game theory. Also those units of the lowest levels of life show different strategies for different environmental situations or different partners. We give a wide overview of evolutionary game theory applications to microscopic units. In this first review situations on the cellular level are tackled. In particular metabolic problems are discussed, such as ATP-producing pathways, secretion of public goods and cross-feeding. Further topics are cyclic competition among more than two partners, intra- and inter-cellular signalling, the struggle between pathogens and the immune system, and the interactions of cancer cells. Moreover, we introduce the theoretical basics to encourage scientists to investigate problems in cell biology and molecular biology by evolutionary game theory.

Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

Science.gov (United States)

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

Evidence Combination From an Evolutionary Game Theory Perspective.

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Deng, Xinyang; Han, Deqiang; Dezert, Jean; Deng, Yong; Shyr, Yu

2016-09-01

Dempster-Shafer evidence theory is a primary methodology for multisource information fusion because it is good at dealing with uncertain information. This theory provides a Dempster's rule of combination to synthesize multiple evidences from various information sources. However, in some cases, counter-intuitive results may be obtained based on that combination rule. Numerous new or improved methods have been proposed to suppress these counter-intuitive results based on perspectives, such as minimizing the information loss or deviation. Inspired by evolutionary game theory, this paper considers a biological and evolutionary perspective to study the combination of evidences. An evolutionary combination rule (ECR) is proposed to help find the most biologically supported proposition in a multievidence system. Within the proposed ECR, we develop a Jaccard matrix game to formalize the interaction between propositions in evidences, and utilize the replicator dynamics to mimick the evolution of propositions. Experimental results show that the proposed ECR can effectively suppress the counter-intuitive behaviors appeared in typical paradoxes of evidence theory, compared with many existing methods. Properties of the ECR, such as solution's stability and convergence, have been mathematically proved as well.

Multiparty Evolutionary Game Model in Coal Mine Safety Management and Its Application

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Rongwu Lu

2018-01-01

Full Text Available Coal mine safety management involves many interested parties and there are complex relationships between them. According to game theory, a multiparty evolutionary game model is established to analyze the selection of strategies. Then, a simplified three-party model is taken as an example to carry out detailed analysis and solution. Based on stability theory of dynamics system and phase diagram analysis, this article studies replicator dynamics of the evolutionary model to make an optimization analysis of the behaviors of those interested parties and the adjustment mechanism of safety management policies and decisions. The results show how the charge of supervision of government department and inspection of coal mine enterprise impact the efficiency of safety management and the effect of constraint measures and incentive and other measures in safety management.

Applying Evolutionary Psychology to a Serious Game about Children's Interpersonal Conflict

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Gordon P. D. Ingram

2012-12-01

Full Text Available This article describes the use of evolutionary psychology to inform the design of a serious computer game aimed at improving 9–12-year-old children's conflict resolution skills. The design of the game will include dynamic narrative generation and emotional tagging, and there is a strong evolutionary rationale for the effect of both of these on conflict resolution. Gender differences will also be taken into consideration in designing the game. In interview research in schools in three countries (Greece, Portugal, and the UK aimed at formalizing the game requirements, we found that gender differences varied in the extent to which they applied cross-culturally. Across the three countries, girls were less likely to talk about responding to conflict with physical aggression, talked more about feeling sad about conflict and about conflicts over friendship alliances, and talked less about conflicts in the context of sports or games. Predicted gender differences in anger and reconciliation were not found. Results are interpreted in terms of differing underlying models of friendship that are motivated by parental investment theory. This research will inform the design of the themes that we use in game scenarios for both girls and boys.

Applying evolutionary psychology to a serious game about children's interpersonal conflict.

Science.gov (United States)

Ingram, Gordon P D; Campos, Joana; Hondrou, Charline; Vasalou, Asimina; Martinho, Carlos; Joinson, Adam

2012-12-20

This article describes the use of evolutionary psychology to inform the design of a serious computer game aimed at improving 9-12-year-old children's conflict resolution skills. The design of the game will include dynamic narrative generation and emotional tagging, and there is a strong evolutionary rationale for the effect of both of these on conflict resolution. Gender differences will also be taken into consideration in designing the game. In interview research in schools in three countries (Greece, Portugal, and the UK) aimed at formalizing the game requirements, we found that gender differences varied in the extent to which they applied cross-culturally. Across the three countries, girls were less likely to talk about responding to conflict with physical aggression, talked more about feeling sad about conflict and about conflicts over friendship alliances, and talked less about conflicts in the context of sports or games. Predicted gender differences in anger and reconciliation were not found. Results are interpreted in terms of differing underlying models of friendship that are motivated by parental investment theory. This research will inform the design of the themes that we use in game scenarios for both girls and boys.

Games of life and death: antibiotic resistance and production through the lens of evolutionary game theory.

Science.gov (United States)

Conlin, Peter L; Chandler, Josephine R; Kerr, Benjamin

2014-10-01

In this review, we demonstrate how game theory can be a useful first step in modeling and understanding interactions among bacteria that produce and resist antibiotics. We introduce the basic features of evolutionary game theory and explore model microbial systems that correspond to some classical games. Each game discussed defines a different category of social interaction with different resulting population dynamics (exclusion, coexistence, bistability, cycling). We then explore how the framework can be extended to incorporate some of the complexity of natural microbial communities. Overall, the game theoretical perspective helps to guide our expectations about the evolution of some forms of antibiotic resistance and production because it makes clear the precise nature of social interaction in this context. Copyright © 2014 Elsevier Ltd. All rights reserved.

THE THEORY OF THE FIRM AND THE EVOLUTIONARY GAMES

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Sirghi Nicoleta

2013-07-01

Full Text Available The neoclassical theory of the firm deals with the pattern of perfect competition, within which the perfect information available to economic agents provides instant allocation of production factors and access to economic goods. The Austrian School (C. Menger, L. von Mises, Hayek, etc. supported the idea of minimal state intervention on the markets, bringing important conceptual developments on the theory of the firm. Hirschleifer (1982 put forward the model of social and institutional functioning, arguing that the game theory is able to predict the outcome of the collective behavior and the human characteristics necessary for building the respective institutions.The evolutionary theory provides the firm and the entrepreneur the recognition of the functions of innovation, of generating and exploiting information and of organizing and coordinating production. The evolutionary perspective of the firm assumes the existence of a body of knowledge that is acquired through and builds up the organizational memory, subsequently found in routines, all choices being made based on these routines (Nelson and Winter, 2002. The evolution of the firm is considered to be similar to natural selection, but unlike the classic market selection, the evolutionists suggest the existence of a plurality of selection media. The present research is structured as follows: a brief introduction into the theories of the firm, the second part of the paper analyzes the theories of the firm from an institutional, neo-institutional and evolutionary perspective. In the third part of the paper the evolutionary games are described and analyzed from the evolutionary perspective of the firm. The last part of the paper represents a study of the “hawk-dove” game dynamic replicator. The final conclusions of the paper show that the evolutionary theory brings valuable contributions to the foundation of explanations regarding economic phenomena, indicating new directions for advanced

Cooperative Evolutionary Game and Applications in Construction Supplier Tendency

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Qianqian Shi

2018-01-01

Full Text Available Major construction projects have a great influence on the national economy and society, wherein cooperative relationship between construction suppliers plays an increasingly significant role in the overall supply chain system. However, the relationships between suppliers are noncontractual, multistage, dynamic, and complicated. To gain a deeper insight into the suppliers’ cooperative relationships, an evolutionary game model is developed to explore the cooperation tendency of multisuppliers. A replicator dynamic system is further formulated to investigate the evolutionary stable strategies of multisuppliers. Then, fourteen “when-then” type scenarios are concluded and classified into six different evolutionary tracks. Meanwhile, the critical influencing factors are identified. The results show that the suppliers’ production capacity, owner-supplier contract, and the owner’s incentive mechanism influence the cooperation tendency of suppliers directly. The managerial implications contribute to insightful references for a more stable cooperative relationship between the owner and suppliers.

Extrapolating Weak Selection in Evolutionary Games

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Wu, Bin; García, Julián; Hauert, Christoph; Traulsen, Arne

2013-01-01

In evolutionary games, reproductive success is determined by payoffs. Weak selection means that even large differences in game outcomes translate into small fitness differences. Many results have been derived using weak selection approximations, in which perturbation analysis facilitates the derivation of analytical results. Here, we ask whether results derived under weak selection are also qualitatively valid for intermediate and strong selection. By “qualitatively valid” we mean that the ranking of strategies induced by an evolutionary process does not change when the intensity of selection increases. For two-strategy games, we show that the ranking obtained under weak selection cannot be carried over to higher selection intensity if the number of players exceeds two. For games with three (or more) strategies, previous examples for multiplayer games have shown that the ranking of strategies can change with the intensity of selection. In particular, rank changes imply that the most abundant strategy at one intensity of selection can become the least abundant for another. We show that this applies already to pairwise interactions for a broad class of evolutionary processes. Even when both weak and strong selection limits lead to consistent predictions, rank changes can occur for intermediate intensities of selection. To analyze how common such games are, we show numerically that for randomly drawn two-player games with three or more strategies, rank changes frequently occur and their likelihood increases rapidly with the number of strategies . In particular, rank changes are almost certain for , which jeopardizes the predictive power of results derived for weak selection. PMID:24339769

Evolutionary game dynamics of controlled and automatic decision-making.

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Toupo, Danielle F P; Strogatz, Steven H; Cohen, Jonathan D; Rand, David G

2015-07-01

We integrate dual-process theories of human cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model in which agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions in which having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and human cognition and suggest necessary conditions for the rise and fall of rationality.

Evolutionary game dynamics of controlled and automatic decision-making

Science.gov (United States)

Toupo, Danielle F. P.; Strogatz, Steven H.; Cohen, Jonathan D.; Rand, David G.

2015-07-01

We integrate dual-process theories of human cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model in which agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions in which having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and human cognition and suggest necessary conditions for the rise and fall of rationality.

An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

Science.gov (United States)

Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano

2017-11-22

Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.

Some Analytical Properties of the Model for Stochastic Evolutionary Games in Finite Populations with Non-uniform Interaction Rate

International Nuclear Information System (INIS)

Quan Ji; Wang Xianjia

2013-01-01

Traditional evolutionary games assume uniform interaction rate, which means that the rate at which individuals meet and interact is independent of their strategies. But in some systems, especially biological systems, the players interact with each other discriminately. Taylor and Nowak (2006) were the first to establish the corresponding non-uniform interaction rate model by allowing the interaction rates to depend on strategies. Their model is based on replicator dynamics which assumes an infinite size population. But in reality, the number of individuals in the population is always finite, and there will be some random interference in the individuals' strategy selection process. Therefore, it is more practical to establish the corresponding stochastic evolutionary model in finite populations. In fact, the analysis of evolutionary games in a finite size population is more difficult. Just as Taylor and Nowak said in the outlook section of their paper, ''The analysis of non-uniform interaction rates should be extended to stochastic game dynamics of finite populations''. In this paper, we are exactly doing this work. We extend Taylor and Nowak's model from infinite to finite case, especially focusing on the infiuence of non-uniform connection characteristics on the evolutionary stable state of the system. We model the strategy evolutionary process of the population by a continuous ergodic Markov process. Based on the limit distribution of the process, we can give the evolutionary stable state of the system. We make a complete classification of the symmetric 2 × 2 games. For each case game, the corresponding limit distribution of the Markov-based process is given when noise intensity is small enough. In contrast with most literatures in evolutionary games using the simulation method, all our results obtained are analytical. Especially, in the dominant-case game, coexistence of the two strategies may become evolutionary stable states in our model. This result can be

The stability concept of evolutionary game theory a dynamic approach

CERN Document Server

1992-01-01

These Notes grew from my research in evolutionary biology, specifically on the theory of evolutionarily stable strategies (ESS theory), over the past ten years. Personally, evolutionary game theory has given me the opportunity to transfer my enthusiasm for abstract mathematics to more practical pursuits. I was fortunate to have entered this field in its infancy when many biologists recognized its potential but were not prepared to grant it general acceptance. This is no longer the case. ESS theory is now a rapidly expanding (in both applied and theoretical directions) force that no evolutionary biologist can afford to ignore. Perhaps, to continue the life-cycle metaphor, ESS theory is now in its late adolescence and displays much of the optimism and exuberance of this exciting age. There are dangers in writing a text about a theory at this stage of development. A comprehensive treatment would involve too many loose ends for the reader to appreciate the central message. On the other hand, the current central m...

Evolutionary competition between boundedly rational behavioral rules in oligopoly games

International Nuclear Information System (INIS)

Cerboni Baiardi, Lorenzo; Lamantia, Fabio; Radi, Davide

2015-01-01

In this paper, we propose an evolutionary model of oligopoly competition where agents can select between different behavioral rules to make decisions on productions. We formalize the model as a general class of evolutionary oligopoly games and then we consider an example with two specific rules, namely Local Monopolistic Approximation and Gradient dynamics. We provide several results on the global dynamic properties of the model, showing that in some cases the attractor of the system may belong to an invariant plane where only one behavioral rule is adopted (monomorphic state). The attractors on the invariant planes can be either strong attractors or weak attractors. However, we also explain why the system can be in a state of Evolutionary Stable Heterogeneity, where it is more profitable for the agents to employ both heuristics in the long term (polymorphic state).

The puzzle of partial migration: Adaptive dynamics and evolutionary game theory perspectives.

Science.gov (United States)

De Leenheer, Patrick; Mohapatra, Anushaya; Ohms, Haley A; Lytle, David A; Cushing, J M

2017-01-07

We consider the phenomenon of partial migration which is exhibited by populations in which some individuals migrate between habitats during their lifetime, but others do not. First, using an adaptive dynamics approach, we show that partial migration can be explained on the basis of negative density dependence in the per capita fertilities alone, provided that this density dependence is attenuated for increasing abundances of the subtypes that make up the population. We present an exact formula for the optimal proportion of migrants which is expressed in terms of the vital rates of migrant and non-migrant subtypes only. We show that this allocation strategy is both an evolutionary stable strategy (ESS) as well as a convergence stable strategy (CSS). To establish the former, we generalize the classical notion of an ESS because it is based on invasion exponents obtained from linearization arguments, which fail to capture the stabilizing effects of the nonlinear density dependence. These results clarify precisely when the notion of a "weak ESS", as proposed in Lundberg (2013) for a related model, is a genuine ESS. Secondly, we use an evolutionary game theory approach, and confirm, once again, that partial migration can be attributed to negative density dependence alone. In this context, the result holds even when density dependence is not attenuated. In this case, the optimal allocation strategy towards migrants is the same as the ESS stemming from the analysis based on the adaptive dynamics. The key feature of the population models considered here is that they are monotone dynamical systems, which enables a rather comprehensive mathematical analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

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Zhu, Xuli; Jiang, Libo; Ye, Meixia; Sun, Lidan; Gragnoli, Claudia; Wu, Rongling

2016-05-01

Natural selection has shaped the evolution of organisms toward optimizing their structural and functional design. However, how this universal principle can enhance genotype-phenotype mapping of quantitative traits has remained unexplored. Here we show that the integration of this principle and functional mapping through evolutionary game theory gains new insight into the genetic architecture of complex traits. By viewing phenotype formation as an evolutionary system, we formulate mathematical equations to model the ecological mechanisms that drive the interaction and coordination of its constituent components toward population dynamics and stability. Functional mapping provides a procedure for estimating the genetic parameters that specify the dynamic relationship of competition and cooperation and predicting how genes mediate the evolution of this relationship during trait formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Continual Online Evolutionary Planning for In-Game Build Order Adaptation in StarCraft

DEFF Research Database (Denmark)

Justesen, Niels Orsleff; Risi, Sebastian

2017-01-01

able to switch between predefined strategies, which makes it hard to adapt to new situations. This paper introduces an evolutionary-based method to overcome this challenge, called Continual Online Evolutionary Planning (COEP), which is able to perform in-game adaptive build-order planning. COEP......The real-time strategy game StarCraft has become an important benchmark for AI research as it poses a complex environment with numerous challenges. An important strategic aspect in this game is to decide what buildings and units to produce. StarCraft bots playing in AI competitions today are only...... was added to an open source StarCraft bot called UAlbertaBot and is able to outperform the built-in bots in the game as well as being competitive against a number of scripted opening strategies. The COEP augmented bot can change its build order dynamically and quickly adapt to the opponent’s strategy....

Statistical physics and computational methods for evolutionary game theory

CERN Document Server

Javarone, Marco Alberto

2018-01-01

This book presents an introduction to Evolutionary Game Theory (EGT) which is an emerging field in the area of complex systems attracting the attention of researchers from disparate scientific communities. EGT allows one to represent and study several complex phenomena, such as the emergence of cooperation in social systems, the role of conformity in shaping the equilibrium of a population, and the dynamics in biological and ecological systems. Since EGT models belong to the area of complex systems, statistical physics constitutes a fundamental ingredient for investigating their behavior. At the same time, the complexity of some EGT models, such as those realized by means of agent-based methods, often require the implementation of numerical simulations. Therefore, beyond providing an introduction to EGT, this book gives a brief overview of the main statistical physics tools (such as phase transitions and the Ising model) and computational strategies for simulating evolutionary games (such as Monte Carlo algor...

Application of evolutionary games to modeling carcinogenesis.

Science.gov (United States)

Swierniak, Andrzej; Krzeslak, Michal

2013-06-01

We review a quite large volume of literature concerning mathematical modelling of processes related to carcinogenesis and the growth of cancer cell populations based on the theory of evolutionary games. This review, although partly idiosyncratic, covers such major areas of cancer-related phenomena as production of cytotoxins, avoidance of apoptosis, production of growth factors, motility and invasion, and intra- and extracellular signaling. We discuss the results of other authors and append to them some additional results of our own simulations dealing with the possible dynamics and/or spatial distribution of the processes discussed.

Evolutionary Game Theory Analysis of Tumor Progression

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Wu, Amy; Liao, David; Sturm, James; Austin, Robert

2014-03-01

Evolutionary game theory applied to two interacting cell populations can yield quantitative prediction of the future densities of the two cell populations based on the initial interaction terms. We will discuss how in a complex ecology that evolutionary game theory successfully predicts the future densities of strains of stromal and cancer cells (multiple myeloma), and discuss the possible clinical use of such analysis for predicting cancer progression. Supported by the National Science Foundation and the National Cancer Institute.

Study on system dynamics of evolutionary mix-game models

Science.gov (United States)

Gou, Chengling; Guo, Xiaoqian; Chen, Fang

2008-11-01

Mix-game model is ameliorated from an agent-based MG model, which is used to simulate the real financial market. Different from MG, there are two groups of agents in Mix-game: Group 1 plays a majority game and Group 2 plays a minority game. These two groups of agents have different bounded abilities to deal with historical information and to count their own performance. In this paper, we modify Mix-game model by assigning the evolution abilities to agents: if the winning rates of agents are smaller than a threshold, they will copy the best strategies the other agent has; and agents will repeat such evolution at certain time intervals. Through simulations this paper finds: (1) the average winning rates of agents in Group 1 and the mean volatilities increase with the increases of the thresholds of Group 1; (2) the average winning rates of both groups decrease but the mean volatilities of system increase with the increase of the thresholds of Group 2; (3) the thresholds of Group 2 have greater impact on system dynamics than the thresholds of Group 1; (4) the characteristics of system dynamics under different time intervals of strategy change are similar to each other qualitatively, but they are different quantitatively; (5) As the time interval of strategy change increases from 1 to 20, the system behaves more and more stable and the performances of agents in both groups become better also.

The Price Equation, Gradient Dynamics, and Continuous Trait Game Theory.

Science.gov (United States)

Lehtonen, Jussi

2018-01-01

A recent article convincingly nominated the Price equation as the fundamental theorem of evolution and used it as a foundation to derive several other theorems. A major section of evolutionary theory that was not addressed is that of game theory and gradient dynamics of continuous traits with frequency-dependent fitness. Deriving fundamental results in these fields under the unifying framework of the Price equation illuminates similarities and differences between approaches and allows a simple, unified view of game-theoretical and dynamic concepts. Using Taylor polynomials and the Price equation, I derive a dynamic measure of evolutionary change, a condition for singular points, the convergence stability criterion, and an alternative interpretation of evolutionary stability. Furthermore, by applying the Price equation to a multivariable Taylor polynomial, the direct fitness approach to kin selection emerges. Finally, I compare these results to the mean gradient equation of quantitative genetics and the canonical equation of adaptive dynamics.

An evolutionary-game model of tumour-cell interactions: possible relevance to gene therapy

DEFF Research Database (Denmark)

Bach, L.A.; Bentzen, S.M.; Alsner, Jan

2001-01-01

Evolutionary games have been applied as simple mathematical models of populations where interactions between individuals control the dynamics. Recently, it has been proposed to use this type of model to describe the evolution of tumour cell populations with interactions between cells. We extent...

A Distributed Dynamic Super Peer Selection Method Based on Evolutionary Game for Heterogeneous P2P Streaming Systems

Directory of Open Access Journals (Sweden)

Jing Chen

2013-01-01

Full Text Available Due to high efficiency and good scalability, hierarchical hybrid P2P architecture has drawn more and more attention in P2P streaming research and application fields recently. The problem about super peer selection, which is the key problem in hybrid heterogeneous P2P architecture, is becoming highly challenging because super peers must be selected from a huge and dynamically changing network. A distributed super peer selection (SPS algorithm for hybrid heterogeneous P2P streaming system based on evolutionary game is proposed in this paper. The super peer selection procedure is modeled based on evolutionary game framework firstly, and its evolutionarily stable strategies are analyzed. Then a distributed Q-learning algorithm (ESS-SPS according to the mixed strategies by analysis is proposed for the peers to converge to the ESSs based on its own payoff history. Compared to the traditional randomly super peer selection scheme, experiments results show that the proposed ESS-SPS algorithm achieves better performance in terms of social welfare and average upload rate of super peers and keeps the upload capacity of the P2P streaming system increasing steadily with the number of peers increasing.

Sequential interactions-in which one player plays first and another responds-promote cooperation in evolutionary-dynamical simulations of single-shot Prisoner's Dilemma and Snowdrift games.

Science.gov (United States)

Laird, Robert A

2018-05-21

Cooperation is a central topic in evolutionary biology because (a) it is difficult to reconcile why individuals would act in a way that benefits others if such action is costly to themselves, and (b) it underpins many of the 'major transitions of evolution', making it essential for explaining the origins of successively higher levels of biological organization. Within evolutionary game theory, the Prisoner's Dilemma and Snowdrift games are the main theoretical constructs used to study the evolution of cooperation in dyadic interactions. In single-shot versions of these games, wherein individuals play each other only once, players typically act simultaneously rather than sequentially. Allowing one player to respond to the actions of its co-player-in the absence of any possibility of the responder being rewarded for cooperation or punished for defection, as in simultaneous or sequential iterated games-may seem to invite more incentive for exploitation and retaliation in single-shot games, compared to when interactions occur simultaneously, thereby reducing the likelihood that cooperative strategies can thrive. To the contrary, I use lattice-based, evolutionary-dynamical simulation models of single-shot games to demonstrate that under many conditions, sequential interactions have the potential to enhance unilaterally or mutually cooperative outcomes and increase the average payoff of populations, relative to simultaneous interactions-benefits that are especially prevalent in a spatially explicit context. This surprising result is attributable to the presence of conditional strategies that emerge in sequential games that can't occur in the corresponding simultaneous versions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Universal scaling for the dilemma strength in evolutionary games

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Wang, Zhen; Kokubo, Satoshi; Jusup, Marko; Tanimoto, Jun

2015-09-01

Why would natural selection favor the prevalence of cooperation within the groups of selfish individuals? A fruitful framework to address this question is evolutionary game theory, the essence of which is captured in the so-called social dilemmas. Such dilemmas have sparked the development of a variety of mathematical approaches to assess the conditions under which cooperation evolves. Furthermore, borrowing from statistical physics and network science, the research of the evolutionary game dynamics has been enriched with phenomena such as pattern formation, equilibrium selection, and self-organization. Numerous advances in understanding the evolution of cooperative behavior over the last few decades have recently been distilled into five reciprocity mechanisms: direct reciprocity, indirect reciprocity, kin selection, group selection, and network reciprocity. However, when social viscosity is introduced into a population via any of the reciprocity mechanisms, the existing scaling parameters for the dilemma strength do not yield a unique answer as to how the evolutionary dynamics should unfold. Motivated by this problem, we review the developments that led to the present state of affairs, highlight the accompanying pitfalls, and propose new universal scaling parameters for the dilemma strength. We prove universality by showing that the conditions for an ESS and the expressions for the internal equilibriums in an infinite, well-mixed population subjected to any of the five reciprocity mechanisms depend only on the new scaling parameters. A similar result is shown to hold for the fixation probability of the different strategies in a finite, well-mixed population. Furthermore, by means of numerical simulations, the same scaling parameters are shown to be effective even if the evolution of cooperation is considered on the spatial networks (with the exception of highly heterogeneous setups). We close the discussion by suggesting promising directions for future research

Evolutionary Game Theory: A Renaissance

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Jonathan Newton

2018-05-01

Full Text Available Economic agents are not always rational or farsighted and can make decisions according to simple behavioral rules that vary according to situation and can be studied using the tools of evolutionary game theory. Furthermore, such behavioral rules are themselves subject to evolutionary forces. Paying particular attention to the work of young researchers, this essay surveys the progress made over the last decade towards understanding these phenomena, and discusses open research topics of importance to economics and the broader social sciences.

Modeling Misbehavior in Cooperative Diversity: A Dynamic Game Approach

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Dehnie, Sintayehu; Memon, Nasir

2009-12-01

Cooperative diversity protocols are designed with the assumption that terminals always help each other in a socially efficient manner. This assumption may not be valid in commercial wireless networks where terminals may misbehave for selfish or malicious intentions. The presence of misbehaving terminals creates a social-dilemma where terminals exhibit uncertainty about the cooperative behavior of other terminals in the network. Cooperation in social-dilemma is characterized by a suboptimal Nash equilibrium where wireless terminals opt out of cooperation. Hence, without establishing a mechanism to detect and mitigate effects of misbehavior, it is difficult to maintain a socially optimal cooperation. In this paper, we first examine effects of misbehavior assuming static game model and show that cooperation under existing cooperative protocols is characterized by a noncooperative Nash equilibrium. Using evolutionary game dynamics we show that a small number of mutants can successfully invade a population of cooperators, which indicates that misbehavior is an evolutionary stable strategy (ESS). Our main goal is to design a mechanism that would enable wireless terminals to select reliable partners in the presence of uncertainty. To this end, we formulate cooperative diversity as a dynamic game with incomplete information. We show that the proposed dynamic game formulation satisfied the conditions for the existence of perfect Bayesian equilibrium.

Modeling Misbehavior in Cooperative Diversity: A Dynamic Game Approach

Directory of Open Access Journals (Sweden)

Sintayehu Dehnie

2009-01-01

Full Text Available Cooperative diversity protocols are designed with the assumption that terminals always help each other in a socially efficient manner. This assumption may not be valid in commercial wireless networks where terminals may misbehave for selfish or malicious intentions. The presence of misbehaving terminals creates a social-dilemma where terminals exhibit uncertainty about the cooperative behavior of other terminals in the network. Cooperation in social-dilemma is characterized by a suboptimal Nash equilibrium where wireless terminals opt out of cooperation. Hence, without establishing a mechanism to detect and mitigate effects of misbehavior, it is difficult to maintain a socially optimal cooperation. In this paper, we first examine effects of misbehavior assuming static game model and show that cooperation under existing cooperative protocols is characterized by a noncooperative Nash equilibrium. Using evolutionary game dynamics we show that a small number of mutants can successfully invade a population of cooperators, which indicates that misbehavior is an evolutionary stable strategy (ESS. Our main goal is to design a mechanism that would enable wireless terminals to select reliable partners in the presence of uncertainty. To this end, we formulate cooperative diversity as a dynamic game with incomplete information. We show that the proposed dynamic game formulation satisfied the conditions for the existence of perfect Bayesian equilibrium.

Stochastic evolutionary voluntary public goods game with punishment in a Quasi-birth-and-death process.

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Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2017-11-23

Traditional replication dynamic model and the corresponding concept of evolutionary stable strategy (ESS) only takes into account whether the system can return to the equilibrium after being subjected to a small disturbance. In the real world, due to continuous noise, the ESS of the system may not be stochastically stable. In this paper, a model of voluntary public goods game with punishment is studied in a stochastic situation. Unlike the existing model, we describe the evolutionary process of strategies in the population as a generalized quasi-birth-and-death process. And we investigate the stochastic stable equilibrium (SSE) instead. By numerical experiments, we get all possible SSEs of the system for any combination of parameters, and investigate the influence of parameters on the probabilities of the system to select different equilibriums. It is found that in the stochastic situation, the introduction of the punishment and non-participation strategies can change the evolutionary dynamics of the system and equilibrium of the game. There is a large range of parameters that the system selects the cooperative states as its SSE with a high probability. This result provides us an insight and control method for the evolution of cooperation in the public goods game in stochastic situations.

Prediction of stock markets by the evolutionary mix-game model

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Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

2008-06-01

This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

Static and evolutionary quantum public goods games

Energy Technology Data Exchange (ETDEWEB)

Liao Zeyang; Qin Gan; Hu Lingzhi; Li Songjian; Xu Nanyang [Hefei National Laboratory for Physical Science at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China); Du Jiangfeng [Hefei National Laboratory for Physical Science at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China); Fachbereich Physik, Universitaet Dortmund, 44221 Dortmund (Germany)], E-mail: djf@ustc.edu.cn

2008-05-12

We apply the continuous-variable quantization scheme to quantize public goods game and find that new pure strategy Nash equilibria emerge in the static case. Furthermore, in the evolutionary public goods game, entanglement can also contribute to the persistence of cooperation under various population structures without altruism, voluntary participation, and punishment.

Coevolution of Artificial Agents Using Evolutionary Computation in Bargaining Game

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Sangwook Lee

2015-01-01

Full Text Available Analysis of bargaining game using evolutionary computation is essential issue in the field of game theory. This paper investigates the interaction and coevolutionary process among heterogeneous artificial agents using evolutionary computation (EC in the bargaining game. In particular, the game performance with regard to payoff through the interaction and coevolution of agents is studied. We present three kinds of EC based agents (EC-agent participating in the bargaining game: genetic algorithm (GA, particle swarm optimization (PSO, and differential evolution (DE. The agents’ performance with regard to changing condition is compared. From the simulation results it is found that the PSO-agent is superior to the other agents.

Minority games, evolving capitals and replicator dynamics

International Nuclear Information System (INIS)

Galla, Tobias; Zhang, Yi-Cheng

2009-01-01

We discuss a simple version of the minority game (MG) in which agents hold only one strategy each, but in which their capitals evolve dynamically according to their success and in which the total trading volume varies in time accordingly. This feature is known to be crucial for MGs to reproduce stylized facts of real market data. The stationary states and phase diagram of the model can be computed, and we show that the ergodicity breaking phase transition common for MGs, and marked by a divergence of the integrated response, is present also in this simplified model. An analogous majority game turns out to be relatively void of interesting features, and the total capital is found to diverge in time. Introducing a restraining force leads to a model akin to the replicator dynamics of evolutionary game theory, and we demonstrate that here a different type of phase transition is observed. Finally we briefly discuss the relation of this model with one strategy per player to more sophisticated minority games with dynamical capitals and several trading strategies per agent

Older partner selection promotes the prevalence of cooperation in evolutionary games.

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Yang, Guoli; Huang, Jincai; Zhang, Weiming

2014-10-21

Evolutionary games typically come with the interplays between evolution of individual strategy and adaptation to network structure. How these dynamics in the co-evolution promote (or obstruct) the cooperation is regarded as an important topic in social, economic, and biological fields. Combining spatial selection with partner choice, the focus of this paper is to identify which neighbour should be selected as a role to imitate during the process of co-evolution. Age, an internal attribute and kind of local piece of information regarding the survivability of the agent, is a significant consideration for the selection strategy. The analysis and simulations presented, demonstrate that older partner selection for strategy imitation could foster the evolution of cooperation. The younger partner selection, however, may decrease the level of cooperation. Our model highlights the importance of agent׳s age on the promotion of cooperation in evolutionary games, both efficiently and effectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evolutionary games played by multi-agent system with different memory capacity

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Zhang, Jianlei; Zhang, Chunyan

2015-06-01

The evolution of cooperation is still an enigma. Resolution of cooperative dilemma is a hot topic as a perplexing interdisciplinary project, and has captured wide attention of researchers from many disciplines as a multidisciplinary field. Our main concern is the design of a networked evolutionary game model in which players show difference in memory capability. The idea of different memory capacities has its origin on the pervasive individual heterogeneity of real agents in nature. It is concluded that this proposed multiple memory capacity stimulates cooperation in lattice-structured populations. The networking effect is also investigated via a scale free network which is associated with the heterogeneous populations structure. Interestingly, results suggest that the effectiveness of a heterogeneous network at fostering cooperation is reduced in the presence of individual memory here. A thorough inquiry in the coevolutionary dynamics of individual memory and spatial structure in evolutionary games is planned for the immediate future.

Evolution of Cooperation in Evolutionary Games for Heterogeneous Interactions

International Nuclear Information System (INIS)

Qian Xiaolan; Yang Junzhong

2012-01-01

When a population structure is modelled as a square lattice, the cooperation may be improved for an evolutionary prisoner dilemma game or be inhibited for an evolutionary snowdrift game. In this work, we investigate cooperation in a population on a square lattice where the interaction among players contains both prisoner dilemma game and snowdrift game. The heterogeneity in interaction is introduced to the population in two different ways: the heterogenous character of interaction assigned to every player (HCP) or the heterogenous character of interaction assigned to every link between any two players (HCL). The resonant enhancement of cooperation in the case of HCP is observed while the resonant inhibition of cooperation in the case of HCL is prominent. The explanations on the enhancement or inhibition of cooperation are presented for these two cases. (general)

Multidimensional extended spatial evolutionary games.

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Krześlak, Michał; Świerniak, Andrzej

2016-02-01

The goal of this paper is to study the classical hawk-dove model using mixed spatial evolutionary games (MSEG). In these games, played on a lattice, an additional spatial layer is introduced for dependence on more complex parameters and simulation of changes in the environment. Furthermore, diverse polymorphic equilibrium points dependent on cell reproduction, model parameters, and their simulation are discussed. Our analysis demonstrates the sensitivity properties of MSEGs and possibilities for further development. We discuss applications of MSEGs, particularly algorithms for modelling cell interactions during the development of tumours. Copyright © 2015 Elsevier Ltd. All rights reserved.

Passivity analysis of higher order evolutionary dynamics and population games

KAUST Repository

Mabrok, Mohamed; Shamma, Jeff S.

2017-01-01

Evolutionary dynamics describe how the population composition changes in response to the fitness levels, resulting in a closed-loop feedback system. Recent work established a connection between passivity theory and certain classes of population

Invisible hand effect in an evolutionary minority game model

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Sysi-Aho, Marko; Saramäki, Jari; Kaski, Kimmo

2005-03-01

In this paper, we study the properties of a minority game with evolution realized by using genetic crossover to modify fixed-length decision-making strategies of agents. Although the agents in this evolutionary game act selfishly by trying to maximize their own performances only, it turns out that the whole society will eventually be rewarded optimally. This “invisible hand” effect is what Adam Smith over two centuries ago expected to take place in the context of free market mechanism. However, this behaviour of the society of agents is realized only under idealized conditions, where all agents are utilizing the same efficient evolutionary mechanism. If on the other hand part of the agents are adaptive, but not evolutionary, the system does not reach optimum performance, which is also the case if part of the evolutionary agents form a uniformly acting “cartel”.

Evolutionary optimization and game strategies for advanced multi-disciplinary design applications to aeronautics and UAV design

CERN Document Server

Periaux, Jacques; Lee, Dong Seop Chris

2015-01-01

Many complex aeronautical design problems can be formulated with efficient multi-objective evolutionary optimization methods and game strategies. This book describes the role of advanced innovative evolution tools in the solution, or the set of solutions of single or multi disciplinary optimization. These tools use the concept of multi-population, asynchronous parallelization and hierarchical topology which allows different models including precise, intermediate and approximate models with each node belonging to the different hierarchical layer handled by a different Evolutionary Algorithm. The efficiency of evolutionary algorithms for both single and multi-objective optimization problems are significantly improved by the coupling of EAs with games and in particular by a new dynamic methodology named “Hybridized Nash-Pareto games”. Multi objective Optimization techniques and robust design problems taking into account uncertainties are introduced and explained in detail. Several applications dealing with c...

Optimality and stability of symmetric evolutionary games with applications in genetic selection.

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Huang, Yuanyuan; Hao, Yiping; Wang, Min; Zhou, Wen; Wu, Zhijun

2015-06-01

Symmetric evolutionary games, i.e., evolutionary games with symmetric fitness matrices, have important applications in population genetics, where they can be used to model for example the selection and evolution of the genotypes of a given population. In this paper, we review the theory for obtaining optimal and stable strategies for symmetric evolutionary games, and provide some new proofs and computational methods. In particular, we review the relationship between the symmetric evolutionary game and the generalized knapsack problem, and discuss the first and second order necessary and sufficient conditions that can be derived from this relationship for testing the optimality and stability of the strategies. Some of the conditions are given in different forms from those in previous work and can be verified more efficiently. We also derive more efficient computational methods for the evaluation of the conditions than conventional approaches. We demonstrate how these conditions can be applied to justifying the strategies and their stabilities for a special class of genetic selection games including some in the study of genetic disorders.

Evolutionary Games and Social Conventions

DEFF Research Database (Denmark)

Hansen, Pelle Guldborg

2007-01-01

-defined metaphors of individual learning and social imitation processes, from which a revised theory of convention may be erected (see Sugden 2004, Binmore 1993 and Young 1998). This paper makes a general argument in support of the evolutionary turn in the theory of convention by a progressive exposition of its...... in Aumann (1976) and which, together with the assumptions of perfect rationality, came to be defining of classical game theory. However, classical game theory is currently undergoing severe crisis as a tool for exploring social phenomena; a crisis emerging from the problem of equilibrium selection around......Some thirty years ago Lewis published his Convention: A Philosophical Study (Lewis, 2002). This laid the foundation for a game-theoretic approach to social conventions, but became more famously known for its seminal analysis of common knowledge; the concept receiving its canonical analysis...

The Effects of Sacred Value Networks Within an Evolutionary, Adversarial Game

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McCalla, Scott G.; Short, Martin B.; Brantingham, P. Jeffrey

2013-05-01

The effects of personal relationships and shared ideologies on levels of crime and the formation of criminal coalitions are studied within the context of an adversarial, evolutionary game first introduced in Short et al. (Phys. Rev. E 82:066114, 2010). Here, we interpret these relationships as connections on a graph of N players. These connections are then used in a variety of ways to define each player's "sacred value network"—groups of individuals that are subject to special consideration or treatment by that player. We explore the effects on the dynamics of the system that these networks introduce, through various forms of protection from both victimization and punishment. Under local protection, these networks introduce a new fixed point within the game dynamics, which we find through a continuum approximation of the discrete game. Under more complicated, extended protection, we numerically observe the emergence of criminal coalitions, or "gangs". We also find that a high-crime steady state is much more frequent in the context of extended protection networks, in both the case of Erdős-Rényi and small world random graphs.

Chemical evolutionary games.

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Aristotelous, Andreas C; Durrett, Richard

2014-05-01

Inspired by the use of hybrid cellular automata in modeling cancer, we introduce a generalization of evolutionary games in which cells produce and absorb chemicals, and the chemical concentrations dictate the death rates of cells and their fitnesses. Our long term aim is to understand how the details of the interactions in a system with n species and m chemicals translate into the qualitative behavior of the system. Here, we study two simple 2×2 games with two chemicals and revisit the two and three species versions of the one chemical colicin system studied earlier by Durrett and Levin (1997). We find that in the 2×2 examples, the behavior of our new spatial model can be predicted from that of the mean field differential equation using ideas of Durrett and Levin (1994). However, in the three species colicin model, the system with diffusion does not have the coexistence which occurs in the lattices model in which sites interact with only their nearest neighbors. Copyright © 2014 Elsevier Inc. All rights reserved.

Evolutionary dynamics of division of labor games with selfish agents

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Zhang, Jianlei; Li, Qiaoyu; Zhang, Chunyan

2017-11-01

The division of labor is one of the most basic and widely studied aspects of collective behavior in natural systems. Studies of division of labor are concerned with the integration of the individual worker behavior into a colony level task organization and with the question of how the regulation of the division of labor may contribute to the colony efficiency. This paper investigates the evolution of the division of labor with three strategies by employing the evolutionary game theory. Thus, these available strategies are, respectively, strategy A (performing task A), strategy B (performing task B), and strategy D (not performing any task but only free riding others' contributions). And, two typical networks (i.e., BA scale-free network and lattice network) are employed here for describing the interaction structure among agents. The theoretical analysis together with simulation results reveal that the division of labor can evolve and leads to players that differ in their tendency to take on a given task. The conditions under which the division of labor evolves depend on the costs for performing the task, the benefits led by performing the task, and the interaction structures among the players who are involved with division of labor games.

Fixation of strategies with the Moran and Fermi processes in evolutionary games

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Liu, Xuesong; He, Mingfeng; Kang, Yibin; Pan, Qiuhui

2017-10-01

A model of stochastic evolutionary game dynamics with finite population was built. It combines the standard Moran and Fermi rules with two strategies cooperation and defection. We obtain the expressions of fixation probabilities and fixation times. The one-third rule which has been found in the frequency dependent Moran process also holds for our model. We obtain the conditions of strategy being an evolutionarily stable strategy in our model, and then make a comparison with the standard Moran process. Besides, the analytical results show that compared with the standard Moran process, fixation occurs with higher probabilities under a prisoner's dilemma game and coordination game, but with lower probabilities under a coexistence game. The simulation result shows that the fixation time in our mixed process is lower than that in the standard Fermi process. In comparison with the standard Moran process, fixation always takes more time on average in spatial populations, regardless of the game. In addition, the fixation time decreases with the growth of the number of neighbors.

Double-dealing behavior potentially promotes cooperation in evolutionary prisoner's dilemma games

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Dai, Qionglin; Li, Haihong; Cheng, Hongyan; Li, Yuting; Yang, Junzhong

2010-11-01

We investigate the effects of double-dealing behavior on cooperation in evolutionary games. Each individual in a population has two attributes: character and action. One's action may be consistent with one's character or not. We provide analytical results by a mean-field description of evolutionary prisoner's dilemma games (PDGs). Moreover, we give numerical results on different networks, ranging from square lattices to scale-free networks (SFNs). Two important conclusions have been drawn from the results on SFNs. Firstly, if only non-influential individuals (those with low degrees) have chances of becoming double-dealers, cooperation is certain to deteriorate. Secondly, when influential individuals (those with high degrees) adopt double-dealing behavior moderately, cooperation would be enhanced, which is in opposition to the traditional belief. These results help us to understand better the social phenomenon of the existence of double-dealers. In addition to the PDG, other types of games including the snowdrift game, the stag-hunt game and the harmony game have also been studied on our model. The results for these three games are also presented, which are consistent with the results for the PDG qualitatively. Furthermore, we consider our model under the co-evolution framework, in which the probability of an individual changing into a double-dealer and the individual strategy both could evolve during the evolutionary process.

Stability of Mixed-Strategy-Based Iterative Logit Quantal Response Dynamics in Game Theory

Science.gov (United States)

Zhuang, Qian; Di, Zengru; Wu, Jinshan

2014-01-01

Using the Logit quantal response form as the response function in each step, the original definition of static quantal response equilibrium (QRE) is extended into an iterative evolution process. QREs remain as the fixed points of the dynamic process. However, depending on whether such fixed points are the long-term solutions of the dynamic process, they can be classified into stable (SQREs) and unstable (USQREs) equilibriums. This extension resembles the extension from static Nash equilibriums (NEs) to evolutionary stable solutions in the framework of evolutionary game theory. The relation between SQREs and other solution concepts of games, including NEs and QREs, is discussed. Using experimental data from other published papers, we perform a preliminary comparison between SQREs, NEs, QREs and the observed behavioral outcomes of those experiments. For certain games, we determine that SQREs have better predictive power than QREs and NEs. PMID:25157502

Dilemma strength as a framework for advancing evolutionary game theory. Reply to comments on "Universal scaling for the dilemma strength in evolutionary games"

Science.gov (United States)

Wang, Zhen; Kokubo, Satoshi; Jusup, Marko; Tanimoto, Jun

2015-09-01

While comprehensive reviews of the literature, by gathering in one place most of the relevant information, undoubtedly steer the development of every scientific field, we found that the comments in response to a review article can be as informative as the review itself, if not more. Namely, reading through the comments on the ideas expressed in Ref. [1], we could identify a number of pressing problems for evolutionary game theory, indicating just how much space there still is for major advances and breakthroughs. In an attempt to bring a sense of order to a multitude of opinions, we roughly classified the comments into three categories, i.e. those concerned with: (i) the universality of scaling in heterogeneous topologies, including empirical dynamic networks [2-8], (ii) the universality of scaling for more general game setups, such as the inclusion of multiple strategies and external features [4,9-11], and (iii) experimental confirmations of the theoretical developments [2,12,13].

A study of driver's route choice behavior based on evolutionary game theory.

Science.gov (United States)

Jiang, Xiaowei; Ji, Yanjie; Du, Muqing; Deng, Wei

2014-01-01

This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers' route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver's route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver's route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

Interaction times change evolutionary outcomes: Two-player matrix games

Czech Academy of Sciences Publication Activity Database

Křivan, Vlastimil; Cressman, R.

2017-01-01

Roč. 416, MAR 07 (2017), s. 199-207 ISSN 0022-5193 EU Projects: European Commission(XE) 690817 - FourCmodelling Institutional support: RVO:60077344 Keywords : evolutionary game theory * Hawk-Dove game * pair formation Subject RIV: EH - Ecology, Behaviour OBOR OECD: Ecology Impact factor: 2.113, year: 2016 http://www.sciencedirect.com/science/article/pii/S0022519317300103

A Graphical Evolutionary Game Approach to Social Learning

Science.gov (United States)

Cao, Xuanyu; Liu, K. J. Ray

2017-06-01

In this work, we study the social learning problem, in which agents of a networked system collaborate to detect the state of the nature based on their private signals. A novel distributed graphical evolutionary game theoretic learning method is proposed. In the proposed game-theoretic method, agents only need to communicate their binary decisions rather than the real-valued beliefs with their neighbors, which endows the method with low communication complexity. Under mean field approximations, we theoretically analyze the steady state equilibria of the game and show that the evolutionarily stable states (ESSs) coincide with the decisions of the benchmark centralized detector. Numerical experiments are implemented to confirm the effectiveness of the proposed game-theoretic learning method.

An Evolutionary Game Theoretic Approach to Multi-Sector Coordination and Self-Organization

Directory of Open Access Journals (Sweden)

Fernando P. Santos

2016-04-01

Full Text Available Coordination games provide ubiquitous interaction paradigms to frame human behavioral features, such as information transmission, conventions and languages as well as socio-economic processes and institutions. By using a dynamical approach, such as Evolutionary Game Theory (EGT, one is able to follow, in detail, the self-organization process by which a population of individuals coordinates into a given behavior. Real socio-economic scenarios, however, often involve the interaction between multiple co-evolving sectors, with specific options of their own, that call for generalized and more sophisticated mathematical frameworks. In this paper, we explore a general EGT approach to deal with coordination dynamics in which individuals from multiple sectors interact. Starting from a two-sector, consumer/producer scenario, we investigate the effects of including a third co-evolving sector that we call public. We explore the changes in the self-organization process of all sectors, given the feedback that this new sector imparts on the other two.

Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature

Science.gov (United States)

Ma, Zhanshan (Sam)

In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal [27][30]-[32]. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three

Evolutionary games on multilayer networks: a colloquium

Science.gov (United States)

Wang, Zhen; Wang, Lin; Szolnoki, Attila; Perc, Matjaž

2015-05-01

Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling through the utilities of players, through the flow of information, as well as through the popularity of different strategies on different network layers. The colloquium highlights the importance of pattern formation and collective behavior for the promotion of cooperation under adverse conditions, as well as the synergies between network science and evolutionary game theory.

Multi-objective optimization of an arch dam shape under static loads using an evolutionary game method

Science.gov (United States)

Meng, Rui; Cheong, Kang Hao; Bao, Wei; Wong, Kelvin Kian Loong; Wang, Lu; Xie, Neng-gang

2018-06-01

This article attempts to evaluate the safety and economic performance of an arch dam under the action of static loads. The geometric description of a crown cantilever section and the horizontal arch ring is presented. A three-objective optimization model of arch dam shape is established based on the arch dam volume, maximum principal tensile stress and total strain energy. The evolutionary game method is then applied to obtain the optimal solution. In the evolutionary game technique, a novel and more efficient exploration method of the game players' strategy space, named the 'sorting partition method under the threshold limit', is presented, with the game profit functions constructed according to both competitive and cooperative behaviour. By way of example, three optimization goals have all shown improvements over the initial solutions. In particular, the evolutionary game method has potentially faster convergence. This demonstrates the preliminary proof of principle of the evolutionary game method.

Games of multicellularity.

Science.gov (United States)

Kaveh, Kamran; Veller, Carl; Nowak, Martin A

2016-08-21

Evolutionary game dynamics are often studied in the context of different population structures. Here we propose a new population structure that is inspired by simple multicellular life forms. In our model, cells reproduce but can stay together after reproduction. They reach complexes of a certain size, n, before producing single cells again. The cells within a complex derive payoff from an evolutionary game by interacting with each other. The reproductive rate of cells is proportional to their payoff. We consider all two-strategy games. We study deterministic evolutionary dynamics with mutations, and derive exact conditions for selection to favor one strategy over another. Our main result has the same symmetry as the well-known sigma condition, which has been proven for stochastic game dynamics and weak selection. For a maximum complex size of n=2 our result holds for any intensity of selection. For n≥3 it holds for weak selection. As specific examples we study the prisoner's dilemma and hawk-dove games. Our model advances theoretical work on multicellularity by allowing for frequency-dependent interactions within groups. Copyright © 2016 Elsevier Ltd. All rights reserved.

Memory boosts turn taking in evolutionary dilemma games.

Science.gov (United States)

Wang, Tao; Chen, Zhigang; Yang, Lei; Zou, You; Luo, Juan

2015-05-01

Spontaneous turn taking phenomenon can be observed in many self-organized systems, and the mechanism is unclear. This paper tries to model it by evolutionary dilemma games with memory mechanism. Prisoner's dilemma, Snowdrift (including Leader and Hero) and Stag-hunt games are unified on an extended S-T plane. Agents play game with all the others and make decision by the last game histories. The experiments find that when agents remember last 2-step histories or more, a kind of cooperative turn taking (CAD) bursts at the area of Snowdrift game with restriction of S + T > 2R and S ≠ T, while the consistent strategy (DorC) gathers on the line of S + T > 2R and S = T. We also find that the system's fitness ratio greatly improved with 2-step memory. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evolutionary quantum game theory in the context of socio-economic systems

International Nuclear Information System (INIS)

Hanauske, Matthias

2011-01-01

The evolution of socio-economic systems depend on the interdependent decision processes of its underlying system components. The mathematical model to describe the strategic decision of players within a socio-economic game is ''game theory''. ''Quantum game theory'' is a mathematical and conceptual amplification of classical game theory. The space of all conceivable decision paths is extended from the purely rational, measurable space in the Hilbert-space of complex numbers - which is the mathematical space where quantum theory is formulated. By the concept of a potential entanglement of the imaginary quantum strategy parts, it is possible to include cooperate decision path, caused by cultural or moral standards. If this strategy entanglement is large enough, then additional Nash equilibria can occur, previously present dominant strategies could become nonexistent and new evolutionary stable strategies do appear for some game classes. Within this PhD thesis the main results of classical and quantum games are summarized and all of the possible game classes of evolutionary (2 player)-(2 strategy) games are extended to quantum games. It is shown that the quantum extension of classical games with an underlying dilemma-like structure give different results, if the strength of strategic entanglement is above a certain barrier. After the German summary and the introduction paper, five different applications of the theory are discussed within the thesis. (orig.)

A Study of Driver’s Route Choice Behavior Based on Evolutionary Game Theory

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Xiaowei Jiang

2014-01-01

Full Text Available This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers’ route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver’s route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver’s route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

Evolutionary dynamics of cooperation in neutral populations

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Szolnoki, Attila; Perc, Matjaž

2018-01-01

Cooperation is a difficult proposition in the face of Darwinian selection. Those that defect have an evolutionary advantage over cooperators who should therefore die out. However, spatial structure enables cooperators to survive through the formation of homogeneous clusters, which is the hallmark of network reciprocity. Here we go beyond this traditional setup and study the spatiotemporal dynamics of cooperation in a population of populations. We use the prisoner's dilemma game as the mathematical model and show that considering several populations simultaneously gives rise to fascinating spatiotemporal dynamics and pattern formation. Even the simplest assumption that strategies between different populations are payoff-neutral with one another results in the spontaneous emergence of cyclic dominance, where defectors of one population become prey of cooperators in the other population, and vice versa. Moreover, if social interactions within different populations are characterized by significantly different temptations to defect, we observe that defectors in the population with the largest temptation counterintuitively vanish the fastest, while cooperators that hang on eventually take over the whole available space. Our results reveal that considering the simultaneous presence of different populations significantly expands the complexity of evolutionary dynamics in structured populations, and it allows us to understand the stability of cooperation under adverse conditions that could never be bridged by network reciprocity alone.

Multiple steady states, limit cycles and chaotic attractors in evolutionary games with Logit Dynamics

NARCIS (Netherlands)

Hommes, C.H.; Ochea, M.I.

2010-01-01

This paper investigates, by means of simple, three and four strategy games, the occurrence of periodic and chaotic behaviour in a smooth version of the Best Response Dynamics, the Logit Dynamics. The main finding is that, unlike Replicator Dynamics, generic Hopf bifurcation and thus, stable limit

Analysis of Urban Car Owners Commute Mode Choice Based on Evolutionary Game Model

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Huawei Gong

2015-01-01

Full Text Available With the aggravation of the traffic congestion in the city, car owners will have to give up commuting with private cars and take the public transportation instead. The paper uses the replication dynamic mechanism to simulate the learning and adjustment mechanism of the automobile owners commuting mode selection. The evolutionary stable strategy is used to describe the long-term evolution of competition game trend. Finally we simulate equilibrium and stability of an evolution of the game under a payoff imbalance situation. The research shows that a certain proportion of car owners will choose public transit under the pressure of public transport development and heavy traffic, and the proportion will be closely related to the initial conditions and urban transportation development policy.

Evolutionary Dynamics of Collective Action in Structured Populations

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Santos, Marta Daniela de Almeida

The pervasiveness of cooperation in Nature is not easily explained. If evolution is characterized by competition and survival of the fittest, why should selfish individuals cooperate with each other? Evolutionary Game Theory (EGT) provides a suitable mathematical framework to study this problem, central to many areas of science. Conventionally, interactions between individuals are modeled in terms of one-shot, symmetric 2-Person Dilemmas of Cooperation, but many real-life situations involve decisions within groups with more than 2 individuals, which are best-dealt in the framework of N-Person games. In this Thesis, we investigate the evolutionary dynamics of two paradigmatic collective social dilemmas - the N-Person Prisoner's Dilemma (NPD) and the N-Person Snowdrift Game (NSG) on structured populations, modeled by networks with diverse topological properties. Cooperative strategies are just one example of the many traits that can be transmitted on social networks. Several recent studies based on empirical evidence from a medical database have suggested the existence of a 3 degrees of influence rule, according to which not only our "friends", but also our friends' friends, and our friends' friends' friends, have a non-trivial influence on our decisions. We investigate the degree of peer influence that emerges from the spread of cooperative strategies, opinions and diseases on populations with distinct underlying networks of contacts. Our results show that networks naturally entangle individuals into interactions of many-body nature and that for each network class considered different processes lead to identical degrees of influence. None

Effects of behavioral response and vaccination policy on epidemic spreading--an approach based on evolutionary-game dynamics.

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Zhang, Hai-Feng; Wu, Zhi-Xi; Tang, Ming; Lai, Ying-Cheng

2014-07-11

How effective are governmental incentives to achieve widespread vaccination coverage so as to prevent epidemic outbreak? The answer largely depends on the complex interplay among the type of incentive, individual behavioral responses, and the intrinsic epidemic dynamics. By incorporating evolutionary games into epidemic dynamics, we investigate the effects of two types of incentives strategies: partial-subsidy policy in which certain fraction of the cost of vaccination is offset, and free-subsidy policy in which donees are randomly selected and vaccinated at no cost. Through mean-field analysis and computations, we find that, under the partial-subsidy policy, the vaccination coverage depends monotonically on the sensitivity of individuals to payoff difference, but the dependence is non-monotonous for the free-subsidy policy. Due to the role models of the donees for relatively irrational individuals and the unchanged strategies of the donees for rational individuals, the free-subsidy policy can in general lead to higher vaccination coverage. Our findings indicate that any disease-control policy should be exercised with extreme care: its success depends on the complex interplay among the intrinsic mathematical rules of epidemic spreading, governmental policies, and behavioral responses of individuals.

Quantum evolutionary stable strategies of 2-player, 2-strategy symmetric games

International Nuclear Information System (INIS)

Sun, Z.W.

2009-01-01

Quantum evolutionary stable strategies (ESSs) of games are considered as stable solutions to population games on molecular level. The distributive diagram of 2-player, 2-strategy (2 x 2) symmetric games is brought out to get a convenient way of looking for their quantum ESSs. It is found that transpositions, related to the parameters in classical payoff and those of initial quantum states, may occur when games are quantized. Conditions for transpositions are given in two tables. One can easily find quantum ESSs of a 2 x 2 symmetric game according to its transposition. This paper also draws an overall outline of NEs and ESSs of this kind of game.

Dynamics of prebiotic RNA reproduction illuminated by chemical game theory.

Science.gov (United States)

Yeates, Jessica A M; Hilbe, Christian; Zwick, Martin; Nowak, Martin A; Lehman, Niles

2016-05-03

Many origins-of-life scenarios depict a situation in which there are common and potentially scarce resources needed by molecules that compete for survival and reproduction. The dynamics of RNA assembly in a complex mixture of sequences is a frequency-dependent process and mimics such scenarios. By synthesizing Azoarcus ribozyme genotypes that differ in their single-nucleotide interactions with other genotypes, we can create molecules that interact among each other to reproduce. Pairwise interplays between RNAs involve both cooperation and selfishness, quantifiable in a 2 × 2 payoff matrix. We show that a simple model of differential equations based on chemical kinetics accurately predicts the outcomes of these molecular competitions using simple rate inputs into these matrices. In some cases, we find that mixtures of different RNAs reproduce much better than each RNA type alone, reflecting a molecular form of reciprocal cooperation. We also demonstrate that three RNA genotypes can stably coexist in a rock-paper-scissors analog. Our experiments suggest a new type of evolutionary game dynamics, called prelife game dynamics or chemical game dynamics. These operate without template-directed replication, illustrating how small networks of RNAs could have developed and evolved in an RNA world.

Dynamics of prebiotic RNA reproduction illuminated by chemical game theory

Science.gov (United States)

Yeates, Jessica A. M.; Hilbe, Christian; Zwick, Martin; Nowak, Martin A.; Lehman, Niles

2016-01-01

Many origins-of-life scenarios depict a situation in which there are common and potentially scarce resources needed by molecules that compete for survival and reproduction. The dynamics of RNA assembly in a complex mixture of sequences is a frequency-dependent process and mimics such scenarios. By synthesizing Azoarcus ribozyme genotypes that differ in their single-nucleotide interactions with other genotypes, we can create molecules that interact among each other to reproduce. Pairwise interplays between RNAs involve both cooperation and selfishness, quantifiable in a 2 × 2 payoff matrix. We show that a simple model of differential equations based on chemical kinetics accurately predicts the outcomes of these molecular competitions using simple rate inputs into these matrices. In some cases, we find that mixtures of different RNAs reproduce much better than each RNA type alone, reflecting a molecular form of reciprocal cooperation. We also demonstrate that three RNA genotypes can stably coexist in a rock–paper–scissors analog. Our experiments suggest a new type of evolutionary game dynamics, called prelife game dynamics or chemical game dynamics. These operate without template-directed replication, illustrating how small networks of RNAs could have developed and evolved in an RNA world. PMID:27091972

Evolutionary dynamics under interactive diversity

Science.gov (United States)

Su, Qi; Li, Aming; Wang, Long

2017-10-01

As evidenced by many cases in human societies, individuals often make different behavior decisions in different interactions, and adaptively adjust their behavior in changeable interactive scenarios. However, up to now, how such diverse interactive behavior affects cooperation dynamics has still remained unknown. Here we develop a general framework of interactive diversity, which models individuals’ separated behavior against distinct opponents and their adaptive adjustment in response to opponents’ strategies, to explore the evolution of cooperation. We find that interactive diversity enables individuals to reciprocate every single opponent, and thus sustains large-scale reciprocal interactions. Our work witnesses an impressive boost of cooperation for a notably extensive range of parameters and for all pairwise games. These results are robust against well-mixed and various networked populations, and against degree-normalized and cumulative payoff patterns. From the perspective of network dynamics, distinguished from individuals competing for nodes in most previous work, in this paper, the system evolves in the form of behavior disseminating along edges. We propose a theoretical method based on evolution of edges, which predicts well both the frequency of cooperation and the compact cooperation clusters. Our thorough investigation clarifies the positive role of interactive diversity in resolving social dilemmas and highlights the significance of understanding evolutionary dynamics from the viewpoint of edge dynamics.

Preferential selection based on strategy persistence and memory promotes cooperation in evolutionary prisoner's dilemma games

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Liu, Yuanming; Huang, Changwei; Dai, Qionglin

2018-06-01

Strategy imitation plays a crucial role in evolutionary dynamics when we investigate the spontaneous emergence of cooperation under the framework of evolutionary game theory. Generally, when an individual updates his strategy, he needs to choose a role model whom he will learn from. In previous studies, individuals choose role models randomly from their neighbors. In recent works, researchers have considered that individuals choose role models according to neighbors' attractiveness characterized by the present network topology or historical payoffs. Here, we associate an individual's attractiveness with the strategy persistence, which characterizes how frequently he changes his strategy. We introduce a preferential parameter α to describe the nonlinear correlation between the selection probability and the strategy persistence and the memory length of individuals M into the evolutionary games. We investigate the effects of α and M on cooperation. Our results show that cooperation could be promoted when α > 0 and at the same time M > 1, which corresponds to the situation that individuals are inclined to select their neighbors with relatively higher persistence levels during the evolution. Moreover, we find that the cooperation level could reach the maximum at an optimal memory length when α > 0. Our work sheds light on how to promote cooperation through preferential selection based on strategy persistence and a limited memory length.

Cycle frequency in standard Rock-Paper-Scissors games: Evidence from experimental economics

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Xu, Bin; Zhou, Hai-Jun; Wang, Zhijian

2013-10-01

The Rock-Paper-Scissors (RPS) game is a widely used model system in game theory. Evolutionary game theory predicts the existence of persistent cycles in the evolutionary trajectories of the RPS game, but experimental evidence has remained to be rather weak. In this work, we performed laboratory experiments on the RPS game and analyzed the social-state evolutionary trajectories of twelve populations of N=6 players. We found strong evidence supporting the existence of persistent cycles. The mean cycling frequency was measured to be 0.029±0.009 period per experimental round. Our experimental observations can be quantitatively explained by a simple non-equilibrium model, namely the discrete-time logit dynamical process with a noise parameter. Our work therefore favors the evolutionary game theory over the classical game theory for describing the dynamical behavior of the RPS game.

The ecology of cancer from an evolutionary game theory perspective.

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Pacheco, Jorge M; Santos, Francisco C; Dingli, David

2014-08-06

The accumulation of somatic mutations, to which the cellular genome is permanently exposed, often leads to cancer. Analysis of any tumour shows that, besides the malignant cells, one finds other 'supporting' cells such as fibroblasts, immune cells of various types and even blood vessels. Together, these cells generate the microenvironment that enables the malignant cell population to grow and ultimately lead to disease. Therefore, understanding the dynamics of tumour growth and response to therapy is incomplete unless the interactions between the malignant cells and normal cells are investigated in the environment in which they take place. The complex interactions between cells in such an ecosystem result from the exchange of information in the form of cytokines- and adhesion-dependent interactions. Such processes impose costs and benefits to the participating cells that may be conveniently recast in the form of a game pay-off matrix. As a result, tumour progression and dynamics can be described in terms of evolutionary game theory (EGT), which provides a convenient framework in which to capture the frequency-dependent nature of ecosystem dynamics. Here, we provide a tutorial review of the central aspects of EGT, establishing a relation with the problem of cancer. Along the way, we also digress on fitness and of ways to compute it. Subsequently, we show how EGT can be applied to the study of the various manifestations and dynamics of multiple myeloma bone disease and its preceding condition known as monoclonal gammopathy of undetermined significance. We translate the complex biochemical signals into costs and benefits of different cell types, thus defining a game pay-off matrix. Then we use the well-known properties of the EGT equations to reduce the number of core parameters that characterize disease evolution. Finally, we provide an interpretation of these core parameters in terms of what their function is in the ecosystem we are describing and generate

Playing Multi-Action Adversarial Games: Online Evolutionary Planning versus Tree Search

OpenAIRE

Justesen, Niels; Mahlmann, Tobias; Risi, Sebastian; Togelius, Julian

2017-01-01

We address the problem of playing turn-based multi-action adversarial games, which include many strategy games with extremely high branching factors as players take multiple actions each turn. This leads to the breakdown of standard tree search methods, including Monte Carlo Tree Search (MCTS), as they become unable to reach a sufficient depth in the game tree. In this paper, we introduce Online Evolutionary Planning (OEP) to address this challenge, which searches for combinations of actions ...

Advances in Dynamic Games

CERN Document Server

Breton, Michele

2011-01-01

This book focuses on various aspects of dynamic game theory, presenting state-of-the-art research and serving as a testament to the vitality and growth of the field of dynamic games and their applications. The selected contributions, written by experts in their respective disciplines, are outgrowths of presentations originally given at the 13th International Symposium of Dynamic Games and Applications held in WrocACaw. The book covers a variety of topics, ranging from theoretical developments in game theory and algorithmic methods to applications, examples, and analysis in fields as varied as

Evolutionary games combining two or three pair coordinations on a square lattice

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Király, Balázs; Szabó, György

2017-10-01

We study multiagent logit-rule-driven evolutionary games on a square lattice whose pair interactions are composed of a maximal number of nonoverlapping elementary coordination games describing Ising-type interactions between just two of the available strategies. Using Monte Carlo simulations we investigate the macroscopic noise-level-dependent behavior of the two- and three-pair games and the critical properties of the continuous phase transtitions these systems exhibit. The four-strategy game is shown to be equivalent to a system that consists of two independent and identical Ising models.

Understanding herding based on a co-evolutionary model for strategy and game structure

International Nuclear Information System (INIS)

Wang, Tao; Huang, Keke; Cheng, Yuan; Zheng, Xiaoping

2015-01-01

Highlights: •We model herding effect in emergency from perspective of evolutionary game theory. •Rational subpopulation survives only when the game parameter is significantly large. •Herding effect may arise if the relative rewarding for rational agents is small. •Increasing the relative rewarding for rational agents will prevent herding effect. •The evolution result is unstable if the game parameter approaches critical points. -- Abstract: So far, there has been no conclusion on the mechanism for herding, which is often discussed in the academia. Assuming escaping behavior of individuals in emergency is rational rather than out of panic according to recent findings in social psychology, we investigate the behavioral evolution of large crowds from the perspective of evolutionary game theory. Specifically, evolution of the whole population divided into two subpopulations, namely the co-evolution of strategy and game structure, is numerically simulated based on the game theoretical models built and the evolutionary rule designed, and a series of phenomena including extinction of one subpopulation and herding effect are predicted in the proposed framework. Furthermore, if the rewarding for rational agents becomes significantly larger than that for emotional ones, herding effect will disappear. It is exciting that some phase transition points with interesting properties for the system can be found. In addition, our model framework is able to explain the fact that it is difficult for mavericks to prevail in society. The current results of this work will be helpful in understanding and restraining herding effect in real life

Universal effect of dynamical reinforcement learning mechanism in spatial evolutionary games

International Nuclear Information System (INIS)

Zhang, Hai-Feng; Wu, Zhi-Xi; Wang, Bing-Hong

2012-01-01

One of the prototypical mechanisms in understanding the ubiquitous cooperation in social dilemma situations is the win–stay, lose–shift rule. In this work, a generalized win–stay, lose–shift learning model—a reinforcement learning model with dynamic aspiration level—is proposed to describe how humans adapt their social behaviors based on their social experiences. In the model, the players incorporate the information of the outcomes in previous rounds with time-dependent aspiration payoffs to regulate the probability of choosing cooperation. By investigating such a reinforcement learning rule in the spatial prisoner's dilemma game and public goods game, a most noteworthy viewpoint is that moderate greediness (i.e. moderate aspiration level) favors best the development and organization of collective cooperation. The generality of this observation is tested against different regulation strengths and different types of network of interaction as well. We also make comparisons with two recently proposed models to highlight the importance of the mechanism of adaptive aspiration level in supporting cooperation in structured populations

Environmental Policy and Technology Diffusion under Imperfect Competition. An Evolutionary Game Theoretical Approach

Energy Technology Data Exchange (ETDEWEB)

De Vries, F.P.

2003-05-01

The analysis of the thesis centers around the diffusion incentives of different environmental policy instruments. Emission taxation, subsidies per unit of emission reduction, marketable emission permits and marketable emission credits will be discussed and compared to each other on how they affect the diffusion of an environmentally benign technology. The analysis is conducted within an applied evolutionary game theoretical framework. An extensive discussion of evolutionary game theory can be found in chapter 2. Chapter 3 reviews classical diffusion models: the epidemic, probit and classic game theoretical model. Then we shift our attention to general evolutionary diffusion models, followed by an outline of the use of evolutionary game theory as a tool for analyzing technology diffusion. The purpose of the chapter is to illustrate the main differences between the various models. Relevant parts of economic theory are reviewed in chapters 4 and 5. Chapter 4 contains a survey and interpretive assessment of the current literature dealing with the impact of environmental policy instruments on the adoption and diffusion of a pollution abatement technology. The chapter illustrates and criticizes the static character of the most influential models. In chapter 2 it will become apparent that an evolutionary analysis is quite appealing when markets axe characterized by perfect competition. Enhanced competitiveness forces firms to produce efficiently in order to avoid elimination. However, in imperfect competitive markets competition is limited to only a small number of firms. Since the central market structure in this thesis is that of imperfect competition, chapter 5 examines the literature on evolutionary game models applied to these type of markets. The survey reveals that the literature focuses on determining whether the evolutionary game models generate output equilibria identical to the traditional static Cournot and Bertrand models or to other output levels. Chapter 6

Some results on ethnic conflicts based on evolutionary game simulation

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Qin, Jun; Yi, Yunfei; Wu, Hongrun; Liu, Yuhang; Tong, Xiaonian; Zheng, Bojin

2014-07-01

The force of the ethnic separatism, essentially originating from the negative effect of ethnic identity, is damaging the stability and harmony of multiethnic countries. In order to eliminate the foundation of the ethnic separatism and set up a harmonious ethnic relationship, some scholars have proposed a viewpoint: ethnic harmony could be promoted by popularizing civic identity. However, this viewpoint is discussed only from a philosophical prospective and still lacks support of scientific evidences. Because ethnic group and ethnic identity are products of evolution and ethnic identity is the parochialism strategy under the perspective of game theory, this paper proposes an evolutionary game simulation model to study the relationship between civic identity and ethnic conflict based on evolutionary game theory. The simulation results indicate that: (1) the ratio of individuals with civic identity has a negative association with the frequency of ethnic conflicts; (2) ethnic conflict will not die out by killing all ethnic members once for all, and it also cannot be reduced by a forcible pressure, i.e., increasing the ratio of individuals with civic identity; (3) the average frequencies of conflicts can stay in a low level by promoting civic identity periodically and persistently.

Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process.

Science.gov (United States)

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-27

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.

Quantifying the Role of Homophily in Human Cooperation Using Multiplex Evolutionary Game Theory.

Directory of Open Access Journals (Sweden)

Alessandro Di Stefano

Full Text Available Nature shows as human beings live and grow inside social structures. This assumption allows us to explain and explore how it may shape most of our behaviours and choices, and why we are not just blindly driven by instincts: our decisions are based on more complex cognitive reasons, based on our connectedness on different spaces. Thus, human cooperation emerges from this complex nature of social network. Our paper, focusing on the evolutionary dynamics, is intended to explore how and why it happens, and what kind of impact is caused by homophily among people. We investigate the evolution of human cooperation using evolutionary game theory on multiplex. Multiplexity, as an extra dimension of analysis, allows us to unveil the hidden dynamics and observe non-trivial patterns within a population across network layers. More importantly, we find a striking role of homophily, as the higher the homophily between individuals, the quicker is the convergence towards cooperation in the social dilemma. The simulation results, conducted both macroscopically and microscopically across the network layers in the multiplex, show quantitatively the role of homophily in human cooperation.

Dynamic Gaming Platform (DGP)

Science.gov (United States)

2009-04-01

GAMING PLATFORM (DGP) Lockheed Martin Corporation...YYYY) APR 09 2. REPORT TYPE Final 3. DATES COVERED (From - To) Jul 07 – Mar 09 4. TITLE AND SUBTITLE DYNAMIC GAMING PLATFORM (DGP) 5a...CMU Carnegie Mellon University DGP Dynamic Gaming Platform GA Genetic Algorithm IARPA Intelligence Advanced Research Projects Activity LM ATL Lockheed Martin Advanced Technology Laboratories PAINT ProActive INTelligence

Random and non-random mating populations: Evolutionary dynamics in meiotic drive.

Science.gov (United States)

Sarkar, Bijan

2016-01-01

Game theoretic tools are utilized to analyze a one-locus continuous selection model of sex-specific meiotic drive by considering nonequivalence of the viabilities of reciprocal heterozygotes that might be noticed at an imprinted locus. The model draws attention to the role of viability selections of different types to examine the stable nature of polymorphic equilibrium. A bridge between population genetics and evolutionary game theory has been built up by applying the concept of the Fundamental Theorem of Natural Selection. In addition to pointing out the influences of male and female segregation ratios on selection, configuration structure reveals some noted results, e.g., Hardy-Weinberg frequencies hold in replicator dynamics, occurrence of faster evolution at the maximized variance fitness, existence of mixed Evolutionarily Stable Strategy (ESS) in asymmetric games, the tending evolution to follow not only a 1:1 sex ratio but also a 1:1 different alleles ratio at particular gene locus. Through construction of replicator dynamics in the group selection framework, our selection model introduces a redefining bases of game theory to incorporate non-random mating where a mating parameter associated with population structure is dependent on the social structure. Also, the model exposes the fact that the number of polymorphic equilibria will depend on the algebraic expression of population structure. Copyright © 2015 Elsevier Inc. All rights reserved.

Evolutionary mixed games in structured populations: Cooperation and the benefits of heterogeneity

Science.gov (United States)

Amaral, Marco A.; Wardil, Lucas; Perc, Matjaž; da Silva, Jafferson K. L.

2016-04-01

Evolutionary games on networks traditionally involve the same game at each interaction. Here we depart from this assumption by considering mixed games, where the game played at each interaction is drawn uniformly at random from a set of two different games. While in well-mixed populations the random mixture of the two games is always equivalent to the average single game, in structured populations this is not always the case. We show that the outcome is, in fact, strongly dependent on the distance of separation of the two games in the parameter space. Effectively, this distance introduces payoff heterogeneity, and the average game is returned only if the heterogeneity is small. For higher levels of heterogeneity the distance to the average game grows, which often involves the promotion of cooperation. The presented results support preceding research that highlights the favorable role of heterogeneity regardless of its origin, and they also emphasize the importance of the population structure in amplifying facilitators of cooperation.

A Study on Standard Competition with Network Effect Based on Evolutionary Game Model

Science.gov (United States)

Wang, Ye; Wang, Bingdong; Li, Kangning

Owing to networks widespread in modern society, standard competition with network effect is now endowed with new connotation. This paper aims to study the impact of network effect on standard competition; it is organized in the mode of "introduction-model setup-equilibrium analysis-conclusion". Starting from a well-structured model of evolutionary game, it is then extended to a dynamic analysis. This article proves both theoretically and empirically that whether or not a standard can lead the market trends depends on the utility it would bring, and the author also discusses some advisable strategies revolving around the two factors of initial position and border break.

Evolutionary game theory using agent-based methods.

Science.gov (United States)

Adami, Christoph; Schossau, Jory; Hintze, Arend

2016-12-01

Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Evolutionary Artificial Neural Network Weight Tuning to Optimize Decision Making for an Abstract Game

Science.gov (United States)

2010-03-01

EVOLUTIONARY ARTIFICIAL NEURAL NETWORK WEIGHT TUNING TO OPTIMIZE DECISION MAKING FOR AN ABSTRACT...AFIT/GCS/ENG/10-06 EVOLUTIONARY ARTIFICIAL NEURAL NETWORK WEIGHT TUNING TO OPTIMIZE DECISION MAKING FOR AN ABSTRACT GAME THESIS Presented...35 14: Diagram of pLoGANN’s Artificial Neural Network and

Evolutionary programming for goal-driven dynamic planning

Science.gov (United States)

Vaccaro, James M.; Guest, Clark C.; Ross, David O.

2002-03-01

one step closer to solving more difficult real-world AI problems. Using a hybrid approach that includes adaptation via evolutionary computation for the intelligent planning of a Risk player's turn provides better dynamic intelligent planning than more uniform approaches.

Analysis of Knowledge-Sharing Evolutionary Game in University Teacher Team

Science.gov (United States)

Huo, Mingkui

2013-01-01

The knowledge-sharing activity is a major drive force behind the progress and innovation of university teacher team. Based on the evolutionary game theory, this article analyzes the knowledge-sharing process model of this team, studies the influencing mechanism of various factors such as knowledge aggregate gap, incentive coefficient and risk…

Fixation and escape times in stochastic game learning

International Nuclear Information System (INIS)

Realpe-Gomez, John; Szczesny, Bartosz; Galla, Tobias; Dall’Asta, Luca

2012-01-01

Evolutionary dynamics in finite populations is known to fixate eventually in the absence of mutation. We here show that a similar phenomenon can be found in stochastic game dynamical batch learning, and investigate fixation in learning processes in a simple 2×2 game, for two-player games with cyclic interaction, and in the context of the best-shot network game. The analogues of finite populations in evolution are here finite batches of observations between strategy updates. We study when and how such fixation can occur, and present results on the average time-to-fixation from numerical simulations. Simple cases are also amenable to analytical approaches and we provide estimates of the behaviour of so-called escape times as a function of the batch size. The differences and similarities with escape and fixation in evolutionary dynamics are discussed. (paper)

Dynamic optimization and differential games

CERN Document Server

Friesz, Terry L

2010-01-01

Dynamic Optimization and Differential Games has been written to address the increasing number of Operations Research and Management Science problems that involve the explicit consideration of time and of gaming among multiple agents. With end-of-chapter exercises throughout, it is a book that can be used both as a reference and as a textbook. It will be useful as a guide to engineers, operations researchers, applied mathematicians and social scientists whose work involves both the theoretical and computational aspects of dynamic optimization and differential games. Included throughout the text are detailed explanations of several original dynamic and game-theoretic mathematical models which are of particular relevance in today's technologically-driven-global economy: revenue management, oligopoly pricing, production planning, supply chain management, dynamic traffic assignment and dynamic congestion pricing. The book emphasizes deterministic theory, computational tools and applications associated with the stu...

An Evolutionary Approach to the Climate Change Negotiation Game

Energy Technology Data Exchange (ETDEWEB)

Courtois, P. [CIRED and University of Paris, Paris (France); Pereau, J.C. [OEP, University of Marne-la-Vallee, Marne-la-Vallee (France); Tazdait, T. [CIRED and OEP, University of Marne-la-Vallee, Marne-la-Vallee (France)

2001-10-01

We describe in this paper an evolutionary game theoretic model aiming at representing the climate change negotiation. The model is used to examine the outcome of climate change negotiations in a framework which seeks to closely represent negotiation patterns. Evolutionary setting allows us to consider a decision making structure characterised by agents with bounded knowledge practising mimics and learning from past events and strategies. We show on that framework that a third significant alternative to the binary coordination-defection strategies needs to be considered: a unilateral commitment as precautionary strategy. As a means to widen cooperation, we examine the influence of linking environmental and trade policies via the implementation of a trade penalty on non cooperative behaviours.

An Evolutionary Approach to the Climate Change Negotiation Game

International Nuclear Information System (INIS)

Courtois, P.; Pereau, J.C.; Tazdait, T.

2001-10-01

We describe in this paper an evolutionary game theoretic model aiming at representing the climate change negotiation. The model is used to examine the outcome of climate change negotiations in a framework which seeks to closely represent negotiation patterns. Evolutionary setting allows us to consider a decision making structure characterised by agents with bounded knowledge practising mimics and learning from past events and strategies. We show on that framework that a third significant alternative to the binary coordination-defection strategies needs to be considered: a unilateral commitment as precautionary strategy. As a means to widen cooperation, we examine the influence of linking environmental and trade policies via the implementation of a trade penalty on non cooperative behaviours

Spatial evolutionary games of interaction among generic cancer cells

DEFF Research Database (Denmark)

Bach, L.A.; Sumpter, D.J.T.; Alsner, J.

2003-01-01

Evolutionary game models of cellular interactions have shown that heterogeneity in the cellular genotypic composition is maintained through evolution to stable coexistence of growth-promoting and non-promoting cell types. We generalise these mean-field models and relax the assumption of perfect m...... at a cellular level. This study thus points a new direction towards more plausible spatial tumour modelling and the understanding of cancerous growth....

Dynamic game balancing implementation using adaptive algorithm in mobile-based Safari Indonesia game

Science.gov (United States)

Yuniarti, Anny; Nata Wardanie, Novita; Kuswardayan, Imam

2018-03-01

In developing a game there is one method that should be applied to maintain the interest of players, namely dynamic game balancing. Dynamic game balancing is a process to match a player’s playing style with the behaviour, attributes, and game environment. This study applies dynamic game balancing using adaptive algorithm in scrolling shooter game type called Safari Indonesia which developed using Unity. The game of this type is portrayed by a fighter aircraft character trying to defend itself from insistent enemy attacks. This classic game is chosen to implement adaptive algorithms because it has quite complex attributes to be developed using dynamic game balancing. Tests conducted by distributing questionnaires to a number of players indicate that this method managed to reduce frustration and increase the pleasure factor in playing.

From genes to games: cooperation and cyclic dominance in meiotic drive.

Science.gov (United States)

Traulsen, Arne; Reed, Floyd A

2012-04-21

Evolutionary change can be described on a genotypic level or a phenotypic level. Evolutionary game theory is typically thought of as a phenotypic approach, although it is frequently argued that it can also be used to describe population genetic evolution. Interpreting the interaction between alleles in a diploid genome as a two player game leads to interesting alternative perspectives on genetic evolution. Here we focus on the case of meiotic drive and illustrate how meiotic drive can be directly and precisely interpreted as a social dilemma, such as the prisoners dilemma or the snowdrift game, in which the drive allele takes more than its fair share. Resistance to meiotic drive can lead to the well understood cyclic dominance found in the rock-paper-scissors game. This perspective is well established for the replicator dynamics, but there is still considerable ground for mutual inspiration between the two fields. For example, evolutionary game theorists can benefit from considering the stochastic evolutionary dynamics arising from finite population size. Population geneticists can benefit from game theoretic tools and perspectives on genetic evolution. Copyright © 2011 Elsevier Ltd. All rights reserved.

Cooperation or Competition: An Evolutionary Game Study between Commercial Banks and Big Data-Based E-Commerce Financial Institutions in China

OpenAIRE

Yi Zhao; Dong Li; Liqiang Pan

2015-01-01

On the premise of participants’ bounded rationality and information asymmetry, this paper focuses on the cooperation or competition relationship between Chinese e-commerce financial institutions and commercial banks from the perspective of dynamic game. Theoretical mathematical model is built to analyze an evolutionary stable strategy under different conditions. We adopt real-life data set collected in Alibaba’s network credit loan business case and Jingdong’s supply chain financing business ...

Public goods games in populations with fluctuating size.

Science.gov (United States)

McAvoy, Alex; Fraiman, Nicolas; Hauert, Christoph; Wakeley, John; Nowak, Martin A

2018-05-01

Many mathematical frameworks of evolutionary game dynamics assume that the total population size is constant and that selection affects only the relative frequency of strategies. Here, we consider evolutionary game dynamics in an extended Wright-Fisher process with variable population size. In such a scenario, it is possible that the entire population becomes extinct. Survival of the population may depend on which strategy prevails in the game dynamics. Studying cooperative dilemmas, it is a natural feature of such a model that cooperators enable survival, while defectors drive extinction. Although defectors are favored for any mixed population, random drift could lead to their elimination and the resulting pure-cooperator population could survive. On the other hand, if the defectors remain, then the population will quickly go extinct because the frequency of cooperators steadily declines and defectors alone cannot survive. In a mutation-selection model, we find that (i) a steady supply of cooperators can enable long-term population survival, provided selection is sufficiently strong, and (ii) selection can increase the abundance of cooperators but reduce their relative frequency. Thus, evolutionary game dynamics in populations with variable size generate a multifaceted notion of what constitutes a trait's long-term success. Copyright © 2018 Elsevier Inc. All rights reserved.

Form of an evolutionary tradeoff affects eco-evolutionary dynamics in a predator-prey system.

Science.gov (United States)

Kasada, Minoru; Yamamichi, Masato; Yoshida, Takehito

2014-11-11

Evolution on a time scale similar to ecological dynamics has been increasingly recognized for the last three decades. Selection mediated by ecological interactions can change heritable phenotypic variation (i.e., evolution), and evolution of traits, in turn, can affect ecological interactions. Hence, ecological and evolutionary dynamics can be tightly linked and important to predict future dynamics, but our understanding of eco-evolutionary dynamics is still in its infancy and there is a significant gap between theoretical predictions and empirical tests. Empirical studies have demonstrated that the presence of genetic variation can dramatically change ecological dynamics, whereas theoretical studies predict that eco-evolutionary dynamics depend on the details of the genetic variation, such as the form of a tradeoff among genotypes, which can be more important than the presence or absence of the genetic variation. Using a predator-prey (rotifer-algal) experimental system in laboratory microcosms, we studied how different forms of a tradeoff between prey defense and growth affect eco-evolutionary dynamics. Our experimental results show for the first time to our knowledge that different forms of the tradeoff produce remarkably divergent eco-evolutionary dynamics, including near fixation, near extinction, and coexistence of algal genotypes, with quantitatively different population dynamics. A mathematical model, parameterized from completely independent experiments, explains the observed dynamics. The results suggest that knowing the details of heritable trait variation and covariation within a population is essential for understanding how evolution and ecology will interact and what form of eco-evolutionary dynamics will result.

Evolutionary Snowdrift Game Incorporating Costly Punishment

Directory of Open Access Journals (Sweden)

Yap Yee Jiun

2012-01-01

Full Text Available The role of punishments in promoting cooperation is an important issue. We incorporate costly punishments into the snowdrift game (SG by introducing a third punishing (P character and study the effects.  The punishers, who carry basically a cooperative (C character, are willing to pay a cost of a so as to punish a non-cooperative (D opponent by ß. Depending on the initial fractions of the characters, a, ß, and the cost-to-benefit ratio r in SG, the three-character system evolves either into a steady state consisting only of C and P characters or only of C and D characters in a well-mixed population.  The former situation represents an enhancement in cooperation relative to SG, while the latter is similar to SG. The dynamics in approaching these different steady states are found to be different.  Analytically, the key features in the steady states and dynamics obtained by simulations are captured by a set of differential equations.  The sensitivity to the initial distribution of characters is studied by depicting the flow in a phase portrait and analyzing the nature of fixed points. The analysis also shows the role of P-character in preventing a system from invasion by D-character agents. Starting from a population consisting only of C and P agents, a D-character agent intended to invade the system cannot survive when the initial fraction of P-agents is greater than r/ß. Our model, defined intentionally as a simulation algorithm, can be readily generalized to incorporate many interesting effects, such as those in a networked population. ABSTRAK: Peranan hukuman dalam meningkatkan kerjasama merupakan isu penting.  Hukuman berat diterapkan ke dalam permainan hanyutan salji (snowdrift game (SG dengan memperkenalkan karekter penghukum (P ketiga dan akibatnya dipantau. Penghukum, pada asasnya membawa watak koperatif (C, sanggup membayar kos a, agar dia menghukum lawan yang tidak koperatif (D dengan ß. Bergantung kepada pecahan permulaan watak

Playing Multi-Action Adversarial Games: Online Evolutionary Planning versus Tree Search

DEFF Research Database (Denmark)

Justesen, Niels; Mahlmann, Tobias; Risi, Sebastian

2017-01-01

We address the problem of playing turn-based multi-action adversarial games, which include many strategy games with extremely high branching factors as players take multiple actions each turn. This leads to the breakdown of standard tree search methods, including Monte Carlo Tree Search (MCTS......), as they become unable to reach a sufficient depth in the game tree. In this paper, we introduce Online Evolutionary Planning (OEP) to address this challenge, which searches for combinations of actions to perform during a single turn guided by a fitness function that evaluates the quality of a particular state....... We compare OEP to different MCTS variations that constrain the exploration to deal with the high branching factor in the turn-based multi-action game Hero Academy. While the constrained MCTS variations outperform the vanilla MCTS implementation by a large margin, OEP is able to search the space...

Evolutionary Stable Strategy

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 21; Issue 9. Evolutionary Stable Strategy: Application of Nash Equilibrium in Biology. General Article Volume 21 Issue 9 September 2016 pp 803- ... Keywords. Evolutionary game theory, evolutionary stable state, conflict, cooperation, biological games.

Combining evolutionary game theory and network theory to analyze human cooperation patterns

International Nuclear Information System (INIS)

Scatà, Marialisa; Di Stefano, Alessandro; La Corte, Aurelio; Liò, Pietro; Catania, Emanuele; Guardo, Ermanno; Pagano, Salvatore

2016-01-01

Highlights: • We investigate the evolutionary dynamics of human cooperation in a social network. • We introduce the concepts of “Critical Mass”, centrality measure and homophily. • The emergence of cooperation is affected by the spatial choice of the “Critical Mass”. • Our findings show that homophily speeds up the convergence towards cooperation. • Centrality and “Critical Mass” spatial choice partially offset the impact of homophily. - Abstract: As natural systems continuously evolve, the human cooperation dilemma represents an increasingly more challenging question. Humans cooperate in natural and social systems, but how it happens and what are the mechanisms which rule the emergence of cooperation, represent an open and fascinating issue. In this work, we investigate the evolution of cooperation through the analysis of the evolutionary dynamics of behaviours within the social network, where nodes can choose to cooperate or defect following the classical social dilemmas represented by Prisoner’s Dilemma and Snowdrift games. To this aim, we introduce a sociological concept and statistical estimator, “Critical Mass”, to detect the minimum initial seed of cooperators able to trigger the diffusion process, and the centrality measure to select within the social network. Selecting different spatial configurations of the Critical Mass nodes, we highlight how the emergence of cooperation can be influenced by this spatial choice of the initial core in the network. Moreover, we target to shed light how the concept of homophily, a social shaping factor for which “birds of a feather flock together”, can affect the evolutionary process. Our findings show that homophily allows speeding up the diffusion process and make quicker the convergence towards human cooperation, while centrality measure and thus the Critical Mass selection, play a key role in the evolution showing how the spatial configurations can create some hidden patterns, partially

Importance of tie strengths in the prisoner's dilemma game on social networks

International Nuclear Information System (INIS)

Xu, Bo; Liu, Lu; You, Weijia

2011-01-01

Though numerous researches have shown that tie strengths play a key role in the formation of collective behavior in social networks, little work has been done to explore their impact on the outcome of evolutionary games. In this Letter, we studied the effect of tie strength in the dynamics of evolutionary prisoner's dilemma games by using online social network datasets. The results show that the fraction of cooperators has a non-trivial dependence on tie strength. Weak ties, just like previous researches on epidemics and information diffusion have shown, play a key role by the maintenance of cooperators in evolutionary prisoner's dilemma games. -- Highlights: → Tie strength is used to measure heterogeneous influences of different pairs of nodes. → Weak ties play a role in maintaining cooperation in prisoner's dilemma games. → Micro-dynamics of nodes are illustrated to explain the conclusion.

Gaming Personality and Game Dynamics in Online Discussion Instructions

Science.gov (United States)

Tu, Chih-Hsiung; Yen, Cherng-Jyh; Sujo-Montes, Laura; Roberts, Gayle A.

2015-01-01

Gamification is the use of game mechanics to drive game-like engagements and actions. It applies game mechanics, dynamics and frameworks to promote desired learning behaviours. Positive and effective gamification could enhance learning and engage learners in more social and context-rich decision-making for problem-solving in learning tasks.…

Cancer treatment as a game: integrating evolutionary game theory into the optimal control of chemotherapy

International Nuclear Information System (INIS)

Orlando, Paul A; Gatenby, Robert A; Brown, Joel S

2012-01-01

Chemotherapy for metastatic cancer commonly fails due to evolution of drug resistance in tumor cells. Here, we view cancer treatment as a game in which the oncologists choose a therapy and tumors ‘choose’ an adaptive strategy. We propose the oncologist can gain an upper hand in the game by choosing treatment strategies that anticipate the adaptations of the tumor. In particular, we examine the potential benefit of exploiting evolutionary tradeoffs in tumor adaptations to therapy. We analyze a math model where cancer cells face tradeoffs in allocation of resistance to two drugs. The tumor ‘chooses’ its strategy by natural selection and the oncologist chooses her strategy by solving a control problem. We find that when tumor cells perform best by investing resources to maximize response to one drug the optimal therapy is a time-invariant delivery of both drugs simultaneously. However, if cancer cells perform better using a generalist strategy allowing resistance to both drugs simultaneously, then the optimal protocol is a time varying solution in which the two drug concentrations negatively covary. However, drug interactions can significantly alter these results. We conclude that knowledge of both evolutionary tradeoffs and drug interactions is crucial in planning optimal chemotherapy schedules for individual patients. (paper)

Cancer treatment as a game: integrating evolutionary game theory into the optimal control of chemotherapy

Science.gov (United States)

Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.

2012-12-01

Chemotherapy for metastatic cancer commonly fails due to evolution of drug resistance in tumor cells. Here, we view cancer treatment as a game in which the oncologists choose a therapy and tumors ‘choose’ an adaptive strategy. We propose the oncologist can gain an upper hand in the game by choosing treatment strategies that anticipate the adaptations of the tumor. In particular, we examine the potential benefit of exploiting evolutionary tradeoffs in tumor adaptations to therapy. We analyze a math model where cancer cells face tradeoffs in allocation of resistance to two drugs. The tumor ‘chooses’ its strategy by natural selection and the oncologist chooses her strategy by solving a control problem. We find that when tumor cells perform best by investing resources to maximize response to one drug the optimal therapy is a time-invariant delivery of both drugs simultaneously. However, if cancer cells perform better using a generalist strategy allowing resistance to both drugs simultaneously, then the optimal protocol is a time varying solution in which the two drug concentrations negatively covary. However, drug interactions can significantly alter these results. We conclude that knowledge of both evolutionary tradeoffs and drug interactions is crucial in planning optimal chemotherapy schedules for individual patients.

Modeling evolutionary games in populations with demographic structure

DEFF Research Database (Denmark)

Li, Xiang-Yi; Giaimo, Stefano; Baudisch, Annette

2015-01-01

interactions, but usually omits life history and the demographic structure of the population. Here we show how an integration of both aspects can substantially alter the underlying evolutionary dynamics. We study the replicator dynamics of strategy interactions in life stage structured populations. Individuals...

Development of a population of cancer cells: Observation and modeling by a Mixed Spatial Evolutionary Games approach.

Science.gov (United States)

Świerniak, Andrzej; Krześlak, Michał; Student, Sebastian; Rzeszowska-Wolny, Joanna

2016-09-21

Living cells, like whole living organisms during evolution, communicate with their neighbors, interact with the environment, divide, change their phenotypes, and eventually die. The development of specific ways of communication (through signaling molecules and receptors) allows some cellular subpopulations to survive better, to coordinate their physiological status, and during embryonal development to create tissues and organs or in some conditions to become tumors. Populations of cells cultured in vitro interact similarly, also competing for space and nutrients and stimulating each other to better survive or to die. The results of these intercellular interactions of different types seem to be good examples of biological evolutionary games, and have been the subjects of simulations by the methods of evolutionary game theory where individual cells are treated as players. Here we present examples of intercellular contacts in a population of living human cancer HeLa cells cultured in vitro and propose an evolutionary game theory approach to model the development of such populations. We propose a new technique termed Mixed Spatial Evolutionary Games (MSEG) which are played on multiple lattices corresponding to the possible cellular phenotypes which gives the possibility of simulating and investigating the effects of heterogeneity at the cellular level in addition to the population level. Analyses performed with MSEG suggested different ways in which cellular populations develop in the case of cells communicating directly and through factors released to the environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simulation of producers behaviour in the electricity market by evolutionary games

Energy Technology Data Exchange (ETDEWEB)

Menniti, Daniele; Pinnarelli, Anna; Sorrentino, Nicola [Department of Electronic, Computer and System Science, University of Calabria (Italy)

2008-03-15

Simulation of the electricity market participant's behaviour is important for producers and consumers to determine their bidding strategies and for regulating the market rules. In literature, for this aim a lot of papers suggest to use the well-known theory of non-cooperative games and the concept of Nash equilibrium. Unfortunately they cannot be applied in an easy way when a multi-players game has to be considered to simulate the operation of the electricity market. In this paper, the authors suggest to use the new theory of evolutionary games and the concept of near Nash equilibrium to simulate the electricity market in the presence of more than two producers. In particular, an opportune genetic algorithm has been developed; from the results reported in the paper, it is clear that this algorithm can be usefully utilised. (author)

Simulation of producers behaviour in the electricity market by evolutionary games

International Nuclear Information System (INIS)

Menniti, Daniele; Pinnarelli, Anna; Sorrentino, Nicola

2008-01-01

Simulation of the electricity market participant's behaviour is important for producers and consumers to determine their bidding strategies and for regulating the market rules. In literature, for this aim a lot of papers suggest to use the well-known theory of non-cooperative games and the concept of Nash equilibrium. Unfortunately they cannot be applied in an easy way when a multi-players game has to be considered to simulate the operation of the electricity market. In this paper, the authors suggest to use the new theory of evolutionary games and the concept of near Nash equilibrium to simulate the electricity market in the presence of more than two producers. In particular, an opportune genetic algorithm has been developed; from the results reported in the paper, it is clear that this algorithm can be usefully utilised. (author)

The limits of weak selection and large population size in evolutionary game theory.

Science.gov (United States)

Sample, Christine; Allen, Benjamin

2017-11-01

Evolutionary game theory is a mathematical approach to studying how social behaviors evolve. In many recent works, evolutionary competition between strategies is modeled as a stochastic process in a finite population. In this context, two limits are both mathematically convenient and biologically relevant: weak selection and large population size. These limits can be combined in different ways, leading to potentially different results. We consider two orderings: the [Formula: see text] limit, in which weak selection is applied before the large population limit, and the [Formula: see text] limit, in which the order is reversed. Formal mathematical definitions of the [Formula: see text] and [Formula: see text] limits are provided. Applying these definitions to the Moran process of evolutionary game theory, we obtain asymptotic expressions for fixation probability and conditions for success in these limits. We find that the asymptotic expressions for fixation probability, and the conditions for a strategy to be favored over a neutral mutation, are different in the [Formula: see text] and [Formula: see text] limits. However, the ordering of limits does not affect the conditions for one strategy to be favored over another.

An evolutionary model of cooperation, fairness and altruistic punishment in public good games.

Directory of Open Access Journals (Sweden)

Moritz Hetzer

Full Text Available We identify and explain the mechanisms that account for the emergence of fairness preferences and altruistic punishment in voluntary contribution mechanisms by combining an evolutionary perspective together with an expected utility model. We aim at filling a gap between the literature on the theory of evolution applied to cooperation and punishment, and the empirical findings from experimental economics. The approach is motivated by previous findings on other-regarding behavior, the co-evolution of culture, genes and social norms, as well as bounded rationality. Our first result reveals the emergence of two distinct evolutionary regimes that force agents to converge either to a defection state or to a state of coordination, depending on the predominant set of self- or other-regarding preferences. Our second result indicates that subjects in laboratory experiments of public goods games with punishment coordinate and punish defectors as a result of an aversion against disadvantageous inequitable outcomes. Our third finding identifies disadvantageous inequity aversion as evolutionary dominant and stable in a heterogeneous population of agents endowed initially only with purely self-regarding preferences. We validate our model using previously obtained results from three independently conducted experiments of public goods games with punishment.

An evolutionary model of cooperation, fairness and altruistic punishment in public good games.

Science.gov (United States)

Hetzer, Moritz; Sornette, Didier

2013-01-01

We identify and explain the mechanisms that account for the emergence of fairness preferences and altruistic punishment in voluntary contribution mechanisms by combining an evolutionary perspective together with an expected utility model. We aim at filling a gap between the literature on the theory of evolution applied to cooperation and punishment, and the empirical findings from experimental economics. The approach is motivated by previous findings on other-regarding behavior, the co-evolution of culture, genes and social norms, as well as bounded rationality. Our first result reveals the emergence of two distinct evolutionary regimes that force agents to converge either to a defection state or to a state of coordination, depending on the predominant set of self- or other-regarding preferences. Our second result indicates that subjects in laboratory experiments of public goods games with punishment coordinate and punish defectors as a result of an aversion against disadvantageous inequitable outcomes. Our third finding identifies disadvantageous inequity aversion as evolutionary dominant and stable in a heterogeneous population of agents endowed initially only with purely self-regarding preferences. We validate our model using previously obtained results from three independently conducted experiments of public goods games with punishment.

Study on Cooperative Mechanism of Prefabricated Producers Based on Evolutionary Game Theory

Directory of Open Access Journals (Sweden)

Tongyao Feng

2017-01-01

Full Text Available Good cooperation mechanism is an important guarantee for the advancement of industrialization construction. To strengthen the partnership between producers, we analyze the behavior evolution trend of both parties using an evolutionary game theory. Based on the original model, the mechanism of coordination and cooperation between prefabricated producers is explained under the condition of punishment and incentive. The results indicate that stable evolutionary strategies exist under both cooperation and noncooperation, and the evolutionary results are influenced by the initial proportion of both decision-making processes. The government can support the production enterprises to establish a solid partnership through effective punishment and incentive mechanisms to reduce the initial cost in the supply chain of prefabricated construction, resulting in a win-win situation.

Evolutionary Game Model Study of Construction Green Supply Chain Management under the Government Intervention

Science.gov (United States)

Xing, Yuanzhi; Deng, Xiaoyi

2017-11-01

The paper first has defined the concepts of green supply chain management and evolution game theory, and pointed out the characteristics of green supply chain management in construction. The main participants and key links of the construction green supply chain management are determined by constructing the organization framework. This paper established the evolutionary game model between construction enterprises and recycling enterprises for the green supply chain closed-loop structure. The waste recycling evolutionary stability equilibrium solution is obtained to explore the principle and effective scope of government policy intervention. This paper put forward the relevant countermeasures to the green supply chain management in construction recycling stage from the government point of view. The conclusion has reference value and guidance to the final product construction enterprises, recycling enterprises and the government during green supply chain.

Importance of tie strengths in the prisoner's dilemma game on social networks

Science.gov (United States)

Xu, Bo; Liu, Lu; You, Weijia

2011-06-01

Though numerous researches have shown that tie strengths play a key role in the formation of collective behavior in social networks, little work has been done to explore their impact on the outcome of evolutionary games. In this Letter, we studied the effect of tie strength in the dynamics of evolutionary prisoner's dilemma games by using online social network datasets. The results show that the fraction of cooperators has a non-trivial dependence on tie strength. Weak ties, just like previous researches on epidemics and information diffusion have shown, play a key role by the maintenance of cooperators in evolutionary prisoner's dilemma games.

Eco-evolutionary spatial dynamics in the Glanville fritillary butterfly.

Science.gov (United States)

Hanski, Ilkka A

2011-08-30

Demographic population dynamics, gene flow, and local adaptation may influence each other and lead to coupling of ecological and evolutionary dynamics, especially in species inhabiting fragmented heterogeneous environments. Here, I review long-term research on eco-evolutionary spatial dynamics in the Glanville fritillary butterfly inhabiting a large network of approximately 4,000 meadows in Finland. The metapopulation persists in a balance between frequent local extinctions and recolonizations. The genetic spatial structure as defined by neutral markers is much more coarse-grained than the demographic spatial structure determined by the fragmented habitat, yet small-scale spatial structure has important consequences for the dynamics. I discuss three examples of eco-evolutionary spatial dynamics. (i) Extinction-colonization metapopulation dynamics influence allele frequency changes in the phosphoglucose isomerase (Pgi) gene, which leads to strong associations between genetic variation in Pgi and dispersal, recolonization, and local population dynamics. (ii) Inbreeding in local populations increases their risk for extinction, whereas reciprocal effects between inbreeding, population size, and emigration represent likely eco-evolutionary feedbacks. (iii) Genetically determined female oviposition preference for two host plant species exhibits a cline paralleling a gradient in host plant relative abundances, and host plant preference of dispersing females in relation to the host plant composition of habitat patches influences immigration (gene flow) and recolonization (founder events). Eco-evolutionary spatial dynamics in heterogeneous environments may not lead to directional evolutionary changes unless the environment itself changes, but eco-evolutionary dynamics may contribute to the maintenance of genetic variation attributable to fluctuating selection in space and time.

System Dynamics and Serious Games

OpenAIRE

Van Daalen, C.; Schaffernicht, M.; Mayer, I.

2014-01-01

This paper deals with the relationship between serious games and system dynamics. Games have been used in SD since the beginning. However, the field of serious gaming also has its own development. The purpose of this contribution is to provide a broad overview of the combination of serious gaming and SD and discuss the state of the art and promise. We first define serious game, simulation and case study and then point out how SD overlaps with them. Then we move on to define the basic componen...

Selection-Mutation Dynamics of Signaling Games

Directory of Open Access Journals (Sweden)

Josef Hofbauer

2015-01-01

Full Text Available We study the structure of the rest points of signaling games and their dynamic behavior under selection-mutation dynamics by taking the case of three signals as our canonical example. Many rest points of the replicator dynamics of signaling games are not isolated and, therefore, not robust under perturbations. However, some of them attract open sets of initial conditions. We prove the existence of certain rest points of the selection-mutation dynamics close to Nash equilibria of the signaling game and show that all but the perturbed rest points close to strict Nash equilibria are dynamically unstable. This is an important result for the evolution of signaling behavior, since it shows that the second-order forces that are governed by mutation can increase the chances of successful signaling.

Stability properties of nonlinear dynamical systems and evolutionary stable states

Energy Technology Data Exchange (ETDEWEB)

Gleria, Iram, E-mail: iram@fis.ufal.br [Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió-AL (Brazil); Brenig, Leon [Faculté des Sciences, Université Libre de Bruxelles, 1050 Brussels (Belgium); Rocha Filho, Tarcísio M.; Figueiredo, Annibal [Instituto de Física and International Center for Condensed Matter Physics, Universidade de Brasília, 70919-970 Brasília-DF (Brazil)

2017-03-18

Highlights: • We address the problem of equilibrium stability in a general class of non-linear systems. • We link Evolutionary Stable States (ESS) to stable fixed points of square quasi-polynomial (QP) systems. • We show that an interior ES point may be related to stable interior fixed points of QP systems. - Abstract: In this paper we address the problem of stability in a general class of non-linear systems. We establish a link between the concepts of asymptotic stable interior fixed points of square Quasi-Polynomial systems and evolutionary stable states, a property of some payoff matrices arising from evolutionary games.

Importance of tie strengths in the prisoner's dilemma game on social networks

Energy Technology Data Exchange (ETDEWEB)

Xu, Bo, E-mail: xubosuper@163.com [Department of Information Systems, School of Economics and Management, Beihang University (China); Liu, Lu; You, Weijia [Department of Information Systems, School of Economics and Management, Beihang University (China)

2011-06-13

Though numerous researches have shown that tie strengths play a key role in the formation of collective behavior in social networks, little work has been done to explore their impact on the outcome of evolutionary games. In this Letter, we studied the effect of tie strength in the dynamics of evolutionary prisoner's dilemma games by using online social network datasets. The results show that the fraction of cooperators has a non-trivial dependence on tie strength. Weak ties, just like previous researches on epidemics and information diffusion have shown, play a key role by the maintenance of cooperators in evolutionary prisoner's dilemma games. -- Highlights: → Tie strength is used to measure heterogeneous influences of different pairs of nodes. → Weak ties play a role in maintaining cooperation in prisoner's dilemma games. → Micro-dynamics of nodes are illustrated to explain the conclusion.

Role of update dynamics in the collective cooperation on the spatial snowdrift games: Beyond unconditional imitation and replicator dynamics

International Nuclear Information System (INIS)

Xia Chengyi; Wang Juan; Wang Li; Sun Shiwen; Sun Junqing; Wang Jinsong

2012-01-01

Highlights: ► We investigate the role of update rules in the spatial snowdrift game on regular lattices. ► Compared with UI and replicator rules, the cooperation can be further promoted by the Moran rule. ► f c and the cluster formation pattern for these three update rules are carefully explored. ► The frequency of cooperators is insensitive to the random initial set of players. - Abstract: In this paper, we investigate the role of update or imitation rules in the spatial snowdrift game on regular lattices. Three different update rules, including unconditional imitation (UI), replicator dynamics (RD) and the Moran process, are utilized to update the strategies of focal players during the game process in the spatial snowdrift on the lattice. We observe that the aggregate cooperation level between players is largely elevated by using the Moran process in the spatial snowdrift game, when compared to the UI or replicator dynamics. Meanwhile, we carefully explore the dynamical evolution of frequency of cooperators and the cluster formation pattern for these three update rules. Moreover, it is also shown that the evolutionary behavior under the Moran update is independent of and insensitive to the randomly initial configurations of cooperators and defectors. The current results clearly indicate that the introduction of moderate randomness in the strategy update will highly promote the maintenance and persistence of cooperation among selfish individuals, which will be greatly instrumental to deeply understand the evolution of cooperation within many natural, biological and social systems.

Theoretical Approaches in Evolutionary Ecology: Environmental Feedback as a Unifying Perspective.

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Lion, Sébastien

2018-01-01

Evolutionary biology and ecology have a strong theoretical underpinning, and this has fostered a variety of modeling approaches. A major challenge of this theoretical work has been to unravel the tangled feedback loop between ecology and evolution. This has prompted the development of two main classes of models. While quantitative genetics models jointly consider the ecological and evolutionary dynamics of a focal population, a separation of timescales between ecology and evolution is assumed by evolutionary game theory, adaptive dynamics, and inclusive fitness theory. As a result, theoretical evolutionary ecology tends to be divided among different schools of thought, with different toolboxes and motivations. My aim in this synthesis is to highlight the connections between these different approaches and clarify the current state of theory in evolutionary ecology. Central to this approach is to make explicit the dependence on environmental dynamics of the population and evolutionary dynamics, thereby materializing the eco-evolutionary feedback loop. This perspective sheds light on the interplay between environmental feedback and the timescales of ecological and evolutionary processes. I conclude by discussing some potential extensions and challenges to our current theoretical understanding of eco-evolutionary dynamics.

Evolutionary quantum game theory in the context of socio-economic systems; Evolutionaere Quanten-Spieltheorie im Kontext sozio-oekonomischer Systeme

Energy Technology Data Exchange (ETDEWEB)

Hanauske, Matthias

2011-02-14

The evolution of socio-economic systems depend on the interdependent decision processes of its underlying system components. The mathematical model to describe the strategic decision of players within a socio-economic game is ''game theory''. ''Quantum game theory'' is a mathematical and conceptual amplification of classical game theory. The space of all conceivable decision paths is extended from the purely rational, measurable space in the Hilbert-space of complex numbers - which is the mathematical space where quantum theory is formulated. By the concept of a potential entanglement of the imaginary quantum strategy parts, it is possible to include cooperate decision path, caused by cultural or moral standards. If this strategy entanglement is large enough, then additional Nash equilibria can occur, previously present dominant strategies could become nonexistent and new evolutionary stable strategies do appear for some game classes. Within this PhD thesis the main results of classical and quantum games are summarized and all of the possible game classes of evolutionary (2 player)-(2 strategy) games are extended to quantum games. It is shown that the quantum extension of classical games with an underlying dilemma-like structure give different results, if the strength of strategic entanglement is above a certain barrier. After the German summary and the introduction paper, five different applications of the theory are discussed within the thesis. (orig.)

Cooperation enhanced by the coevolution of teaching activity in evolutionary prisoner's dilemma games with voluntary participation.

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Shen, Chen; Chu, Chen; Geng, Yini; Jin, Jiahua; Chen, Fei; Shi, Lei

2018-01-01

Voluntary participation, as an additional strategy involved in repeated games, has been proved to be an efficient way to promote the evolution of cooperation theoretically and empirically. Besides, current studies show that the coevolution of teaching activity can promote cooperation. Thus, inspired by aforementioned above, we investigate the effect of coevolution of teaching activity on the evolution of cooperation for prisoner's dilemma game with voluntary participation: when the focal player successfully enforces its strategy on the opponent, his teaching ability will get an increase. Through numerical simulation, we have shown that voluntary participation could effectively promote the fraction of cooperation, which is also affected by the value of increment. Furthermore, we investigate the influence of the increment value on the density of different strategies and find that there exists an optimal increment value that plays an utmost role on the evolutionary dynamics. With regard to this observation, we unveil that an optimal value of increment can lead to strongest heterogeneity in agents' teaching ability, further promoting the evolution of cooperation.

Cooperation enhanced by the coevolution of teaching activity in evolutionary prisoner's dilemma games with voluntary participation.

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Chen Shen

Full Text Available Voluntary participation, as an additional strategy involved in repeated games, has been proved to be an efficient way to promote the evolution of cooperation theoretically and empirically. Besides, current studies show that the coevolution of teaching activity can promote cooperation. Thus, inspired by aforementioned above, we investigate the effect of coevolution of teaching activity on the evolution of cooperation for prisoner's dilemma game with voluntary participation: when the focal player successfully enforces its strategy on the opponent, his teaching ability will get an increase. Through numerical simulation, we have shown that voluntary participation could effectively promote the fraction of cooperation, which is also affected by the value of increment. Furthermore, we investigate the influence of the increment value on the density of different strategies and find that there exists an optimal increment value that plays an utmost role on the evolutionary dynamics. With regard to this observation, we unveil that an optimal value of increment can lead to strongest heterogeneity in agents' teaching ability, further promoting the evolution of cooperation.

Teaching methods for increasing the participations of students: Innovative dynamics games Teaching methods for increasing the participations of students: Innovative dynamics games Teaching methods for increasing the participations of students: Innovative dynamics games

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Ester Oliveras

2013-09-01

Full Text Available Purpose: This paper analyses new dynamics as teaching methodologies in the context of   the degrees adapted to the EHEA. The aim of this study is double: to assess whether there is greater involvement in seminars with these new dynamics and to test if learning also experienced changes. Design/methodology/approach: To experiment with the introduction of innovative dynamic games in an introductory course in accounting.  These new dynamics are applied during the academic year 2010-11 in the UPF. The design, implementation and evaluation of the methodology devised have followed three stages: 1 Game Design and adequate dynamic; 2 To test the games; 2 Implementation during the course. Findings: The results show that students value positively those dynamics improving their learning and creating greater involvement. Research limitations/implications: There are some contradictory results regarding the knowledge gained by the students. Another area to be explored relates to the skills that the teacher must have in order to manage this type of dynamics. Originality/value: In an introductory level of the Financial Accounting course the most common dynamics is solving exercises. Due to the nature of matter, these are closed so they not provoke discussion among students. However, you can use activities that allow greater participation, especially through dynamics or games. This paper shows that.Purpose: This paper analyses new dynamics as teaching methodologies in the context of   the degrees adapted to the EHEA. The aim of this study is double: to assess whether there is greater involvement in seminars with these new dynamics and to test if learning also experienced changes.Design/methodology/approach: To experiment with the introduction of innovative dynamic games in an introductory course in accounting.  These new dynamics are applied during the academic year 2010-11 in the UPF. The design, implementation and evaluation of the methodology devised

A study of the dynamics of multi-player games on small networks using territorial interactions.

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Broom, Mark; Lafaye, Charlotte; Pattni, Karan; Rychtář, Jan

2015-12-01

Recently, the study of structured populations using models of evolutionary processes on graphs has begun to incorporate a more general type of interaction between individuals, allowing multi-player games to be played among the population. In this paper, we develop a birth-death dynamics for use in such models and consider the evolution of populations for special cases of very small graphs where we can easily identify all of the population states and carry out exact analyses. To do so, we study two multi-player games, a Hawk-Dove game and a public goods game. Our focus is on finding the fixation probability of an individual from one type, cooperator or defector in the case of the public goods game, within a population of the other type. We compare this value for both games on several graphs under different parameter values and assumptions, and identify some interesting general features of our model. In particular there is a very close relationship between the fixation probability and the mean temperature, with high temperatures helping fitter individuals and punishing unfit ones and so enhancing selection, whereas low temperatures give a levelling effect which suppresses selection.

Plausibility orderings in dynamic games

NARCIS (Netherlands)

Perea ý Monsuwé, A.

2014-01-01

In this paper we explore game-theoretic reasoning in dynamic games within the framework of belief revision theory. More precisely, we focus on the forward induction concept of ‘common strong belief in rationality’ (Battigalli and Siniscalchi (2002) and the backward induction concept of ‘common

The migration game in habitat network: the case of tuna

DEFF Research Database (Denmark)

Mariani, Patrizio; Krivan, Vlastimil; MacKenzie, Brian

2016-01-01

migration in direction of increasing fitness should lead to the ideal free distribution (IFD) which is the evolutionary stable strategy of the habitat selection game. We introduce a migration game which focuses on migrating dynamics leading to the IFD for age-structured populations and in time varying...

Tractable dynamic global games and applications

Czech Academy of Sciences Publication Activity Database

Mathevet, L.; Steiner, Jakub

2013-01-01

Roč. 148, č. 6 (2013), s. 2583-2619 ISSN 0022-0531 Institutional support: RVO:67985998 Keywords : global games * dynamic game * coordination Subject RIV: AH - Economics Impact factor: 0.919, year: 2013

Advances in dynamic and mean field games theory, applications, and numerical methods

CERN Document Server

Viscolani, Bruno

2017-01-01

This contributed volume considers recent advances in dynamic games and their applications, based on presentations given at the 17th Symposium of the International Society of Dynamic Games, held July 12-15, 2016, in Urbino, Italy. Written by experts in their respective disciplines, these papers cover various aspects of dynamic game theory including mean-field games, stochastic and pursuit-evasion games, and computational methods for dynamic games. Topics covered include Pedestrian flow in crowded environments Models for climate change negotiations Nash Equilibria for dynamic games involving Volterra integral equations Differential games in healthcare markets Linear-quadratic Gaussian dynamic games Aircraft control in wind shear conditions Advances in Dynamic and Mean-Field Games presents state-of-the-art research in a wide spectrum of areas. As such, it serves as a testament to the continued vitality and growth of the field of dynamic games and their applications. It will be of interest to an interdisciplinar...

Evolutionary stability concepts in a stochastic environment

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Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi

2017-09-01

Over the past 30 years, evolutionary game theory and the concept of an evolutionarily stable strategy have been not only extensively developed and successfully applied to explain the evolution of animal behaviors, but also widely used in economics and social sciences. Nonetheless, the stochastic dynamical properties of evolutionary games in randomly fluctuating environments are still unclear. In this study, we investigate conditions for stochastic local stability of fixation states and constant interior equilibria in a two-phenotype model with random payoffs following pairwise interactions. Based on this model, we develop the concepts of stochastic evolutionary stability (SES) and stochastic convergence stability (SCS). We show that the condition for a pure strategy to be SES and SCS is more stringent than in a constant environment, while the condition for a constant mixed strategy to be SES is less stringent than the condition to be SCS, which is less stringent than the condition in a constant environment.

The Dynamics of the Discrete Ultimatum Game and the Role of the Expectation Level

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Lili Deng

2016-01-01

Full Text Available We have studied evolutionary ultimatum game with spatially arranged players, who have choice between the two kinds of strategies (named greedy and altruist. The strategies in the ultimatum game here are described by p(i and a(i, that is, the probability of offering i to himself and the accepting probability when receiving i. By using computer simulations with C++ builder, we have provided the dynamics of the greedy and altruistic strategies and found that the proportion evolution of the “greedy” strategy for different initial cases is approximately 60%. Furthermore, the explanations for the interesting phenomenon are presented from different aspects. In addition, we illustrate that the factor of the expectation level (aspiration level in the updating rule plays an important role in the promotion of altruistic behaviors.

Effects of Inertia on Evolutionary Prisoner's Dilemma Game

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Du, Wen-Bo; Cao, Xian-Bin; Liu, Run-Ran; Wang, Zhen

2012-09-01

Considering the inertia of individuals in real life, we propose a modified Fermi updating rule, where the inertia of players is introduced into evolutionary prisoner's dilemma game (PDG) on square lattices. We mainly focus on how the inertia affects the cooperative behavior of the system. Interestingly, we find that the cooperation level has a nonmonotonic dependence on the inertia: with small inertia, cooperators will soon be invaded by defectors; with large inertia, players are unwilling to change their strategies and the cooperation level remains the same as the initial state; while a moderate inertia can induce the highest cooperation level. Moreover, effects of environmental noise and individual inertia are studied. Our work may be helpful in understanding the emergence and persistence of cooperation in nature and society.

Argoball: A Dynamic-Rules Game for Teaching Striking-and-Fielding Game Tactics

Science.gov (United States)

Todorovich, John R.; Fox, James P.; Ryan, Stuart; Todorovich, Sarah W.

2008-01-01

Physical educators using the teaching games for understanding (TGFU) approach employ modified game forms to teach children skills and tactics. Inspired by Danish Longball, "Argoball" is a dynamic-rules game that teachers interested in the TGFU model use to help their students develop effective skills and tactics to better participate in…

Game dynamic model for yeast development.

Science.gov (United States)

Huang, Yuanyuan; Wu, Zhijun

2012-07-01

Game theoretic models, along with replicator equations, have been applied successfully to the study of evolution of populations of competing species, including the growth of a population, the reaching of the population to an equilibrium state, and the evolutionary stability of the state. In this paper, we analyze a game model proposed by Gore et al. (Nature 456:253-256, 2009) in their recent study on the co-development of two mixed yeast strains. We examine the mathematical properties of this model with varying experimental parameters. We simulate the growths of the yeast strains and compare them with the experimental results. We also compute and analyze the equilibrium state of the system and prove that it is asymptotically and evolutionarily stable.

Forest insurance market participants’ game behavior in China: An analysis based on tripartite dynamic game model

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Ning Ma

2015-11-01

Full Text Available Purpose: In forest insurance market, there are three main participants including the insurance company, the forest farmer and the government. As different participant has different benefit object, there will be a complex and dynamic game relationship among all participants. The purpose of this paper is to make the game relationship among all participants in forest insurance market clear, and then to put forward some policy suggestions on the implementation of forest insurance from the view of game theory. Design/methodology/approach: Firstly, the static game model between the insurance company and the forest farmer is set up. According to the result of static game model, it’s difficult to implement forest insurance without government. Secondly, the tripartite dynamic game model among the government, the insurance company and the forest farmer is proposed, and the equilibrium solution of tripartite dynamic game model is acquired. Finally, the behavioral characteristics of all participants are analyzed according to the equilibrium solution of tripartite dynamic game model. Findings: the government’s allowance will be an important positive factor to implement forest insurance. The loss of the insurance company, which the lower insurance premium brings, can be compensated by the allowance from the government. The more the government provides allowance, the more actively the insurance company will implement forest insurance at a low insurance premium. In this situation, the forest farmer will be more likely to purchase the forest insurance, then the scope of forest insurance implementation will expend. Originality/value: There is a complex and dynamic game relationship among all participants in forest insurance market. Based on the tripartite dynamic game model, to make the game relationship between each participant clear is conducive to the implementation of forest insurance market in China.

Interplay between social influence and competitive strategical games in multiplex networks.

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Amato, Roberta; Díaz-Guilera, Albert; Kleineberg, Kaj-Kolja

2017-08-01

We present a model that takes into account the coupling between evolutionary game dynamics and social influence. Importantly, social influence and game dynamics take place in different domains, which we model as different layers of a multiplex network. We show that the coupling between these dynamical processes can lead to cooperation in scenarios where the pure game dynamics predicts defection. In addition, we show that the structure of the network layers and the relation between them can further increase cooperation. Remarkably, if the layers are related in a certain way, the system can reach a polarized metastable state. These findings could explain the prevalence of polarization observed in many social dilemmas.

Evolutionary Game Theory-Based Evaluation of P2P File-Sharing Systems in Heterogeneous Environments

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Yusuke Matsuda

2010-01-01

Full Text Available Peer-to-Peer (P2P file sharing is one of key technologies for achieving attractive P2P multimedia social networking. In P2P file-sharing systems, file availability is improved by cooperative users who cache and share files. Note that file caching carries costs such as storage consumption and processing load. In addition, users have different degrees of cooperativity in file caching and they are in different surrounding environments arising from the topological structure of P2P networks. With evolutionary game theory, this paper evaluates the performance of P2P file sharing systems in such heterogeneous environments. Using micro-macro dynamics, we analyze the impact of the heterogeneity of user selfishness on the file availability and system stability. Further, through simulation experiments with agent-based dynamics, we reveal how other aspects, for example, synchronization among nodes and topological structure, affect the system performance. Both analytical and simulation results show that the environmental heterogeneity contributes to the file availability and system stability.

Cooperation or Competition: An Evolutionary Game Study between Commercial Banks and Big Data-Based E-Commerce Financial Institutions in China

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Yi Zhao

2015-01-01

Full Text Available On the premise of participants’ bounded rationality and information asymmetry, this paper focuses on the cooperation or competition relationship between Chinese e-commerce financial institutions and commercial banks from the perspective of dynamic game. Theoretical mathematical model is built to analyze an evolutionary stable strategy under different conditions. We adopt real-life data set collected in Alibaba’s network credit loan business case and Jingdong’s supply chain financing business case to verify the evolution process of cooperation and competition relationship. The results show that (cooperation, cooperation is bound to be the evolutionary stable strategy (ESS and cooperation tends to be increasingly in-depth and expansive for commercial banks as well as e-commerce financial institutions in China. The complementarity of participants’ core competitiveness is explored as the root of cooperation. Finally, strategic suggestions are put forward on cooperation between e-commerce financial institutions and commercial banks.

Coevolution of network structure and cooperation in the public goods game

International Nuclear Information System (INIS)

Wang Lei; Xia Chengyi; Wang Juan

2013-01-01

Recently, the emergence of cooperation has become a central topic in the evolutionary game field, and coevolution of game dynamics and network topology structure can give us a fresh viewpoint of how the network evolves and cooperation arises. In this paper, we show in detail a picture of the co-evolutionary behaviors between the microscopic structure of the network and cooperation promotion in the public goods game (PGG). Based on a mechanism named after evolutionary preferential attachment (EPA), in which the growth of the network depends on the outcome of PGG dynamics, we explore the structural properties of networks and cooperative behaviors taking place on the networks created by EPA rules. Extensive simulation results indicate that the structure of the resulting networks displays a transition from homogeneous to heterogeneous properties as the selection strength ϵ increases, and the cooperative behaviors have a non-trivial state in which cooperators and defectors can simultaneously occupy the hub nodes in the network. Current results are of interest for us to further understand the cooperation persistence and structure evolution in many natural, social and economical systems. (paper)

Evolutionary Dynamics of Nitrogen Fixation in the Legume–Rhizobia Symbiosis

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Fujita, Hironori; Aoki, Seishiro; Kawaguchi, Masayoshi

2014-01-01

The stabilization of host–symbiont mutualism against the emergence of parasitic individuals is pivotal to the evolution of cooperation. One of the most famous symbioses occurs between legumes and their colonizing rhizobia, in which rhizobia extract nutrients (or benefits) from legume plants while supplying them with nitrogen resources produced by nitrogen fixation (or costs). Natural environments, however, are widely populated by ineffective rhizobia that extract benefits without paying costs and thus proliferate more efficiently than nitrogen-fixing cooperators. How and why this mutualism becomes stabilized and evolutionarily persists has been extensively discussed. To better understand the evolutionary dynamics of this symbiosis system, we construct a simple model based on the continuous snowdrift game with multiple interacting players. We investigate the model using adaptive dynamics and numerical simulations. We find that symbiotic evolution depends on the cost–benefit balance, and that cheaters widely emerge when the cost and benefit are similar in strength. In this scenario, the persistence of the symbiotic system is compatible with the presence of cheaters. This result suggests that the symbiotic relationship is robust to the emergence of cheaters, and may explain the prevalence of cheating rhizobia in nature. In addition, various stabilizing mechanisms, such as partner fidelity feedback, partner choice, and host sanction, can reinforce the symbiotic relationship by affecting the fitness of symbionts in various ways. This result suggests that the symbiotic relationship is cooperatively stabilized by various mechanisms. In addition, mixed nodule populations are thought to encourage cheater emergence, but our model predicts that, in certain situations, cheaters can disappear from such populations. These findings provide a theoretical basis of the evolutionary dynamics of legume–rhizobia symbioses, which is extendable to other single-host, multiple

When Reputation Enforces Evolutionary Cooperation in Unreliable MANETs.

Science.gov (United States)

Tang, Changbing; Li, Ang; Li, Xiang

2015-10-01

In self-organized mobile ad hoc networks (MANETs), network functions rely on cooperation of self-interested nodes, where a challenge is to enforce their mutual cooperation. In this paper, we study cooperative packet forwarding in a one-hop unreliable channel which results from loss of packets and noisy observation of transmissions. We propose an indirect reciprocity framework based on evolutionary game theory, and enforce cooperation of packet forwarding strategies in both structured and unstructured MANETs. Furthermore, we analyze the evolutionary dynamics of cooperative strategies and derive the threshold of benefit-to-cost ratio to guarantee the convergence of cooperation. The numerical simulations verify that the proposed evolutionary game theoretic solution enforces cooperation when the benefit-to-cost ratio of the altruistic exceeds the critical condition. In addition, the network throughput performance of our proposed strategy in structured MANETs is measured, which is in close agreement with that of the full cooperative strategy.

Eco-evolutionary dynamics in a coevolving host-virus system.

Science.gov (United States)

Frickel, Jens; Sieber, Michael; Becks, Lutz

2016-04-01

Eco-evolutionary dynamics have been shown to be important for understanding population and community stability and their adaptive potential. However, coevolution in the framework of eco-evolutionary theory has not been addressed directly. Combining experiments with an algal host and its viral parasite, and mathematical model analyses we show eco-evolutionary dynamics in antagonistic coevolving populations. The interaction between antagonists initially resulted in arms race dynamics (ARD) with selective sweeps, causing oscillating host-virus population dynamics. However, ARD ended and populations stabilised after the evolution of a general resistant host, whereas a trade-off between host resistance and growth then maintained host diversity over time (trade-off driven dynamics). Most importantly, our study shows that the interaction between ecology and evolution had important consequences for the predictability of the mode and tempo of adaptive change and for the stability and adaptive potential of populations. © 2016 John Wiley & Sons Ltd/CNRS.

Evolutionary Exploration of the Finitely Repeated Prisoners’ Dilemma—The Effect of Out-of-Equilibrium Play

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Kristian Lindgren

2013-01-01

Full Text Available The finitely repeated Prisoners’ Dilemma is a good illustration of the discrepancy between the strategic behaviour suggested by a game-theoretic analysis and the behaviour often observed among human players, where cooperation is maintained through most of the game. A game-theoretic reasoning based on backward induction eliminates strategies step by step until defection from the first round is the only remaining choice, reflecting the Nash equilibrium of the game. We investigate the Nash equilibrium solution for two different sets of strategies in an evolutionary context, using replicator-mutation dynamics. The first set consists of conditional cooperators, up to a certain round, while the second set in addition to these contains two strategy types that react differently on the first round action: The ”Convincer” strategies insist with two rounds of initial cooperation, trying to establish more cooperative play in the game, while the ”Follower” strategies, although being first round defectors, have the capability to respond to an invite in the first round. For both of these strategy sets, iterated elimination of strategies shows that the only Nash equilibria are given by defection from the first round. We show that the evolutionary dynamics of the first set is always characterised by a stable fixed point, corresponding to the Nash equilibrium, if the mutation rate is sufficiently small (but still positive. The second strategy set is numerically investigated, and we find that there are regions of parameter space where fixed points become unstable and the dynamics exhibits cycles of different strategy compositions. The results indicate that, even in the limit of very small mutation rate, the replicator-mutation dynamics does not necessarily bring the system with Convincers and Followers to the fixed point corresponding to the Nash equilibrium of the game. We also perform a detailed analysis of how the evolutionary behaviour depends on

Evolutionary Dynamics and Diversity in Microbial Populations

Science.gov (United States)

Thompson, Joel; Fisher, Daniel

2013-03-01

Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.

Dynamics of spatial traveler's dilemma games

International Nuclear Information System (INIS)

Tanimoto, Jun

2014-01-01

By examining payoff structures, we elucidate the traveler's dilemma (TD) game. It can be said that the TD game as the 2-player and multi-strategy game is a variant of the donor and recipient game, which itself is a subclass of the 2-player and 2-strategy (2 × 2) prisoner's dilemma, in the sense that the Nash equilibrium and fair Pareto optimum appear on mutual defection and mutual cooperation, respectively. Exploring spatial TD games, we observed that the network reciprocity of TD games can be universally scaled with a single dilemma parameter as can be performed in usual 2 × 2 games. Furthermore, we observed a local peak event reflecting a resurging cooperation fraction with increasing dilemma strength after degradation to a low level. We successfully demonstrate that this is caused by the specific dynamics of TD games created by their specific payoff structure. (paper)

Recidivism and Rehabilitation of Criminal Offenders: A Carrot and Stick Evolutionary Game

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Berenji, Bijan; Chou, Tom; D'Orsogna, Maria R.

2014-01-01

Motivated by recent efforts by the criminal justice system to treat and rehabilitate nonviolent offenders rather than focusing solely on their punishment, we introduce an evolutionary game theoretic model to study the effects of “carrot and stick” intervention programs on criminal recidivism. We use stochastic simulations to study the evolution of a population where individuals may commit crimes depending on their past history, surrounding environment and, in the case of recidivists, on any counseling, educational or training programs available to them after being punished for their previous crimes. These sociological factors are embodied by effective parameters that determine the decision making probabilities. Players may decide to permanently reform or continue engaging in criminal activity, eventually reaching a state where they are considered incorrigible. Depending on parameter choices, the outcome of the game is a society with a majority of virtuous, rehabilitated citizens or incorrigibles. Since total resources may be limited, we constrain the combined punishment and rehabilitation costs per crime to be fixed, so that increasing one effort will necessarily decrease the other. We find that the most successful strategy in reducing crime is to optimally allocate resources so that after being punished, criminals experience impactful intervention programs, especially during the first stages of their return to society. Excessively harsh or lenient punishments are less effective. We also develop a system of coupled ordinary differential equations with memory effects to give a qualitative description of our simulated societal dynamics. We discuss our findings and sociological implications. PMID:24454884

Recidivism and rehabilitation of criminal offenders: a carrot and stick evolutionary game.

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Bijan Berenji

Full Text Available Motivated by recent efforts by the criminal justice system to treat and rehabilitate nonviolent offenders rather than focusing solely on their punishment, we introduce an evolutionary game theoretic model to study the effects of "carrot and stick" intervention programs on criminal recidivism. We use stochastic simulations to study the evolution of a population where individuals may commit crimes depending on their past history, surrounding environment and, in the case of recidivists, on any counseling, educational or training programs available to them after being punished for their previous crimes. These sociological factors are embodied by effective parameters that determine the decision making probabilities. Players may decide to permanently reform or continue engaging in criminal activity, eventually reaching a state where they are considered incorrigible. Depending on parameter choices, the outcome of the game is a society with a majority of virtuous, rehabilitated citizens or incorrigibles. Since total resources may be limited, we constrain the combined punishment and rehabilitation costs per crime to be fixed, so that increasing one effort will necessarily decrease the other. We find that the most successful strategy in reducing crime is to optimally allocate resources so that after being punished, criminals experience impactful intervention programs, especially during the first stages of their return to society. Excessively harsh or lenient punishments are less effective. We also develop a system of coupled ordinary differential equations with memory effects to give a qualitative description of our simulated societal dynamics. We discuss our findings and sociological implications.

Symposium of the International Society of Dynamic Games

CERN Document Server

Haurie, Alain; Annals of the International Society of Dynamic Games

1994-01-01

Recent years have witnessed a surge of activity in the field of dynamic both theory and applications. Theoretical as well as practical games, in problems in zero-sum and nonzero-sum games, continuous time differential and discrete time multistage games, and deterministic and stochastic games games are currently being investigated by researchers in diverse disciplines, such as engineering, mathematics, biology, economics, management science, and political science. This surge of interest has led to the formation of the International Society of Dynamic Games (ISDG) in 1990, whose primary goal is to foster the development of advanced research and applications in the field of game theory. One important activity of the Society is to organize biannually an international symposium which aims at bringing together all those who contribute to the development of this active field of applied science. In 1992 the symposium was organized in Grimentz, Switzerland, under the supervision of an international scientific committe...

Modelling the host-pathogen interactions of macrophages and Candida albicans using Game Theory and dynamic optimization.

Science.gov (United States)

Dühring, Sybille; Ewald, Jan; Germerodt, Sebastian; Kaleta, Christoph; Dandekar, Thomas; Schuster, Stefan

2017-07-01

The release of fungal cells following macrophage phagocytosis, called non-lytic expulsion, is reported for several fungal pathogens. On one hand, non-lytic expulsion may benefit the fungus in escaping the microbicidal environment of the phagosome. On the other hand, the macrophage could profit in terms of avoiding its own lysis and being able to undergo proliferation. To analyse the causes of non-lytic expulsion and the relevance of macrophage proliferation in the macrophage- Candida albicans interaction, we employ Evolutionary Game Theory and dynamic optimization in a sequential manner. We establish a game-theoretical model describing the different strategies of the two players after phagocytosis. Depending on the parameter values, we find four different Nash equilibria and determine the influence of the systems state of the host upon the game. As our Nash equilibria are a direct consequence of the model parameterization, we can depict several biological scenarios. A parameter region, where the host response is robust against the fungal infection, is determined. We further apply dynamic optimization to analyse whether macrophage mitosis is relevant in the host-pathogen interaction of macrophages and C. albicans For this, we study the population dynamics of the macrophage- C. albicans interactions and the corresponding optimal controls for the macrophages, indicating the best macrophage strategy of switching from proliferation to attacking fungal cells. © 2017 The Author(s).

Simple Unawareness in Dynamic Psychological Games

DEFF Research Database (Denmark)

Nielsen, Carsten Søren; Sebald, Alexander Christopher

2017-01-01

Building on Battigalli and Dufwenberg (2009)’s framework of dynamic psychological games and the progress in the modeling of dynamic unawareness by Heifetz, Meier, and Schipper (2013a) we model and analyze the impact of asymmetric awareness in the strategic interaction of players motivated...... by reciprocity and guilt. Specifically we characterize extensive-form games with psychological payoffs and simple unawareness, define extensive-form rationalizability and, using this, show that unawareness has a pervasive impact on the strategic interaction of psychologically motivated players. Intuitively...

Bridging developmental systems theory and evolutionary psychology using dynamic optimization.

Science.gov (United States)

Frankenhuis, Willem E; Panchanathan, Karthik; Clark Barrett, H

2013-07-01

Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic optimization integrates developmental systems theorists' focus on dynamics and contingency with the 'design stance' of evolutionary psychology. It provides a theoretical framework as well as a set of tools for exploring the properties of developmental systems that natural selection might favor, given particular evolutionary ecologies. We also discuss limitations of the approach. © 2013 Blackwell Publishing Ltd.

Tractable dynamic global games and applications

Czech Academy of Sciences Publication Activity Database

Mathevet, L.; Steiner, Jakub

2013-01-01

Roč. 148, č. 6 (2013), s. 2583-2619 ISSN 0022-0531 R&D Projects: GA ČR(CZ) GA13-34759S Grant - others:UK(CZ) UNCE 204005/2012 Institutional support: PRVOUK-P23 Keywords : global games * dynamic game * coordination Subject RIV: AH - Economics Impact factor: 0.919, year: 2013

Effects of Inertia on Evolutionary Prisoner's Dilemma Game

International Nuclear Information System (INIS)

Du Wenbo; Cao Xianbin; Liu Runran; Wang Zhen

2012-01-01

Considering the inertia of individuals in real life, we propose a modified Fermi updating rule, where the inertia of players is introduced into evolutionary prisoner's dilemma game (PDG) on square lattices. We mainly focus on how the inertia affects the cooperative behavior of the system. Interestingly, we find that the cooperation level has a nonmonotonic dependence on the inertia: with small inertia, cooperators will soon be invaded by defectors; with large inertia, players are unwilling to change their strategies and the cooperation level remains the same as the initial state; while a moderate inertia can induce the highest cooperation level. Moreover, effects of environmental noise and individual inertia are studied. Our work may be helpful in understanding the emergence and persistence of cooperation in nature and society. (interdisciplinary physics and related areas of science and technology)

The dynamics of alliances. A game theoretical approach

NARCIS (Netherlands)

Ridder, A. de

2007-01-01

In this dissertation, Annelies de Ridder presents a game theoretical approach to strategic alliances. More specifically, the dynamics of and within alliances have been studied. To do so, four new models have been developed in the game theoretical tradition. Both coalition theory and strategic game

Evolutionary Game Analysis of Government Regulation and Enterprise Emission from the Perspective of Environmental Tax

Science.gov (United States)

Mai, Yazong

2017-12-01

In the context of the upcoming implementation of the environmental tax policy, there is a need for a focus on the relationship between government regulation and corporate emissions. To achieve the real effect of environmental tax policy, government need to regulate the illegal emissions of enterprises. Based on the hypothesis of bounded rationality, this paper analyses the strategic set of government regulators and polluting enterprises in the implementation of environmental tax policy. By using the evolutionary game model, the utility function and payoff matrix of the both sides are constructed, and the evolutionary analysis and strategy adjustment of the environmental governance target and the actual profit of the stakeholders are carried out. Thus, the wrong behaviours could be corrected so that the equilibrium of the evolutionary system can be achieved gradually, which could also get the evolutionary stable strategies of the government and the polluting enterprises in the implementation of environmental tax policy.

Dynamic games theory and applications

CERN Document Server

Haurie, Alain

2005-01-01

Dynamic games continue to attract strong interest from researchers interested in modeling competitive and conflict situations to study the behavior of players (decision-makers) and to predict the outcome of such situations in many areas including engineering, economics, management science, military, biology, and political science. This collection of articles by established researchers is an excellent reference covering a wide range of emerging and revisited problems in both cooperative and non-cooperative games.

A uniform Tauberian theorem in dynamic games

Science.gov (United States)

Khlopin, D. V.

2018-01-01

Antagonistic dynamic games including games represented in normal form are considered. The asymptotic behaviour of value in these games is investigated as the game horizon tends to infinity (Cesàro mean) and as the discounting parameter tends to zero (Abel mean). The corresponding Abelian-Tauberian theorem is established: it is demonstrated that in both families the game value uniformly converges to the same limit, provided that at least one of the limits exists. Analogues of one-sided Tauberian theorems are obtained. An example shows that the requirements are essential even for control problems. Bibliography: 31 titles.

An evolutionary game model for behavioral gambit of loyalists: Global awareness and risk-aversion

Science.gov (United States)

Alfinito, E.; Barra, A.; Beccaria, M.; Fachechi, A.; Macorini, G.

2018-02-01

We study the phase diagram of a minority game where three classes of agents are present. Two types of agents play a risk-loving game that we model by the standard Snowdrift Game. The behaviour of the third type of agents is coded by indifference with respect to the game at all: their dynamics is designed to account for risk-aversion as an innovative behavioral gambit. From this point of view, the choice of this solitary strategy is enhanced when innovation starts, while is depressed when it becomes the majority option. This implies that the payoff matrix of the game becomes dependent on the global awareness of the agents measured by the relevance of the population of the indifferent players. The resulting dynamics is nontrivial with different kinds of phase transition depending on a few model parameters. The phase diagram is studied on regular as well as complex networks.

Evolutionary dynamics of complex communications networks

CERN Document Server

Karyotis, Vasileios; Papavassiliou, Symeon

2013-01-01

Until recently, most network design techniques employed a bottom-up approach with lower protocol layer mechanisms affecting the development of higher ones. This approach, however, has not yielded fascinating results in the case of wireless distributed networks. Addressing the emerging aspects of modern network analysis and design, Evolutionary Dynamics of Complex Communications Networks introduces and develops a top-bottom approach where elements of the higher layer can be exploited in modifying the lowest physical topology-closing the network design loop in an evolutionary fashion similar to

Topological chaos of the spatial prisoner's dilemma game on regular networks.

Science.gov (United States)

Jin, Weifeng; Chen, Fangyue

2016-02-21

The spatial version of evolutionary prisoner's dilemma on infinitely large regular lattice with purely deterministic strategies and no memories among players is investigated in this paper. Based on the statistical inferences, it is pertinent to confirm that the frequency of cooperation for characterizing its macroscopic behaviors is very sensitive to the initial conditions, which is the most practically significant property of chaos. Its intrinsic complexity is then justified on firm ground from the theory of symbolic dynamics; that is, this game is topologically mixing and possesses positive topological entropy on its subsystems. It is demonstrated therefore that its frequency of cooperation could not be adopted by simply averaging over several steps after the game reaches the equilibrium state. Furthermore, the chaotically changing spatial patterns via empirical observations can be defined and justified in view of symbolic dynamics. It is worth mentioning that the procedure proposed in this work is also applicable to other deterministic spatial evolutionary games therein. Copyright © 2015 Elsevier Ltd. All rights reserved.

Player guild dynamics and evolution in massively multiplayer online games.

Science.gov (United States)

Chen, Chien-Hsun; Sun, Chuen-Tsai; Hsieh, Jilung

2008-06-01

In the latest versions of massively multiplayer online games (MMOGs), developers have purposefully made guilds part of game environments. Guilds represent a powerful method for giving players a sense of online community, but there is little quantitative data on guild dynamics. To address this topic, we took advantage of a feature found in one of today's most popular MMOGs (World of Warcraft) to collect in-game data: user interfaces that players can modify and refine. In addition to collecting data on in-game player activities, we used this feature to observe and investigate how players join and leave guilds. Data were analyzed for the purpose of identifying factors that propel game-world guild dynamics and evolution. After collecting data for 641,805 avatars on 62 Taiwanese World of Warcraft game servers between February 10 and April 10, 2006, we created five guild type categories (small, large, elite, newbie, and unstable) that have different meanings in terms of in-game group dynamics. By viewing players as the most important resource affecting guild life cycles, it is possible to analyze game worlds as ecosystems consisting of evolving guilds and to study how guild life cycles reflect game world characteristics.

Spatial evolutionary games with weak selection.

Science.gov (United States)

Nanda, Mridu; Durrett, Richard

2017-06-06

Recently, a rigorous mathematical theory has been developed for spatial games with weak selection, i.e., when the payoff differences between strategies are small. The key to the analysis is that when space and time are suitably rescaled, the spatial model converges to the solution of a partial differential equation (PDE). This approach can be used to analyze all [Formula: see text] games, but there are a number of [Formula: see text] games for which the behavior of the limiting PDE is not known. In this paper, we give rules for determining the behavior of a large class of [Formula: see text] games and check their validity using simulation. In words, the effect of space is equivalent to making changes in the payoff matrix, and once this is done, the behavior of the spatial game can be predicted from the behavior of the replicator equation for the modified game. We say predicted here because in some cases the behavior of the spatial game is different from that of the replicator equation for the modified game. For example, if a rock-paper-scissors game has a replicator equation that spirals out to the boundary, space stabilizes the system and produces an equilibrium.

Inactivation of tumor suppressor genes and cancer therapy: An evolutionary game theory approach.

Science.gov (United States)

Khadem, Heydar; Kebriaei, Hamed; Veisi, Zahra

2017-06-01

Inactivation of alleles in tumor suppressor genes (TSG) is one of the important issues resulting in evolution of cancerous cells. In this paper, the evolution of healthy, one and two missed allele cells is modeled using the concept of evolutionary game theory and replicator dynamics. The proposed model also takes into account the interaction rates of the cells as designing parameters of the system. Different combinations of the equilibrium points of the parameterized nonlinear system is studied and categorized into some cases. In each case, the interaction rates' values are suggested in a way that the equilibrium points of the replicator dynamics are located on an appropriate region of the state space. Based on the suggested interaction rates, it is proved that the system doesn't have any undesirable interior equilibrium point as well. Therefore, the system will converge to the desirable region, where there is a scanty level of cancerous cells. In addition, the proposed conditions for interaction rates guarantee that, when a trajectory of the system reaches the boundaries, then it will stay there forever which is a desirable property since the equilibrium points have been already located on the boundaries, appropriately. The simulation results show the effectiveness of the suggestions in the elimination of the cancerous cells in different scenarios. Copyright © 2017 Elsevier Inc. All rights reserved.

The evolutionary rate dynamically tracks changes in HIV-1 epidemics

Energy Technology Data Exchange (ETDEWEB)

Maljkovic-berry, Irina [Los Alamos National Laboratory; Athreya, Gayathri [Los Alamos National Laboratory; Daniels, Marcus [Los Alamos National Laboratory; Bruno, William [Los Alamos National Laboratory; Korber, Bette [Los Alamos National Laboratory; Kuiken, Carla [Los Alamos National Laboratory; Ribeiro, Ruy M [Los Alamos National Laboratory

2009-01-01

Large-sequence datasets provide an opportunity to investigate the dynamics of pathogen epidemics. Thus, a fast method to estimate the evolutionary rate from large and numerous phylogenetic trees becomes necessary. Based on minimizing tip height variances, we optimize the root in a given phylogenetic tree to estimate the most homogenous evolutionary rate between samples from at least two different time points. Simulations showed that the method had no bias in the estimation of evolutionary rates and that it was robust to tree rooting and topological errors. We show that the evolutionary rates of HIV-1 subtype B and C epidemics have changed over time, with the rate of evolution inversely correlated to the rate of virus spread. For subtype B, the evolutionary rate slowed down and tracked the start of the HAART era in 1996. Subtype C in Ethiopia showed an increase in the evolutionary rate when the prevalence increase markedly slowed down in 1995. Thus, we show that the evolutionary rate of HIV-1 on the population level dynamically tracks epidemic events.

Evolutionary dynamics of mammalian karyotypes

Directory of Open Access Journals (Sweden)

Carlo Alberto Redi

2012-12-01

Full Text Available This special volume of Cytogenetic and Genome Research (edited by Roscoe Stanyon, University of Florence and Alexander Graphodatsky, Siberian division of the Russian Academy of Sciences is dedicated to the fascinating long search of the forces behind the evolutionary dynamics of mammalian karyotypes, revealed after the hypotonic miracle of the 1950s....

Spatial Evolutionary Games of Interaction among Generic Cancer Cells

DEFF Research Database (Denmark)

Bach, Lars Arve; Sumpter, David J.T.; Alsner, Jan

2003-01-01

Evolutionary game models of cellular interactions have shown that heterogeneity in the cellular genotypic composition is maintained through evolution to stable coexistence of growth-promoting and non-promoting cell types. We generalise these mean-field models and relax the assumption of perfect...... mixing of cells by instead implementing an individual-based model that includes the stochastic and spatial effects likely to occur in tumours. The scope for coexistence of genotypic strategies changed with the inclusion of explicit space and stochasticity. The spatial models show some interesting...... deviations from their mean-field counterparts, for example the possibility of altruistic (paracrine) cell strategies to thrive. Such effects can however, be highly sensitive to model implementation and the more realistic models with semi-synchronous and stochastic updating do not show evolution of altruism...

Evolution in Mind: Evolutionary Dynamics, Cognitive Processes, and Bayesian Inference.

Science.gov (United States)

Suchow, Jordan W; Bourgin, David D; Griffiths, Thomas L

2017-07-01

Evolutionary theory describes the dynamics of population change in settings affected by reproduction, selection, mutation, and drift. In the context of human cognition, evolutionary theory is most often invoked to explain the origins of capacities such as language, metacognition, and spatial reasoning, framing them as functional adaptations to an ancestral environment. However, evolutionary theory is useful for understanding the mind in a second way: as a mathematical framework for describing evolving populations of thoughts, ideas, and memories within a single mind. In fact, deep correspondences exist between the mathematics of evolution and of learning, with perhaps the deepest being an equivalence between certain evolutionary dynamics and Bayesian inference. This equivalence permits reinterpretation of evolutionary processes as algorithms for Bayesian inference and has relevance for understanding diverse cognitive capacities, including memory and creativity. Copyright © 2017 Elsevier Ltd. All rights reserved.

On dynamical multi-team Cournot game in exploitation of a renewable resource

International Nuclear Information System (INIS)

Asker, S.S.

2007-01-01

A dynamical multi-team Cournot game is formulated for a renewable resource (harvest fish and sell it in a market). Puu's imperfect information to dynamic standard game is generalized to multi-team Cournot game. The asymptotic stability of the equilibrium solution of the resulting game is studied

Gold rush - A swarm dynamics in games

Science.gov (United States)

Zelinka, Ivan; Bukacek, Michal

2017-07-01

This paper is focused on swarm intelligence techniques and its practical use in computer games. The aim is to show how a swarm dynamics can be generated by multiplayer game, then recorded, analyzed and eventually controlled. In this paper we also discuss possibility to use swarm intelligence instead of game players. Based on our previous experiments two games, using swarm algorithms are mentioned briefly here. The first one is strategy game StarCraft: Brood War, and TicTacToe in which SOMA algorithm has also take a role of player against human player. Open research reported here has shown potential benefit of swarm computation in the field of strategy games and players strategy based on swarm behavior record and analysis. We propose new game called Gold Rush as an experimental environment for human or artificial swarm behavior and consequent analysis.

Offspring mortality was a determinant factor in the evolution of paternal investment in humans: An evolutionary game approach.

Science.gov (United States)

López Alonso, Diego; Ortiz-Rodríguez, Isabel M

2017-04-21

Some researchers support the belief that man evolved philandering behavior because of the greater reproductive success of promiscuous males. According to this idea, deserting behavior from the man should be expected along with null paternal involvement in offspring care. Paradoxically however, the average offspring investment in the human male is far higher than that of any other male mammal, including other primates. In our work, we have addressed this conundrum by employing evolutionary game theory, using objective payoffs instead of, as are commonly used, arbitrary payoffs. Payoffs were computed as reproductive successes by a model based on trivial probabilities, implemented within the Barreto's Population Dynamics Toolbox (2014). The evolution of the parent conflict was simulated by a game with two players (the woman and the man). First, a simple game was assayed with two strategies, 'desert-unfaithful' and 'care-faithful'. Then, the game was played with a third mixed strategy, 'care-unfaithful'. The two-strategy game results were mainly determined by the offspring survival rate (s) and the non-paternity rate (z), with remaining factors playing a secondary role. Starting from two empirical estimates for both rates (s = 0.617 and z = 0.033) and decreasing the offspring mortality from near 0.4 to 0.1, the results were consistent with a win for the 'care-faithful' strategy. The 'desert-unfaithful' strategy only won at unrealistically high non-paternity rates (z>0.2). When three-strategy games were played, the mixed strategy of 'care-unfaithful' man could win the game in some less frequent cases. Regardless of the number of game strategies, 'care' fathers always won. These results strongly suggest that offspring mortality was the key factor in the evolution of paternal investment within the Homo branch. The 'care-faithful' strategy would have been the main strategy in human evolution but 'care-unfaithful' men did evolve at a lesser frequency. It can therefore be

A survey of static and dynamic potential games

Institute of Scientific and Technical Information of China (English)

GONZLEZ-SNCHEZ David; HERNNDEZ-LERMA Onsimo

2016-01-01

Potential games are noncooperative games for which there exist auxiliary functions, called potentials,such that the maximizers of the potential are also Nash equilibria of the corresponding game. Some properties of Nash equilibria, such as existence or stability, can be derived from the potential, whenever it exists. We survey different classes of potential games in the static and dynamic cases, with a finite number of players, as well as in population games where a continuum of players is allowed. Likewise, theoretical concepts and applications are discussed by means of illustrative examples.

Dynamic probability of reinforcement for cooperation: Random game termination in the centipede game.

Science.gov (United States)

Krockow, Eva M; Colman, Andrew M; Pulford, Briony D

2018-03-01

Experimental games have previously been used to study principles of human interaction. Many such games are characterized by iterated or repeated designs that model dynamic relationships, including reciprocal cooperation. To enable the study of infinite game repetitions and to avoid endgame effects of lower cooperation toward the final game round, investigators have introduced random termination rules. This study extends previous research that has focused narrowly on repeated Prisoner's Dilemma games by conducting a controlled experiment of two-player, random termination Centipede games involving probabilistic reinforcement and characterized by the longest decision sequences reported in the empirical literature to date (24 decision nodes). Specifically, we assessed mean exit points and cooperation rates, and compared the effects of four different termination rules: no random game termination, random game termination with constant termination probability, random game termination with increasing termination probability, and random game termination with decreasing termination probability. We found that although mean exit points were lower for games with shorter expected game lengths, the subjects' cooperativeness was significantly reduced only in the most extreme condition with decreasing computer termination probability and an expected game length of two decision nodes. © 2018 Society for the Experimental Analysis of Behavior.

Scaling behavior can be tricky: Comment on "Universal scaling for the dilemma strength in evolutionary games" by Z. Wang et al.

Science.gov (United States)

Hui, Pak Ming; Xu, Chen

2015-09-01

Evolutionary game theory is a powerful tool for studying the emergence of cooperation among competing individuals [1]. Popularly studied games include the prisoner's dilemma [2], snowdrift game [3] and stag hunt game [4]. They have been extensively studied for the extent of cooperative behavior under different dilemma strengths. Generally, the games can be defined by a 2 × 2 matrix and thus four payoff elements, T, R, P, and S, for the possible payoffs to players when they use pure strategies against each other. Detailed definitions of the four payoffs are given in the review by Wang et al. [5]. For simplicity, it is often the case that fewer parameters are invoked, e.g. a single parameter [3] and more generally two parameters [6]. Generally speaking, reducing the number of parameters has the effect of restricting the system to a certain subspace of the unreduced case. In addition, the spatial structures, such as a well-mixed population or a population forming a complex network, that govern the competing relationship and environment of the agents, and the evolutionary rules, that govern how agents update their strategies, are vital in determining how cooperation evolves, as well documented in the references of [5].

Dynamics of the Minority Game for Patients

OpenAIRE

Kim, Kyungsik; Yoon, Seong-Min; Yum, Myung-Kul

2003-01-01

We analyze the minority game for patients, and the results known from the minority game are applied to the patient problem consulted at the department of pediatric cardiology. We find numerically the standard deviation and the global efficiency, similar to the El Farol bar problem. After the score equation and the scaled utility are introduced, the dynamical behavior of our model is discussed for particular strategies. Our result presented will be compared with the well-known minority games.

Robustness of cooperation in the evolutionary prisoner's dilemma on complex networks

International Nuclear Information System (INIS)

Poncela, J; Gomez-Gardenes, J; FlorIa, L M; Moreno, Y

2007-01-01

Recent studies on the evolutionary dynamics of the prisoner's dilemma game in scale-free networks have demonstrated that the heterogeneity of the network interconnections enhances the evolutionary success of cooperation. In this paper we address the issue of how the characterization of the asymptotic states of the evolutionary dynamics depends on the initial concentration of cooperators. We find that the measure and the connectedness properties of the set of nodes where cooperation reaches fixation is largely independent of initial conditions, in contrast with the behaviour of both the set of nodes where defection is fixed, and the fluctuating nodes. We also check for the robustness of these results when varying the degree heterogeneity along a one-parametric family of networks interpolating between the class of Erdos-Renyi graphs and the Barabasi-Albert networks

On the Evolutionary Stability of Bargaining Inefficiency

DEFF Research Database (Denmark)

Poulsen, Anders

This paper investigates whether 'tough' bargaining behavior, which gives rise to inefficiency, can be evolutionary stable. We show that in a two-stage Nash Demand Game tough behavior survives. Indeed, almost all the surplus may be wasted. We also study the Ultimatum Game. Here evolutionary select...

Critical Behavior of Spatial Evolutionary Game with Altruistic to Spiteful Preferences on Two-Dimensional Lattices

International Nuclear Information System (INIS)

Yang Bo; Li Xiao-Teng; Chen Xiao-Song; Chen Wei; Liu Jian

2016-01-01

Self-questioning mechanism which is similar to single spin-flip of Ising model in statistical physics is introduced into spatial evolutionary game model. We propose a game model with altruistic to spiteful preferences via weighted sums of own and opponent's payoffs. This game model can be transformed into Ising model with an external field. Both interaction between spins and the external field are determined by the elements of payoff matrix and the preference parameter. In the case of perfect rationality at zero social temperature, this game model has three different phases which are entirely cooperative phase, entirely non-cooperative phase and mixed phase. In the investigations of the game model with Monte Carlo simulation, two paths of payoff and preference parameters are taken. In one path, the system undergoes a discontinuous transition from cooperative phase to non-cooperative phase with the change of preference parameter. In another path, two continuous transitions appear one after another when system changes from cooperative phase to non-cooperative phase with the prefenrence parameter. The critical exponents v, β, and γ of two continuous phase transitions are estimated by the finite-size scaling analysis. Both continuous phase transitions have the same critical exponents and they belong to the same universality class as the two-dimensional Ising model. (paper)

Evolutionary dynamics on infinite strategy spaces

OpenAIRE

Oechssler, Jörg; Riedel, Frank

1998-01-01

The study of evolutionary dynamics was so far mainly restricted to finite strategy spaces. In this paper we show that this unsatisfying restriction is unnecessary. We specify a simple condition under which the continuous time replicator dynamics are well defined for the case of infinite strategy spaces. Furthermore, we provide new conditions for the stability of rest points and show that even strict equilibria may be unstable. Finally, we apply this general theory to a number of applications ...

Evolutionary prisoner's dilemma games on the network with punishment and opportunistic partner switching

Science.gov (United States)

Takesue, H.

2018-02-01

Punishment and partner switching are two well-studied mechanisms that support the evolution of cooperation. Observation of human behaviour suggests that the extent to which punishment is adopted depends on the usage of alternative mechanisms, including partner switching. In this study, we investigate the combined effect of punishment and partner switching in evolutionary prisoner's dilemma games conducted on a network. In the model, agents are located on the network and participate in the prisoner's dilemma games with punishment. In addition, they can opportunistically switch interaction partners to improve their payoff. Our Monte Carlo simulation showed that a large frequency of punishers is required to suppress defectors when the frequency of partner switching is low. In contrast, cooperation is the most abundant strategy when the frequency of partner switching is high regardless of the strength of punishment. Interestingly, cooperators become abundant not because they avoid the cost of inflicting punishment and earn a larger average payoff per game but rather because they have more numerous opportunities to be referred to as a role agent by defectors. Our results imply that the fluidity of social relationships has a profound effect on the adopted strategy in maintaining cooperation.

Topology control with IPD network creation games

International Nuclear Information System (INIS)

Scholz, Jan C; Greiner, Martin O W

2007-01-01

Network creation games couple a two-players game with the evolution of network structure. A vertex player may increase its own payoff with a change of strategy or with a modification of its edge-defined neighbourhood. By referring to the iterated prisoners dilemma (IPD) game we show that this evolutionary dynamics converges to network-Nash equilibria, where no vertex is able to improve its payoff. The resulting network structure exhibits a strong dependence on the parameter of the payoff matrix. Degree distributions and cluster coefficients are also strongly affected by the specific interactions chosen for the neighbourhood exploration. This allows network creation games to be seen as a promising artificial-social-systems approach for a distributive topology control of complex networked systems

Environmental fluctuations restrict eco-evolutionary dynamics in predator-prey system.

Science.gov (United States)

Hiltunen, Teppo; Ayan, Gökçe B; Becks, Lutz

2015-06-07

Environmental fluctuations, species interactions and rapid evolution are all predicted to affect community structure and their temporal dynamics. Although the effects of the abiotic environment and prey evolution on ecological community dynamics have been studied separately, these factors can also have interactive effects. Here we used bacteria-ciliate microcosm experiments to test for eco-evolutionary dynamics in fluctuating environments. Specifically, we followed population dynamics and a prey defence trait over time when populations were exposed to regular changes of bottom-up or top-down stressors, or combinations of these. We found that the rate of evolution of a defence trait was significantly lower in fluctuating compared with stable environments, and that the defence trait evolved to lower levels when two environmental stressors changed recurrently. The latter suggests that top-down and bottom-up changes can have additive effects constraining evolutionary response within populations. The differences in evolutionary trajectories are explained by fluctuations in population sizes of the prey and the predator, which continuously alter the supply of mutations in the prey and strength of selection through predation. Thus, it may be necessary to adopt an eco-evolutionary perspective on studies concerning the evolution of traits mediating species interactions. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Randomness and arbitrary coordination in the reactive ultimatum game

Science.gov (United States)

da Silva, Roberto; Valverde, Pablo; Lamb, Luis C.

2016-07-01

Darwin's theory of evolution - as introduced in game theory by Maynard Smith - is not the only important evolutionary aspect in an evolutionary dynamics, since complex interdependencies, competition, and growth should be modeled by, for example, reactive aspects. In the ultimatum game, the reciprocity and the fifty-fifty partition seems to be a deviation from rational behavior of the players under the light of Nash equilibrium. Such equilibrium emerges, for example, from the punishment of the responder who generally tends to refuse unfair proposals. In the iterated version of the game, the proposers are able to improve their proposals by adding a value thus making fairer proposals. Such evolutionary aspects are not properly Darwinian-motivated, but they are endowed with a fundamental aspect: they reflect their actions according to value of the offers. Recently, a reactive version of the ultimatum game where acceptance occurs with fixed probability was proposed. In this paper, we aim at exploring this reactive version of the ultimatum game where the acceptance by players depends on the offer. In order to do so, we analyze two situations: (i) mean field and (ii) we consider players inserted within the networks with arbitrary coordination. We then show that the reactive aspect, here studied, thus far not analyzed in the evolutionary game theory literature can unveil an essential feature for the convergence to fifty-fifty split. Moreover we also analyze populations under four different polices ranging from a highly conservative to a moderate one, with respect to the decision in changing the proposal based on acceptances. We show that the idea of gaining less more times added to the reciprocity of the players is highly relevant to the concept of ;healthy; societies population bargaining.

Evolutionary stability of mixed strategies on graphs

International Nuclear Information System (INIS)

Li, Yan; Liu, Xinsheng; Claussen, Jens Christian

2016-01-01

Up to the present time, the study of evolutionary dynamics mostly focused on pure strategy games in finite discrete strategy space, either in well-mixed or structured populations. In this paper, we study mixed strategy games in continuous strategy space on graphs of degree k . Each player is arranged on a vertex of the graph. The edges denote the interaction between two individuals. In the limit of weak selection, we first derive the payoff functions of two mixed strategies under three different updating rules, named birth–death, death–birth and imitation. Then we obtain the conditions for a strategy being a continuously stable strategy (CSS), and we also confirm that the equilibrium distribution corresponding to the CSS is neighborhood attracting and strongly uninvadable. Finally, we apply our theory to the prisoner’s dilemma and the snowdrift game to obtain possible CSS. Simulations are performed for the two special games and the results are well consistent with the conclusions we made. (paper)

Population and evolutionary dynamics in spatially structured seasonally varying environments.

Science.gov (United States)

Reid, Jane M; Travis, Justin M J; Daunt, Francis; Burthe, Sarah J; Wanless, Sarah; Dytham, Calvin

2018-03-25

Increasingly imperative objectives in ecology are to understand and forecast population dynamic and evolutionary responses to seasonal environmental variation and change. Such population and evolutionary dynamics result from immediate and lagged responses of all key life-history traits, and resulting demographic rates that affect population growth rate, to seasonal environmental conditions and population density. However, existing population dynamic and eco-evolutionary theory and models have not yet fully encompassed within-individual and among-individual variation, covariation, structure and heterogeneity, and ongoing evolution, in a critical life-history trait that allows individuals to respond to seasonal environmental conditions: seasonal migration. Meanwhile, empirical studies aided by new animal-tracking technologies are increasingly demonstrating substantial within-population variation in the occurrence and form of migration versus year-round residence, generating diverse forms of 'partial migration' spanning diverse species, habitats and spatial scales. Such partially migratory systems form a continuum between the extreme scenarios of full migration and full year-round residence, and are commonplace in nature. Here, we first review basic scenarios of partial migration and associated models designed to identify conditions that facilitate the maintenance of migratory polymorphism. We highlight that such models have been fundamental to the development of partial migration theory, but are spatially and demographically simplistic compared to the rich bodies of population dynamic theory and models that consider spatially structured populations with dispersal but no migration, or consider populations experiencing strong seasonality and full obligate migration. Second, to provide an overarching conceptual framework for spatio-temporal population dynamics, we define a 'partially migratory meta-population' system as a spatially structured set of locations that can

Despotism, democracy, and the evolutionary dynamics of leadership and followership.

Science.gov (United States)

Van Vugt, Mark

2009-01-01

Responds to comments made by George B. Graen and Stephen J. Guastello on the current author's article Leadership, followership, and evolution: Some lessons from the past by Van Vugt, Hogan, and Kaiser. In the original article my co-authors and I proposed a new way of thinking about leadership, informed by evolutionary (neo-Darwinian) theory. In the first commentary, Graen noted that we ignored a number of recently developed psychological theories of leadership that take into account the leader-follower relationship, most notably LMX theory. LMX theory asserts that leadership effectiveness and team performance are affected by the quality of working relationships between superior and subordinates. Because the original article primarily dealt with questions about the origins of leadership--the phylogenetic and evolutionary causes--we had to be concise in our review of proximate psychological theories of leadership. In the second commentary, Guastello concurred with the importance of an evolutionary game analysis for studying leadership but disagreed with certain details of our analysis. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Critical Behavior of Spatial Evolutionary Game with Altruistic to Spiteful Preferences on Two-Dimensional Lattices

Science.gov (United States)

Yang, Bo; Li, Xiao-Teng; Chen, Wei; Liu, Jian; Chen, Xiao-Song

2016-10-01

Self-questioning mechanism which is similar to single spin-flip of Ising model in statistical physics is introduced into spatial evolutionary game model. We propose a game model with altruistic to spiteful preferences via weighted sums of own and opponent's payoffs. This game model can be transformed into Ising model with an external field. Both interaction between spins and the external field are determined by the elements of payoff matrix and the preference parameter. In the case of perfect rationality at zero social temperature, this game model has three different phases which are entirely cooperative phase, entirely non-cooperative phase and mixed phase. In the investigations of the game model with Monte Carlo simulation, two paths of payoff and preference parameters are taken. In one path, the system undergoes a discontinuous transition from cooperative phase to non-cooperative phase with the change of preference parameter. In another path, two continuous transitions appear one after another when system changes from cooperative phase to non-cooperative phase with the prefenrence parameter. The critical exponents v, β, and γ of two continuous phase transitions are estimated by the finite-size scaling analysis. Both continuous phase transitions have the same critical exponents and they belong to the same universality class as the two-dimensional Ising model. Supported by the National Natural Science Foundation of China under Grant Nos. 11121403 and 11504384

On the Evolutionary Stability of 'Tough' Bargaining Behavior

DEFF Research Database (Denmark)

Poulsen, Anders

2003-01-01

This paper investigates whether 'tough' bargaining behavior, which gives rise to inefficiency, can be evolutionary stable. We show that in a two-stage Nash Demand Game such behavior survives. We also study the Ultimatum Game. Here evolutionary selection wipes out all tough behavior, as long as th...

The influence of tie strength on evolutionary games on networks: An empirical investigation

Science.gov (United States)

Buesser, Pierre; Peña, Jorge; Pestelacci, Enea; Tomassini, Marco

2011-11-01

Extending previous work on unweighted networks, we present here a systematic numerical investigation of standard evolutionary games on weighted networks. In the absence of any reliable model for generating weighted social networks, we attribute weights to links in a few ways supported by empirical data ranging from totally uncorrelated to weighted bipartite networks. The results of the extensive simulation work on standard complex network models show that, except in a case that does not seem to be common in social networks, taking the tie strength into account does not change in a radical manner the long-run steady-state behavior of the studied games. Besides model networks, we also included a real-life case drawn from a coauthorship network. In this case also, taking the weights into account only changes the results slightly with respect to the raw unweighted graph, although to draw more reliable conclusions on real social networks many more cases should be studied as these weighted networks become available.

Evolutionary dynamics of fluctuating populations with strong mutualism

Science.gov (United States)

Chotibut, Thiparat; Nelson, David

2013-03-01

Evolutionary game theory with finite interacting populations is receiving increased attention, including subtle phenomena associated with number fluctuations, i.e., ``genetic drift.'' Models of cooperation and competition often utilize a simplified Moran model, with a strictly fixed total population size. We explore a more general evolutionary model with independent fluctuations in the numbers of two distinct species, in a regime characterized by ``strong mutualism.'' The model has two absorbing states, each corresponding to fixation of one of the two species, and allows exploration of the interplay between growth, competition, and mutualism. When mutualism is favored, number fluctuations eventually drive the system away from a stable fixed point, characterized by cooperation, to one of the absorbing states. Well-mixed populations will thus be taken over by a single species in a finite time, despite the bias towards cooperation. We calculate both the fixation probability and the mean fixation time as a function of the initial conditions and carrying capacities in the strong mutualism regime, using the method of matched asymptotic expansions. Our results are compared to computer simulations.

Dynamic Difficulty Adaptation for Heterogeneously Skilled Player Groups in Multiplayer Collaborative Games

OpenAIRE

Greciano, Miguel Cristian

2016-01-01

This work focuses on the combination of two key concepts: Dynamic Difficulty Adjustment/Adaptation (video games adapting their difficulty according to the in-game performance of players, making themselves easier if the player performs poorly or more difficult if the player performs well) and Collaborative Multiplayer Games (video games where two or more human players work together to achieve a common goal). It considers and analyzes the challenges, potential and possibilities of Dynamic Diffi...

A dynamic game on Green Supply Chain Management

OpenAIRE

Mehrnoosh Khademi; Massimiliano Ferrara; Bruno Pansera; Mehdi Salimi

2015-01-01

In this paper, we establish a dynamic game to allocate CSR (Corporate Social Responsibility) to the members of a supply chain. We propose a model of three-tier supply chain in decentralized state that is including supplier, manufacturer and retailer. For analyzing supply chain performance in decentralized state and the relationships between the members of supply chain, we use Stackelberg game and we consider in this paper a hierarchical equilibrium solution for a two-level game. Specially, we...

Evolutionary game theory meets social science: is there a unifying rule for human cooperation?

Science.gov (United States)

Rosas, Alejandro

2010-05-21

Evolutionary game theory has shown that human cooperation thrives in different types of social interactions with a PD structure. Models treat the cooperative strategies within the different frameworks as discrete entities and sometimes even as contenders. Whereas strong reciprocity was acclaimed as superior to classic reciprocity for its ability to defeat defectors in public goods games, recent experiments and simulations show that costly punishment fails to promote cooperation in the IR and DR games, where classic reciprocity succeeds. My aim is to show that cooperative strategies across frameworks are capable of a unified treatment, for they are governed by a common underlying rule or norm. An analysis of the reputation and action rules that govern some representative cooperative strategies both in models and in economic experiments confirms that the different frameworks share a conditional action rule and several reputation rules. The common conditional rule contains an option between costly punishment and withholding benefits that provides alternative enforcement methods against defectors. Depending on the framework, individuals can switch to the appropriate strategy and method of enforcement. The stability of human cooperation looks more promising if one mechanism controls successful strategies across frameworks. Published by Elsevier Ltd.

Evolutionary game theory: molecules as players.

Science.gov (United States)

Bohl, Katrin; Hummert, Sabine; Werner, Sarah; Basanta, David; Deutsch, Andreas; Schuster, Stefan; Theissen, Günter; Schroeter, Anja

2014-12-01

In this and an accompanying paper we review the use of game theoretical concepts in cell biology and molecular biology. This review focuses on the subcellular level by considering viruses, genes, and molecules as players. We discuss in which way catalytic RNA can be treated by game theory. Moreover, genes can compete for success in replication and can have different strategies in interactions with other genetic elements. Also transposable elements, or "jumping genes", can act as players because they usually bear different traits or strategies. Viruses compete in the case of co-infecting a host cell. Proteins interact in a game theoretical sense when forming heterodimers. Finally, we describe how the Shapley value can be applied to enzymes in metabolic pathways. We show that game theory can be successfully applied to describe and analyse scenarios at the molecular level resulting in counterintuitive conclusions.

Going Green : Framing Effects in a Dynamic Coordination Game

NARCIS (Netherlands)

Gerlagh, Reyer; van der Heijden, Eline

2015-01-01

We experimentally study decision-making in a novel dynamic coordination game. The game captures features of a transition between externality networks. Groups consisting of three subjects start in a stable benchmark equilibrium with network externality. Over seven rounds, they can transit to an

Dynamics of three-agent games

International Nuclear Information System (INIS)

Mungan, Muhittin; Rador, Tonguc

2008-01-01

We study the dynamics and resulting score distribution of three-agent games where after each competition a single agent wins and scores a point. A single competition is described by a triplet of numbers p, t and q denoting the probabilities that the team with the highest, middle or lowest accumulated score wins. The three-agent game can be regarded as a social model where a player can be favored or disfavored for advancement, based on his/her accumulated score. We study the full family of solutions in the regime, where the number of agents and competitions is large, which can be regarded as a hydrodynamic limit. Depending on the parameter values (p, q, t), we find six qualitatively different asymptotic score distributions and we provide a qualitative explanation of these results. We also compare our analytical results against numerical simulations of the microscopic model and find these to be in excellent agreement. It is possible to decide the outcome of a three-agent game through a mini-tournament of two-agent competitions among the participating players and it turns out that the resulting possible score distributions are a subset of those obtained for the general three-agent games. We discuss how one can add a steady and democratic decline rate to the model and present a simple geometric construction that allows one to obtain the score evolution equations for n-agent games

Dynamics of three-agent games

Science.gov (United States)

Mungan, Muhittin; Rador, Tonguç

2008-02-01

We study the dynamics and resulting score distribution of three-agent games where after each competition a single agent wins and scores a point. A single competition is described by a triplet of numbers p, t and q denoting the probabilities that the team with the highest, middle or lowest accumulated score wins. The three-agent game can be regarded as a social model where a player can be favored or disfavored for advancement, based on his/her accumulated score. We study the full family of solutions in the regime, where the number of agents and competitions is large, which can be regarded as a hydrodynamic limit. Depending on the parameter values (p, q, t), we find six qualitatively different asymptotic score distributions and we provide a qualitative explanation of these results. We also compare our analytical results against numerical simulations of the microscopic model and find these to be in excellent agreement. It is possible to decide the outcome of a three-agent game through a mini-tournament of two-agent competitions among the participating players and it turns out that the resulting possible score distributions are a subset of those obtained for the general three-agent games. We discuss how one can add a steady and democratic decline rate to the model and present a simple geometric construction that allows one to obtain the score evolution equations for n-agent games.

Evolutionary fate of memory-one strategies in repeated prisoner's dilemma game in structured populations

Science.gov (United States)

Liu, Xu-Sheng; Wu, Zhi-Xi; Chen, Michael Z. Q.; Guan, Jian-Yue

2017-07-01

We study evolutionary spatial prisoner's dilemma game involving a one-step memory mechanism of the individuals whenever making strategy updating. In particular, during the process of strategy updating, each individual keeps in mind all the outcome of the action pairs adopted by himself and each of his neighbors in the last interaction, and according to which the individuals decide what actions they will take in the next round. Computer simulation results imply that win-stay-lose-shift like strategy win out of the memory-one strategy set in the stationary state. This result is robust in a large range of the payoff parameter, and does not depend on the initial state of the system. Furthermore, theoretical analysis with mean field and quasi-static approximation predict the same result. Thus, our studies suggest that win-stay-lose-shift like strategy is a stable dominant strategy in repeated prisoner's dilemma game in homogeneous structured populations.

Dynamics of the minority game for patients

Science.gov (United States)

Kim, Kyungsik; Yoon, Seong-Min; Kul Yum, Myung

2004-12-01

We analyze the minority game for patients, and the results known from the minority game are applied to the patient problem consulted at the department of pediatric cardiology. We find numerically the standard deviation and the global efficiency, which is discussed similar to the El Farol bar problem. After the score equation and the scaled utility are introduced, the dynamical behavior of our model is discussed for particular strategies. Our results presented will be compared with recent numerical calculations.

Extinction rates in tumour public goods games.

Science.gov (United States)

Gerlee, Philip; Altrock, Philipp M

2017-09-01

Cancer evolution and progression are shaped by cellular interactions and Darwinian selection. Evolutionary game theory incorporates both of these principles, and has been proposed as a framework to understand tumour cell population dynamics. A cornerstone of evolutionary dynamics is the replicator equation, which describes changes in the relative abundance of different cell types, and is able to predict evolutionary equilibria. Typically, the replicator equation focuses on differences in relative fitness. We here show that this framework might not be sufficient under all circumstances, as it neglects important aspects of population growth. Standard replicator dynamics might miss critical differences in the time it takes to reach an equilibrium, as this time also depends on cellular turnover in growing but bounded populations. As the system reaches a stable manifold, the time to reach equilibrium depends on cellular death and birth rates. These rates shape the time scales, in particular, in coevolutionary dynamics of growth factor producers and free-riders. Replicator dynamics might be an appropriate framework only when birth and death rates are of similar magnitude. Otherwise, population growth effects cannot be neglected when predicting the time to reach an equilibrium, and cell-type-specific rates have to be accounted for explicitly. © 2017 The Authors.

The combination of system dynamics and game theory in analyzing oligopoly markets

Directory of Open Access Journals (Sweden)

Ali Mohammadi

2016-04-01

Full Text Available In this paper, we present a hybrid method of game theory and dynamic systems to study the behavior of firms in an oligopoly market. The aim of this study is to build a model for an oligopoly game on the basis of feedback loops and system dynamics approach and to solve the resulted problems under some special conditions where traditional game theory methods are unable to handle. The method includes a combination of qualitative methods including interviews with industry experts to prepare the model and quantitative methods of system dynamics, simulation methodologies and game theory. The results indicate that competitive behavior and the important parameters such as volume of demand, interest rates and price fluctuation will be stabilized after a transition period.

Online networks, social interaction and segregation: An evolutionary approach

OpenAIRE

Antoci, Angelo; Sabatini, Fabio

2018-01-01

There is growing evidence that face-to-face interaction is declining in many countries, exacerbating the phenomenon of social isolation. On the other hand, social interaction through online networking sites is steeply rising. To analyze these societal dynamics, we have built an evolutionary game model in which agents can choose between three strategies of social participation: 1) interaction via both online social networks and face-to-face encounters; 2) interaction by exclusive means of face...

Game theory decisions, interaction and evolution

CERN Document Server

Webb, James N

2007-01-01

This introduction to game theory is written from a mathematical perspective. Its primary purpose is to be a first course for undergraduate students of mathematics, but it also contains material which will be of interest to advanced students or researchers in biology and economics. The outstanding feature of the book is that it provides a unified account of three types of decision problem: Situations involving a single decision-maker: in which a sequence of choices is to be made in "a game against nature". This introduces the basic ideas of optimality and decision processes. Classical game theory: in which the interactions of two or more decision-makers are considered. This leads to the concept of the Nash equilibrium. Evolutionary game theory: in which the changing structure of a population of interacting decision makers is considered. This leads to the ideas of evolutionarily stable strategies and replicator dynamics. An understanding of basic calculus and probability is assumed but no prior knowledge of gam...

Abstract of Dynamic Range: When Game Design and Narratives Unite

OpenAIRE

Arsenault, Dominic

2005-01-01

This paper proposes a tool and methodology for measuring the degree of freedom given to a player in any resource-driven game (that is, any game in which managing resources is an integral part of the gameplay). This concept, which I call the Dynamic Range, can be used namely to evaluate a given game system’s potential for developing emergent narratives, as defined by Henry Jenkins in his publication Game Design as Narrative Architecture. While Jenkins places at the heart of the creation of nar...

The Hitchhiker’s Guide to Adaptive Dynamics

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Jacob Johansson

2013-06-01

Full Text Available Adaptive dynamics is a mathematical framework for studying evolution. It extends evolutionary game theory to account for more realistic ecological dynamics and it can incorporate both frequency- and density-dependent selection. This is a practical guide to adaptive dynamics that aims to illustrate how the methodology can be applied to the study of specific systems. The theory is presented in detail for a single, monomorphic, asexually reproducing population. We explain the necessary terminology to understand the basic arguments in models based on adaptive dynamics, including invasion fitness, the selection gradient, pairwise invasibility plots (PIP, evolutionarily singular strategies, and the canonical equation. The presentation is supported with a worked-out example of evolution of arrival times in migratory birds. We show how the adaptive dynamics methodology can be extended to study evolution in polymorphic populations using trait evolution plots (TEPs. We give an overview of literature that generalises adaptive dynamics techniques to other scenarios, such as sexual, diploid populations, and spatially-structured populations. We conclude by discussing how adaptive dynamics relates to evolutionary game theory and how adaptive-dynamics techniques can be used in speciation research.

Cooperation in an evolutionary prisoner’s dilemma game with probabilistic strategies

International Nuclear Information System (INIS)

Li Haihong; Dai Qionglin; Cheng Hongyan; Yang Junzhong

2012-01-01

Highlights: ► Introducing probabilistic strategies instead of the pure C/D in the PDG. ► The strategies patterns depends on interaction structures and updating rules. ► There exists an optimal increment of the probabilistic strategy. - Abstract: In this work, we investigate an evolutionary prisoner’s dilemma game in structured populations with probabilistic strategies instead of the pure strategies of cooperation and defection. We explore the model in details by considering different strategy update rules and different population structures. We find that the distribution of probabilistic strategies patterns is dependent on both the interaction structures and the updating rules. We also find that, when an individual updates her strategy by increasing or decreasing her probabilistic strategy a certain amount towards that of her opponent, there exists an optimal increment of the probabilistic strategy at which the cooperator frequency reaches its maximum.

Equilibria, information and frustration in heterogeneous network games with conflicting preferences

Science.gov (United States)

Mazzoli, M.; Sánchez, A.

2017-11-01

Interactions between people are the basis on which the structure of our society arises as a complex system and, at the same time, are the starting point of any physical description of it. In the last few years, much theoretical research has addressed this issue by combining the physics of complex networks with a description of interactions in terms of evolutionary game theory. We here take this research a step further by introducing a most salient societal factor such as the individuals’ preferences, a characteristic that is key to understanding much of the social phenomenology these days. We consider a heterogeneous, agent-based model in which agents interact strategically with their neighbors, but their preferences and payoffs for the possible actions differ. We study how such a heterogeneous network behaves under evolutionary dynamics and different strategic interactions, namely coordination games and best shot games. With this model we study the emergence of the equilibria predicted analytically in random graphs under best response dynamics, and we extend this test to unexplored contexts like proportional imitation and scale free networks. We show that some theoretically predicted equilibria do not arise in simulations with incomplete information, and we demonstrate the importance of the graph topology and the payoff function parameters for some games. Finally, we discuss our results with the available experimental evidence on coordination games, showing that our model agrees better with the experiment than standard economic theories, and draw hints as to how to maximize social efficiency in situations of conflicting preferences.

Aspiration dynamics and the sustainability of resources in the public goods dilemma

Energy Technology Data Exchange (ETDEWEB)

Du, Jinming, E-mail: jmdu@pku.edu.cn [Center for Systems and Control, College of Engineering, Peking University, Beijing 100871 (China); Wu, Bin, E-mail: bin.wu@evolbio.mpg.de [School of Science, Beijing University of Posts and Communications, Beijing 100876 (China); Department of Evolutionary Theory, Max-Planck Institute for Evolutionary Biology, August-Thienemann-Straße 2, 24306 Plön (Germany); Wang, Long, E-mail: longwang@pku.edu.cn [Center for Systems and Control, College of Engineering, Peking University, Beijing 100871 (China)

2016-04-01

How to exploit public non-renewable resources is a public goods dilemma. Individuals can choose to limit the depletion in order to use the resource for a longer time or consume more goods to benefit themselves. When the resource is used up, there is no benefit for the future generations any more, thus the evolutionary process ends. Here we investigate what mechanisms can extend the use of resources in the framework of evolutionary game theory under two updating rules based on imitation and aspiration, respectively. Compared with imitation process, aspiration dynamics may prolong the sustainable time of a public resource. - Highlights: • We establish a game model to capture the sustainable time of public goods. • We propose a theoretical method to study how fast an evolutionary process ends. • Strong selection shortens the evolutionary time of public resource dilemma. • Compared with imitation process, aspiration dynamics prolong the sustainable time. • The sustainable time is the shortest for the intermediate aspiration level.

Aspiration dynamics and the sustainability of resources in the public goods dilemma

International Nuclear Information System (INIS)

Du, Jinming; Wu, Bin; Wang, Long

2016-01-01

How to exploit public non-renewable resources is a public goods dilemma. Individuals can choose to limit the depletion in order to use the resource for a longer time or consume more goods to benefit themselves. When the resource is used up, there is no benefit for the future generations any more, thus the evolutionary process ends. Here we investigate what mechanisms can extend the use of resources in the framework of evolutionary game theory under two updating rules based on imitation and aspiration, respectively. Compared with imitation process, aspiration dynamics may prolong the sustainable time of a public resource. - Highlights: • We establish a game model to capture the sustainable time of public goods. • We propose a theoretical method to study how fast an evolutionary process ends. • Strong selection shortens the evolutionary time of public resource dilemma. • Compared with imitation process, aspiration dynamics prolong the sustainable time. • The sustainable time is the shortest for the intermediate aspiration level.

Promoting the Sustainable Building Market: an Evolution Analysis and System Dynamics Simulation on Behaviors of Real Estate Developers and Government

Directory of Open Access Journals (Sweden)

Xiuli Xie

2014-05-01

Full Text Available Purpose: The Chinese government takes measures to promote the development of green building (GB. But until 2013, there are only few green buildings in China. The real estate developers are skeptical in entering GB market, which requires theories to explain developers and government’s behaviors.Design/methodology/approach: In this study, we attempt Evolutionary game theory and System dynamics (SD into the analysis. A system dynamics model is built for studying evolutionary games between the government and developers in greening building decision making.Findings and Originality/value: The results of mixed-strategy stability analysis and SD simulation show that evolutionary equilibrium does not exist with a static government incentive. Therefore, a dynamical incentive is suggested in the SD model for promoting the green building market. The symmetric game and asymmetric game between two developers show, if the primary proportion who choose GB strategy is lower, all the group in game may finally evolve to GB strategy. In this case and in this time, the government should take measures to encourage developers to enter into the GB market. If the proportion who choose GB strategy is high enough, the government should gradually cancel or reduce those incentive measure.Research limitations/implications: an Evolution Analysis and System Dynamics Simulation on Behaviors of Real Estate Developers and Government could give some advice for the government to promote the green building market.

Feedback between Population and Evolutionary Dynamics Determines the Fate of Social Microbial Populations

Science.gov (United States)

Sanchez, Alvaro; Gore, Jeff

2013-01-01

The evolutionary spread of cheater strategies can destabilize populations engaging in social cooperative behaviors, thus demonstrating that evolutionary changes can have profound implications for population dynamics. At the same time, the relative fitness of cooperative traits often depends upon population density, thus leading to the potential for bi-directional coupling between population density and the evolution of a cooperative trait. Despite the potential importance of these eco-evolutionary feedback loops in social species, they have not yet been demonstrated experimentally and their ecological implications are poorly understood. Here, we demonstrate the presence of a strong feedback loop between population dynamics and the evolutionary dynamics of a social microbial gene, SUC2, in laboratory yeast populations whose cooperative growth is mediated by the SUC2 gene. We directly visualize eco-evolutionary trajectories of hundreds of populations over 50–100 generations, allowing us to characterize the phase space describing the interplay of evolution and ecology in this system. Small populations collapse despite continual evolution towards increased cooperative allele frequencies; large populations with a sufficient number of cooperators “spiral” to a stable state of coexistence between cooperator and cheater strategies. The presence of cheaters does not significantly affect the equilibrium population density, but it does reduce the resilience of the population as well as its ability to adapt to a rapidly deteriorating environment. Our results demonstrate the potential ecological importance of coupling between evolutionary dynamics and the population dynamics of cooperatively growing organisms, particularly in microbes. Our study suggests that this interaction may need to be considered in order to explain intraspecific variability in cooperative behaviors, and also that this feedback between evolution and ecology can critically affect the demographic fate

feedback between population and evolutionary dynamics determines the fate of social microbial populations.

Directory of Open Access Journals (Sweden)

Alvaro Sanchez

Full Text Available The evolutionary spread of cheater strategies can destabilize populations engaging in social cooperative behaviors, thus demonstrating that evolutionary changes can have profound implications for population dynamics. At the same time, the relative fitness of cooperative traits often depends upon population density, thus leading to the potential for bi-directional coupling between population density and the evolution of a cooperative trait. Despite the potential importance of these eco-evolutionary feedback loops in social species, they have not yet been demonstrated experimentally and their ecological implications are poorly understood. Here, we demonstrate the presence of a strong feedback loop between population dynamics and the evolutionary dynamics of a social microbial gene, SUC2, in laboratory yeast populations whose cooperative growth is mediated by the SUC2 gene. We directly visualize eco-evolutionary trajectories of hundreds of populations over 50-100 generations, allowing us to characterize the phase space describing the interplay of evolution and ecology in this system. Small populations collapse despite continual evolution towards increased cooperative allele frequencies; large populations with a sufficient number of cooperators "spiral" to a stable state of coexistence between cooperator and cheater strategies. The presence of cheaters does not significantly affect the equilibrium population density, but it does reduce the resilience of the population as well as its ability to adapt to a rapidly deteriorating environment. Our results demonstrate the potential ecological importance of coupling between evolutionary dynamics and the population dynamics of cooperatively growing organisms, particularly in microbes. Our study suggests that this interaction may need to be considered in order to explain intraspecific variability in cooperative behaviors, and also that this feedback between evolution and ecology can critically affect the

Reinforcement learning in complementarity game and population dynamics.

Science.gov (United States)

Jost, Jürgen; Li, Wei

2014-02-01

We systematically test and compare different reinforcement learning schemes in a complementarity game [J. Jost and W. Li, Physica A 345, 245 (2005)] played between members of two populations. More precisely, we study the Roth-Erev, Bush-Mosteller, and SoftMax reinforcement learning schemes. A modified version of Roth-Erev with a power exponent of 1.5, as opposed to 1 in the standard version, performs best. We also compare these reinforcement learning strategies with evolutionary schemes. This gives insight into aspects like the issue of quick adaptation as opposed to systematic exploration or the role of learning rates.

Genome-driven evolutionary game theory helps understand the rise of metabolic interdependencies in microbial communities.

Science.gov (United States)

Zomorrodi, Ali R; Segrè, Daniel

2017-11-16

Metabolite exchanges in microbial communities give rise to ecological interactions that govern ecosystem diversity and stability. It is unclear, however, how the rise of these interactions varies across metabolites and organisms. Here we address this question by integrating genome-scale models of metabolism with evolutionary game theory. Specifically, we use microbial fitness values estimated by metabolic models to infer evolutionarily stable interactions in multi-species microbial "games". We first validate our approach using a well-characterized yeast cheater-cooperator system. We next perform over 80,000 in silico experiments to infer how metabolic interdependencies mediated by amino acid leakage in Escherichia coli vary across 189 amino acid pairs. While most pairs display shared patterns of inter-species interactions, multiple deviations are caused by pleiotropy and epistasis in metabolism. Furthermore, simulated invasion experiments reveal possible paths to obligate cross-feeding. Our study provides genomically driven insight into the rise of ecological interactions, with implications for microbiome research and synthetic ecology.

Contrasting evolutionary dynamics between angiosperm and mammalian genomes

Czech Academy of Sciences Publication Activity Database

Kejnovský, Eduard; Leitch, I.J.; Leitch, A.R.

2009-01-01

Roč. 24, č. 10 (2009), s. 572-582 ISSN 0169-5347 R&D Projects: GA MŠk(CZ) LC06004 Institutional research plan: CEZ:AV0Z50040507; CEZ:AV0Z50040702 Keywords : genomes * evolutionary dynamics * recombination Subject RIV: BO - Biophysics Impact factor: 11.564, year: 2009

Designing a performance measurement system for supply chain using balanced scorecard, path analysis, cooperative game theory and evolutionary game theory: A Case Study

Directory of Open Access Journals (Sweden)

Seyed Hootan Eskafi

2015-04-01

Full Text Available In recent years, supply chain management is known as the key factor for achieving competitive advantage. Better customer service, revenue improvement and cost reduction are the results of this philosophy. Organizations can manage the performance of their firms by appropriate goal setting, identifying criteria and continuous performance measurement, which creates a good view for the business circumstances. Developing and defining appropriate indicators at different levels of chain is necessary for implementing a performance measurement system. In this study, we propose a new method to determine the measurement indicators and strategies of the company in term of balanced scorecard. The study is a combination of balanced scorecard, path analysis, evolutionary game theory and cooperative game theory for strategic planning. The study offers an appropriate program for future activities of organizations and determines the present status of the firm. The implementation of the proposed method is introduced for a food producer and the results are analyzed.

Evolutionary dynamics of populations with conflicting interactions: Classification and analytical treatment considering asymmetry and power

Science.gov (United States)

Helbing, Dirk; Johansson, Anders

2010-01-01

Evolutionary game theory has been successfully used to investigate the dynamics of systems, in which many entities have competitive interactions. From a physics point of view, it is interesting to study conditions under which a coordination or cooperation of interacting entities will occur, be it spins, particles, bacteria, animals, or humans. Here, we analyze the case, where the entities are heterogeneous, particularly the case of two populations with conflicting interactions and two possible states. For such systems, explicit mathematical formulas will be determined for the stationary solutions and the associated eigenvalues, which determine their stability. In this way, four different types of system dynamics can be classified and the various kinds of phase transitions between them will be discussed. While these results are interesting from a physics point of view, they are also relevant for social, economic, and biological systems, as they allow one to understand conditions for (1) the breakdown of cooperation, (2) the coexistence of different behaviors (“subcultures”), (3) the evolution of commonly shared behaviors (“norms”), and (4) the occurrence of polarization or conflict. We point out that norms have a similar function in social systems that forces have in physics.

Evolutionary dynamics of incubation periods.

Science.gov (United States)

Ottino-Loffler, Bertrand; Scott, Jacob G; Strogatz, Steven H

2017-12-21

The incubation period for typhoid, polio, measles, leukemia and many other diseases follows a right-skewed, approximately lognormal distribution. Although this pattern was discovered more than sixty years ago, it remains an open question to explain its ubiquity. Here, we propose an explanation based on evolutionary dynamics on graphs. For simple models of a mutant or pathogen invading a network-structured population of healthy cells, we show that skewed distributions of incubation periods emerge for a wide range of assumptions about invader fitness, competition dynamics, and network structure. The skewness stems from stochastic mechanisms associated with two classic problems in probability theory: the coupon collector and the random walk. Unlike previous explanations that rely crucially on heterogeneity, our results hold even for homogeneous populations. Thus, we predict that two equally healthy individuals subjected to equal doses of equally pathogenic agents may, by chance alone, show remarkably different time courses of disease.

Integrating evolutionary game theory into an agent-based model of ductal carcinoma in situ: Role of gap junctions in cancer progression.

Science.gov (United States)

Malekian, Negin; Habibi, Jafar; Zangooei, Mohammad Hossein; Aghakhani, Hojjat

2016-11-01

There are many cells with various phenotypic behaviors in cancer interacting with each other. For example, an apoptotic cell may induce apoptosis in adjacent cells. A living cell can also protect cells from undergoing apoptosis and necrosis. These survival and death signals are propagated through interaction pathways between adjacent cells called gap junctions. The function of these signals depends on the cellular context of the cell receiving them. For instance, a receiver cell experiencing a low level of oxygen may interpret a received survival signal as an apoptosis signal. In this study, we examine the effect of these signals on tumor growth. We make an evolutionary game theory component in order to model the signal propagation through gap junctions. The game payoffs are defined as a function of cellular context. Then, the game theory component is integrated into an agent-based model of tumor growth. After that, the integrated model is applied to ductal carcinoma in situ, a type of early stage breast cancer. Different scenarios are explored to observe the impact of the gap junction communication and parameters of the game theory component on cancer progression. We compare these scenarios by using the Wilcoxon signed-rank test. The Wilcoxon signed-rank test succeeds in proving a significant difference between the tumor growth of the model before and after considering the gap junction communication. The Wilcoxon signed-rank test also proves that the tumor growth significantly depends on the oxygen threshold of turning survival signals into apoptosis. In this study, the gap junction communication is modeled by using evolutionary game theory to illustrate its role at early stage cancers such as ductal carcinoma in situ. This work indicates that the gap junction communication and the oxygen threshold of turning survival signals into apoptosis can notably affect cancer progression. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Evolutionary Fates and Dynamic Functionalization of Young Duplicate Genes in Arabidopsis Genomes.

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Wang, Jun; Tao, Feng; Marowsky, Nicholas C; Fan, Chuanzhu

2016-09-01

Gene duplication is a primary means to generate genomic novelties, playing an essential role in speciation and adaptation. Particularly in plants, a high abundance of duplicate genes has been maintained for significantly long periods of evolutionary time. To address the manner in which young duplicate genes were derived primarily from small-scale gene duplication and preserved in plant genomes and to determine the underlying driving mechanisms, we generated transcriptomes to produce the expression profiles of five tissues in Arabidopsis thaliana and the closely related species Arabidopsis lyrata and Capsella rubella Based on the quantitative analysis metrics, we investigated the evolutionary processes of young duplicate genes in Arabidopsis. We determined that conservation, neofunctionalization, and specialization are three main evolutionary processes for Arabidopsis young duplicate genes. We explicitly demonstrated the dynamic functionalization of duplicate genes along the evolutionary time scale. Upon origination, duplicates tend to maintain their ancestral functions; but as they survive longer, they might be likely to develop distinct and novel functions. The temporal evolutionary processes and functionalization of plant duplicate genes are associated with their ancestral functions, dynamic DNA methylation levels, and histone modification abundances. Furthermore, duplicate genes tend to be initially expressed in pollen and then to gain more interaction partners over time. Altogether, our study provides novel insights into the dynamic retention processes of young duplicate genes in plant genomes. © 2016 American Society of Plant Biologists. All rights reserved.

Game-based dynamic simulations supporting technical education and training

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Tore Bjølseth

2006-04-01

Full Text Available Educational games may improve learning by taking advantage of the new knowledge and skills of today’s students obtained from extensive use of interactive games. This paper describes how interactive dynamic simulators of advanced technical systems and phenomena can be shaped and adapted as games and competitions supporting technical education and training. Some selected examples at different educational levels are shown, from vocational training to university level courses. The potential benefit and perceived learning effect of this approach is also described and underpinned from comprehensive user feedback.

Cognitive Hierarchy Theory and Two-Person Games

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Carlos Gracia-Lázaro

2017-01-01

Full Text Available The outcome of many social and economic interactions, such as stock-market transactions, is strongly determined by the predictions that agents make about the behavior of other individuals. Cognitive hierarchy theory provides a framework to model the consequences of forecasting accuracy that has proven to fit data from certain types of game theory experiments, such as Keynesian beauty contests and entry games. Here, we focus on symmetric two-player-two-action games and establish an algorithm to find the players’ strategies according to the cognitive hierarchy approach. We show that the snowdrift game exhibits a pattern of behavior whose complexity grows as the cognitive levels of players increases. In addition to finding the solutions up to the third cognitive level, we demonstrate, in this theoretical frame, two new properties of snowdrift games: (i any snowdrift game can be characterized by only a parameter, its class; (ii they are anti-symmetric with respect to the diagonal of the pay-off’s space. Finally, we propose a model based on an evolutionary dynamics that captures the main features of the cognitive hierarchy theory.

A new concept: Epigenetic game theory. Comment on: ;Epigenetic game theory: How to compute the epigenetic control of maternal-to-zygotic transition; by Qian Wang et al.

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Zheng, Xiu-Deng; Tao, Yi

2017-03-01

The evolutionary significance of the interaction between paternal and maternal genomes in fertilized zygotes is a very interesting and challenging question. Wang et al. developed the concept of epigenetic game theory, and they try to use this concept to explain the interaction between paternal and maternal genomes in fertilized zygotes [1]. They emphasize that the embryogenesis can be considered as an ecological system in which two highly distinct and specialized gametes coordinate through either cooperation or competition, or both, to maximize the fitness of embryos under Darwinian selection. More specifically, they integrate game theory to model the pattern of coordination of paternal genome and maternal genomes mediated by DNA methylation dynamics, and they called this epigenetic game theory.

Evolutionary dynamics of protein domain architecture in plants

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Zhang Xue-Cheng

2012-01-01

Full Text Available Abstract Background Protein domains are the structural, functional and evolutionary units of the protein. Protein domain architectures are the linear arrangements of domain(s in individual proteins. Although the evolutionary history of protein domain architecture has been extensively studied in microorganisms, the evolutionary dynamics of domain architecture in the plant kingdom remains largely undefined. To address this question, we analyzed the lineage-based protein domain architecture content in 14 completed green plant genomes. Results Our analyses show that all 14 plant genomes maintain similar distributions of species-specific, single-domain, and multi-domain architectures. Approximately 65% of plant domain architectures are universally present in all plant lineages, while the remaining architectures are lineage-specific. Clear examples are seen of both the loss and gain of specific protein architectures in higher plants. There has been a dynamic, lineage-wise expansion of domain architectures during plant evolution. The data suggest that this expansion can be largely explained by changes in nuclear ploidy resulting from rounds of whole genome duplications. Indeed, there has been a decrease in the number of unique domain architectures when the genomes were normalized into a presumed ancestral genome that has not undergone whole genome duplications. Conclusions Our data show the conservation of universal domain architectures in all available plant genomes, indicating the presence of an evolutionarily conserved, core set of protein components. However, the occurrence of lineage-specific domain architectures indicates that domain architecture diversity has been maintained beyond these core components in plant genomes. Although several features of genome-wide domain architecture content are conserved in plants, the data clearly demonstrate lineage-wise, progressive changes and expansions of individual protein domain architectures, reinforcing

Bribe and Punishment: An Evolutionary Game-Theoretic Analysis of Bribery.

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Prateek Verma

Full Text Available Harassment bribes, paid by citizens to corrupt officers for services the former are legally entitled to, constitute one of the most widespread forms of corruption in many countries. Nation states have adopted different policies to address this form of corruption. While some countries make both the bribe giver and the bribe taker equally liable for the crime, others impose a larger penalty on corrupt officers. We examine the consequences of asymmetric and symmetric penalties by developing deterministic and stochastic evolutionary game-theoretic models of bribery. We find that the asymmetric penalty scheme can lead to a reduction in incidents of bribery. However, the extent of reduction depends on how the players update their strategies over time. If the interacting members change their strategies with a probability proportional to the payoff of the alternative strategy option, the reduction in incidents of bribery is less pronounced. Our results indicate that changing from a symmetric to an asymmetric penalty scheme may not suffice in achieving significant reductions in incidents of harassment bribery.

Bribe and Punishment: An Evolutionary Game-Theoretic Analysis of Bribery.

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Verma, Prateek; Sengupta, Supratim

2015-01-01

Harassment bribes, paid by citizens to corrupt officers for services the former are legally entitled to, constitute one of the most widespread forms of corruption in many countries. Nation states have adopted different policies to address this form of corruption. While some countries make both the bribe giver and the bribe taker equally liable for the crime, others impose a larger penalty on corrupt officers. We examine the consequences of asymmetric and symmetric penalties by developing deterministic and stochastic evolutionary game-theoretic models of bribery. We find that the asymmetric penalty scheme can lead to a reduction in incidents of bribery. However, the extent of reduction depends on how the players update their strategies over time. If the interacting members change their strategies with a probability proportional to the payoff of the alternative strategy option, the reduction in incidents of bribery is less pronounced. Our results indicate that changing from a symmetric to an asymmetric penalty scheme may not suffice in achieving significant reductions in incidents of harassment bribery.

The Use of Game Dynamics to Enhance Curriculum and Instruction: What Teachers Can Learn from the Design of Video Games

OpenAIRE

Curtis Chandler

2013-01-01

Video games have received an increased amount of attention from educational institutions due to their widespread use and their ability to engage and sustain players in difficult learning tasks for extended amounts of time. While many studies have been done on digital games' potential to impact learning, only recently has educational research begun to analyze the game dynamics embedded in video games used to immerse students in difficult problem-solving and to support their learning. This ar...

Game theory and extremal optimization for community detection in complex dynamic networks.

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Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca

2014-01-01

The detection of evolving communities in dynamic complex networks is a challenging problem that recently received attention from the research community. Dynamics clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal optimization to address dynamic communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach.

Flash Learning Games Wow Students and Instructors: Moving Toward An Academic Gaming Portal

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Dan H Lim

2003-02-01

Full Text Available This paper describes and discusses the rationale, background, design, and implementation of Flash learning games. The paper explains why Macromedia Flash has been selected as the authoring tool in the development of highly interactive learning games for online learning. The background evolutionary process of developing the learning games points out why it has been a daunting task to create compelling learning games that impact learning. Designing learning game objects that allow other educators to customize game content is the core of this paper. The author envisions this academic gaming project will evolve into an academic gaming portal, developed in conjunction with other major institutional partners.

Chaotic evolution of prisoner's dilemma game with volunteering on interdependent networks

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Luo, Chao; Zhang, Xiaolin; Zheng, YuanJie

2017-06-01

In this article, the evolution of prisoner's dilemma game with volunteering on interdependent networks is investigated. Different from the traditional two-strategy game, voluntary participation as an additional strategy is involved in repeated game, that can introduce more complex evolutionary dynamics. And, interdependent networks provide a more generalized network architecture to study the intricate variability of dynamics. We have showed that voluntary participation could effectively promote the density of co-operation, that is also greatly affected by interdependent strength between two coupled networks. We further discussed the influence of interdependent strength on the densities of different strategies and found that an intermediate interdependence would play a bigger role on the evolution of dynamics. Subsequently, the critical values of the defection temptation for phase transitions under different conditions have been studied. Moreover, the global oscillations induced by the circle of dominance of three strategies on interdependent networks have been quantitatively investigated. Counter-intuitively, the oscillations of strategy densities are not periodic or stochastic, but have rich dynamical behaviors. By means of various analysis tools, we have demonstrated the global oscillations of strategy densities possessed chaotic characteristics.

n-Person Dynamic Strategic Market Games

Energy Technology Data Exchange (ETDEWEB)

Wiecek, Piotr, E-mail: Piotr.Wiecek@pwr.wroc.pl [Wroclaw University of Technology, Institute of Mathematics and Computer Science (Poland)

2012-04-15

We present a discrete n-person model of a dynamic strategic market game. We show that for some values of the discount factor the game possesses a stationary equilibrium where all the players make high bids. Within the class of all the high-bidding strategies we distinguish between two classes of more and less aggressive ones. We show that the set of discount factors for which these more aggressive strategies form equilibria shrinks as n goes to infinity. On the other hand, the analogous set for the less aggressive strategies grows to the whole interval (0,1) as n grows to infinity. Further we analyze the properties of the value function corresponding to these high-bidding equilibria. We also give some numerical examples contradicting some other properties that seem intuitive.

Fixation Probabilities of Evolutionary Graphs Based on the Positions of New Appearing Mutants

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Pei-ai Zhang

2014-01-01

Full Text Available Evolutionary graph theory is a nice measure to implement evolutionary dynamics on spatial structures of populations. To calculate the fixation probability is usually regarded as a Markov chain process, which is affected by the number of the individuals, the fitness of the mutant, the game strategy, and the structure of the population. However the position of the new mutant is important to its fixation probability. Here the position of the new mutant is laid emphasis on. The method is put forward to calculate the fixation probability of an evolutionary graph (EG of single level. Then for a class of bilevel EGs, their fixation probabilities are calculated and some propositions are discussed. The conclusion is obtained showing that the bilevel EG is more stable than the corresponding one-rooted EG.

Epigenetic game theory and its application in plants. Comment on: ;Epigenetic game theory: How to compute the epigenetic control of maternal-to-zygotic transition; by Qian Wang et al.

Science.gov (United States)

Zhang, Yuan-Ming; Zhang, Yinghao; Guo, Mingyue

2017-03-01

Wang's et al. article [1] is the first to integrate game theory (especially evolutionary game theory) with epigenetic modification of zygotic genomes. They described and assessed a modeling framework based on evolutionary game theory to quantify, how sperms and oocytes interact through epigenetic processes, to determine embryo development. They also studied the internal mechanisms for normal embryo development: 1) evolutionary interactions between DNA methylation of the paternal and maternal genomes, and 2) the application of game theory to formulate and quantify how different genes compete or cooperate to regulate embryogenesis through methylation. Although it is not very comprehensive and profound regarding game theory modeling, this article bridges the gap between evolutionary game theory and the epigenetic control of embryo development by powerful ordinary differential equations (ODEs). The epiGame framework includes four aspects: 1) characterizing how epigenetic game theory works by the strategy matrix, in which the pattern and relative magnitude of the methylation effects on embryogenesis, are described by the cooperation and competition mechanisms, 2) quantifying the game that the direction and degree of P-M interactions over embryo development can be explained by the sign and magnitude of interaction parameters in model (2), 3) modeling epigenetic interactions within the morula, especially for two coupled nonlinear ODEs, with explicit functions in model (4), which provide a good fit to the observed data for the two sexes (adjusted R2 = 0.956), and 4) revealing multifactorial interactions in embryogenesis from the coupled ODEs in model (2) to triplet ODEs in model (6). Clearly, this article extends game theory from evolutionary game theory to epigenetic game theory.

Weight of fitness deviation governs strict physical chaos in replicator dynamics.

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Pandit, Varun; Mukhopadhyay, Archan; Chakraborty, Sagar

2018-03-01

Replicator equation-a paradigm equation in evolutionary game dynamics-mathematizes the frequency dependent selection of competing strategies vying to enhance their fitness (quantified by the average payoffs) with respect to the average fitnesses of the evolving population under consideration. In this paper, we deal with two discrete versions of the replicator equation employed to study evolution in a population where any two players' interaction is modelled by a two-strategy symmetric normal-form game. There are twelve distinct classes of such games, each typified by a particular ordinal relationship among the elements of the corresponding payoff matrix. Here, we find the sufficient conditions for the existence of asymptotic solutions of the replicator equations such that the solutions-fixed points, periodic orbits, and chaotic trajectories-are all strictly physical, meaning that the frequency of any strategy lies inside the closed interval zero to one at all times. Thus, we elaborate on which of the twelve types of games are capable of showing meaningful physical solutions and for which of the two types of replicator equation. Subsequently, we introduce the concept of the weight of fitness deviation that is the scaling factor in a positive affine transformation connecting two payoff matrices such that the corresponding one-shot games have exactly same Nash equilibria and evolutionary stable states. The weight also quantifies how much the excess of fitness of a strategy over the average fitness of the population affects the per capita change in the frequency of the strategy. Intriguingly, the weight's variation is capable of making the Nash equilibria and the evolutionary stable states, useless by introducing strict physical chaos in the replicator dynamics based on the normal-form game.

Evolutionary game theory and social learning can determine how vaccine scares unfold.

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Bauch, Chris T; Bhattacharyya, Samit

2012-01-01

Immunization programs have often been impeded by vaccine scares, as evidenced by the measles-mumps-rubella (MMR) autism vaccine scare in Britain. A "free rider" effect may be partly responsible: vaccine-generated herd immunity can reduce disease incidence to such low levels that real or imagined vaccine risks appear large in comparison, causing individuals to cease vaccinating. This implies a feedback loop between disease prevalence and strategic individual vaccinating behavior. Here, we analyze a model based on evolutionary game theory that captures this feedback in the context of vaccine scares, and that also includes social learning. Vaccine risk perception evolves over time according to an exogenously imposed curve. We test the model against vaccine coverage data and disease incidence data from two vaccine scares in England & Wales: the whole cell pertussis vaccine scare and the MMR vaccine scare. The model fits vaccine coverage data from both vaccine scares relatively well. Moreover, the model can explain the vaccine coverage data more parsimoniously than most competing models without social learning and/or feedback (hence, adding social learning and feedback to a vaccine scare model improves model fit with little or no parsimony penalty). Under some circumstances, the model can predict future vaccine coverage and disease incidence--up to 10 years in advance in the case of pertussis--including specific qualitative features of the dynamics, such as future incidence peaks and undulations in vaccine coverage due to the population's response to changing disease incidence. Vaccine scares could become more common as eradication goals are approached for more vaccine-preventable diseases. Such models could help us predict how vaccine scares might unfold and assist mitigation efforts.

Bidirectional Dynamic Diversity Evolutionary Algorithm for Constrained Optimization

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Weishang Gao

2013-01-01

Full Text Available Evolutionary algorithms (EAs were shown to be effective for complex constrained optimization problems. However, inflexible exploration-exploitation and improper penalty in EAs with penalty function would lead to losing the global optimum nearby or on the constrained boundary. To determine an appropriate penalty coefficient is also difficult in most studies. In this paper, we propose a bidirectional dynamic diversity evolutionary algorithm (Bi-DDEA with multiagents guiding exploration-exploitation through local extrema to the global optimum in suitable steps. In Bi-DDEA potential advantage is detected by three kinds of agents. The scale and the density of agents will change dynamically according to the emerging of potential optimal area, which play an important role of flexible exploration-exploitation. Meanwhile, a novel double optimum estimation strategy with objective fitness and penalty fitness is suggested to compute, respectively, the dominance trend of agents in feasible region and forbidden region. This bidirectional evolving with multiagents can not only effectively avoid the problem of determining penalty coefficient but also quickly converge to the global optimum nearby or on the constrained boundary. By examining the rapidity and veracity of Bi-DDEA across benchmark functions, the proposed method is shown to be effective.

A dynamic game of a transboundary pollutant with asymmetric players

International Nuclear Information System (INIS)

Martin, W.E.; Patrick, R.H.; Tolwinski, B.

1993-01-01

Modeling transboundary pollutants in a dynamic game framework provides a foundation for analyzing the impact of various policy options. The focus of this analysis is on the results of a tax/subsidy scheme used to address the transboundary problem of global climate change. A nonzero-sum dynamic game with asymmetric players is used to evaluate the policy impact of the tax/subsidy scheme on the respective player's value functions and strategies as determined by a Nash equilibrium feedback solution. The asymmetry of the players is reflected in their respective attitudes toward global climate change with one player benefiting from the change and the other losing. 17 refs., 5 tabs

Dynamics of Three Agent Games

OpenAIRE

Rador, Tonguc; Mungan, Muhittin

2007-01-01

We study the dynamics and resulting score distribution of three-agent games where after each competition a single agent wins and scores a point. A single competition is described by a triplet of numbers $p$, $t$ and $q$ denoting the probabilities that the team with the highest, middle or lowest accumulated score wins. We study the full family of solutions in the regime, where the number of agents and competitions is large, which can be regarded as a hydrodynamic limit. Depending on the parame...

Evolutionary Game Theory and Leadership

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Guastello, Stephen J.

2009-01-01

Comments on the article Leadership, followership, and evolution: Some lessons from the past by Van Vugt, Hogan, and Kaiser. This article offers a fresh perspective on leaders, followers, and their possible origins in nonhuman and primitive human behavior patterns. The connections between group coordination, leadership, and game theory have some…

Convergence analysis and control of evolutionary matrix-game dynamics

NARCIS (Netherlands)

Ramazi, Pouria

2017-01-01

Networks of decision-making individuals with simple dynamics may give rise to complex and seemingly unpredictable collective behaviors which may have negative consequences such as traffic jams and market crashes or positive outcomes such as volunteer disaster relief and free-market stabilization.

Multiple equilibria and limit cycles in evolutonary games with Logit Dynamics

NARCIS (Netherlands)

Hommes, C.H.; Ochea, M.I.

2012-01-01

This note shows, by means of two simple, three-strategy games, the existence of stable periodic orbits and of multiple, interior steady states in a smooth version of the Best-Response Dynamics, the Logit Dynamics. The main finding is that, unlike Replicator Dynamics, generic Hopf bifurcation and

The impact of rapid evolution on population dynamics in the wild: experimental test of eco-evolutionary dynamics.

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Turcotte, Martin M; Reznick, David N; Hare, J Daniel

2011-11-01

Rapid evolution challenges the assumption that evolution is too slow to impact short-term ecological dynamics. This insight motivates the study of 'Eco-Evolutionary Dynamics' or how evolution and ecological processes reciprocally interact on short time scales. We tested how rapid evolution impacts concurrent population dynamics using an aphid (Myzus persicae) and an undomesticated host (Hirschfeldia incana) in replicated wild populations. We manipulated evolvability by creating non-evolving (single clone) and potentially evolving (two-clone) aphid populations that contained genetic variation in intrinsic growth rate. We observed significant evolution in two-clone populations whether or not they were exposed to predators and competitors. Evolving populations grew up to 42% faster and attained up to 67% higher density, compared with non-evolving control populations but only in treatments exposed to competitors and predators. Increased density also correlates with relative fitness of competing clones suggesting a full eco-evolutionary dynamic cycle defined as reciprocal interactions between evolution and density. © 2011 Blackwell Publishing Ltd/CNRS.

Evolutionary Fates and Dynamic Functionalization of Young Duplicate Genes in Arabidopsis Genomes1[OPEN

Science.gov (United States)

Wang, Jun; Tao, Feng; Marowsky, Nicholas C.; Fan, Chuanzhu

2016-01-01

Gene duplication is a primary means to generate genomic novelties, playing an essential role in speciation and adaptation. Particularly in plants, a high abundance of duplicate genes has been maintained for significantly long periods of evolutionary time. To address the manner in which young duplicate genes were derived primarily from small-scale gene duplication and preserved in plant genomes and to determine the underlying driving mechanisms, we generated transcriptomes to produce the expression profiles of five tissues in Arabidopsis thaliana and the closely related species Arabidopsis lyrata and Capsella rubella. Based on the quantitative analysis metrics, we investigated the evolutionary processes of young duplicate genes in Arabidopsis. We determined that conservation, neofunctionalization, and specialization are three main evolutionary processes for Arabidopsis young duplicate genes. We explicitly demonstrated the dynamic functionalization of duplicate genes along the evolutionary time scale. Upon origination, duplicates tend to maintain their ancestral functions; but as they survive longer, they might be likely to develop distinct and novel functions. The temporal evolutionary processes and functionalization of plant duplicate genes are associated with their ancestral functions, dynamic DNA methylation levels, and histone modification abundances. Furthermore, duplicate genes tend to be initially expressed in pollen and then to gain more interaction partners over time. Altogether, our study provides novel insights into the dynamic retention processes of young duplicate genes in plant genomes. PMID:27485883

Game Design Document Format For Video Games With Passive Dynamic Difficulty Adjustment

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Pratama Wirya Atmaja

2016-07-01

satisfaction of its players is the primary mean to measure its quality. One important element of player’s satisfaction is a proper difficulty level, which is neither too easy nor too hard. The current state-of-the-art way to implement it is with Dynamic Difficulty Adjustment (DDA, which allows the difficulty level of a video game to be adjusted at run-time. Currently, the most popular type of DDA is the passive one. Meanwhile, Game Design Document (GDD is an important artefact in the development process of a video game software, and there is still no GDD format that supports the design of passive DDA mechanism. The aim of this research was to find a new GDD format that supports the mechanism. We modified a general purpose GDD format by adding new parts for designing passive DDA mechanism. We tested the usefulness of the modified format in a testing process involving developers and players. The developers developed video games using the modified GDD format and the general purpose one. Their development processes were observed and evaluated to know if there were any difficulties. The resulting video games were played by the players to find which are better in terms of passive DDA mechanism. The result of developer testing showed that the modified format is better than the general purpose one. The result of player testing showed that the video games made with the modified format are better than their counterparts, albeit by an insignificant margin. Based on the results, we declare that the modified GDD format is successful.Keywords: Video game, requirement engineering, game design document, dynamic difficulty adjustment, software development.

Bacteria and game theory: the rise and fall of cooperation in spatially heterogeneous environments.

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Lambert, Guillaume; Vyawahare, Saurabh; Austin, Robert H

2014-08-06

One of the predictions of game theory is that cooperative behaviours are vulnerable to exploitation by selfish individuals, but this result seemingly contradicts the survival of cooperation observed in nature. In this review, we will introduce game theoretical concepts that lead to this conclusion and show how the spatial competition dynamics between microorganisms can be used to model the survival and maintenance of cooperation. In particular, we focus on how Escherichia coli bacteria with a growth advantage in stationary phase (GASP) phenotype maintain a proliferative phenotype when faced with overcrowding to gain a fitness advantage over wild-type populations. We review recent experimental approaches studying the growth dynamics of competing GASP and wild-type strains of E. coli inside interconnected microfabricated habitats and use a game theoretical approach to analyse the observed inter-species interactions. We describe how the use of evolutionary game theory and the ideal free distribution accurately models the spatial distribution of cooperative and selfish individuals in spatially heterogeneous environments. Using bacteria as a model system of cooperative and selfish behaviours may lead to a better understanding of the competition dynamics of other organisms-including tumour-host interactions during cancer development and metastasis.

A Self-adaptive Dynamic Evaluation Model for Diabetes Mellitus, Based on Evolutionary Strategies

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An-Jiang Lu

2016-03-01

Full Text Available In order to evaluate diabetes mellitus objectively and accurately, this paper builds a self-adaptive dynamic evaluation model for diabetes mellitus, based on evolutionary strategies. First of all, on the basis of a formalized description of the evolutionary process of diabetes syndromes, using a state transition function, it judges whether a disease is evolutionary, through an excitation parameter. It then, provides evidence for the rebuilding of the evaluation index system. After that, by abstracting and rebuilding the composition of evaluation indexes, it makes use of a heuristic algorithm to determine the composition of the evolved evaluation index set of diabetes mellitus, It then, calculates the weight of each index in the evolved evaluation index set of diabetes mellitus by building a dependency matrix and realizes the self-adaptive dynamic evaluation of diabetes mellitus under an evolutionary environment. Using this evaluation model, it is possible to, quantify all kinds of diagnoses and treatment experiences of diabetes and finally to adopt ideal diagnoses and treatment measures for different patients with diabetics.

How to Love the Bomb: Trying to solve the prisoner's dilemma with evolutionary game theory

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Castela, Vasco

Economists traditionally see altruistic acts as irrational. However, in the Prisoner's Dilemma, a rational player can do worse than a moral player. The rules of the game imply that one cannot defend one's best interest if one tries to. Game theory has struggled to explain how an agent could have access to the strategically best outcome without behaving irrationally, but with little success. Can a complex systems approach do better?. Peter Danielson, using Evolutionary Game Theory, has avoided some of the assumptions of Game Theory by using a complexity approach to reframe the problem, and offers a solution of sorts. According to Danielson, the foundations of altruism are mechanisms of deterrence that rely on credible threat - we are nice for fear of retaliation. He is both right and wrong. It will be argued that utilitarian, consequentialist principles must have been at work to create the conditions for altruistic acts to be performed. It is wrong to expect, however, that the same reasons are the reasons for action. In order for a model of genuine altruism to be possible, an extra cog must be inserted in the mechanism of causality in order to distance moral action from its strategic advantages. If emotions fulfill this role, we can tell a story in which it is rational to act on altruistic motivations and materially advantageous to hold such motivations. Moral sentiments can be seen as a tool designed by evolution to help optimize cooperation in a social environment. The proposed account integrates the Humean theory of motivation with Robert Frank's commitment model and Aristotle's views on moral education, keeping an adequate story of how it can be in our material interest to be moral without having to renounce to the existence of genuine acts of altruism.

Dynamic Bayesian Network Modeling of Game Based Diagnostic Assessments. CRESST Report 837

Science.gov (United States)

Levy, Roy

2014-01-01

Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. A Bayesian approach to model construction, calibration, and use in…

Quantum games on evolving random networks

OpenAIRE

Pawela, Łukasz

2015-01-01

We study the advantages of quantum strategies in evolutionary social dilemmas on evolving random networks. We focus our study on the two-player games: prisoner's dilemma, snowdrift and stag-hunt games. The obtained result show the benefits of quantum strategies for the prisoner's dilemma game. For the other two games, we obtain regions of parameters where the quantum strategies dominate, as well as regions where the classical strategies coexist.

Development and application of coupled system dynamics and game theory: A dynamic water conflict resolution method.

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Mehdi Zomorodian

Full Text Available Conflicts over water resources can be highly dynamic and complex due to the various factors which can affect such systems, including economic, engineering, social, hydrologic, environmental and even political, as well as the inherent uncertainty involved in many of these factors. Furthermore, the conflicting behavior, preferences and goals of stakeholders can often make such conflicts even more challenging. While many game models, both cooperative and non-cooperative, have been suggested to deal with problems over utilizing and sharing water resources, most of these are based on a static viewpoint of demand points during optimization procedures. Moreover, such models are usually developed for a single reservoir system, and so are not really suitable for application to an integrated decision support system involving more than one reservoir. This paper outlines a coupled simulation-optimization modeling method based on a combination of system dynamics (SD and game theory (GT. The method harnesses SD to capture the dynamic behavior of the water system, utilizing feedback loops between the system components in the course of the simulation. In addition, it uses GT concepts, including pure-strategy and mixed-strategy games as well as the Nash Bargaining Solution (NBS method, to find the optimum allocation decisions over available water in the system. To test the capability of the proposed method to resolve multi-reservoir and multi-objective conflicts, two different deterministic simulation-optimization models with increasing levels of complexity were developed for the Langat River basin in Malaysia. The later is a strategic water catchment that has a range of different stakeholders and managerial bodies, which are however willing to cooperate in order to avoid unmet demand. In our first model, all water users play a dynamic pure-strategy game. The second model then adds in dynamic behaviors to reservoirs to factor in inflow uncertainty and adjust the

Development and application of coupled system dynamics and game theory: A dynamic water conflict resolution method.

Science.gov (United States)

Zomorodian, Mehdi; Lai, Sai Hin; Homayounfar, Mehran; Ibrahim, Shaliza; Pender, Gareth

2017-01-01

Conflicts over water resources can be highly dynamic and complex due to the various factors which can affect such systems, including economic, engineering, social, hydrologic, environmental and even political, as well as the inherent uncertainty involved in many of these factors. Furthermore, the conflicting behavior, preferences and goals of stakeholders can often make such conflicts even more challenging. While many game models, both cooperative and non-cooperative, have been suggested to deal with problems over utilizing and sharing water resources, most of these are based on a static viewpoint of demand points during optimization procedures. Moreover, such models are usually developed for a single reservoir system, and so are not really suitable for application to an integrated decision support system involving more than one reservoir. This paper outlines a coupled simulation-optimization modeling method based on a combination of system dynamics (SD) and game theory (GT). The method harnesses SD to capture the dynamic behavior of the water system, utilizing feedback loops between the system components in the course of the simulation. In addition, it uses GT concepts, including pure-strategy and mixed-strategy games as well as the Nash Bargaining Solution (NBS) method, to find the optimum allocation decisions over available water in the system. To test the capability of the proposed method to resolve multi-reservoir and multi-objective conflicts, two different deterministic simulation-optimization models with increasing levels of complexity were developed for the Langat River basin in Malaysia. The later is a strategic water catchment that has a range of different stakeholders and managerial bodies, which are however willing to cooperate in order to avoid unmet demand. In our first model, all water users play a dynamic pure-strategy game. The second model then adds in dynamic behaviors to reservoirs to factor in inflow uncertainty and adjust the strategies for

Game-theoretic interference coordination approaches for dynamic spectrum access

CERN Document Server

Xu, Yuhua

2016-01-01

Written by experts in the field, this book is based on recent research findings in dynamic spectrum access for cognitive radio networks. It establishes a game-theoretic framework and presents cutting-edge technologies for distributed interference coordination. With game-theoretic formulation and the designed distributed learning algorithms, it provides insights into the interactions between multiple decision-makers and the converging stable states. Researchers, scientists and engineers in the field of cognitive radio networks will benefit from the book, which provides valuable information, useful methods and practical algorithms for use in emerging 5G wireless communication.

Experimental test of an eco-evolutionary dynamic feedback loop between evolution and population density in the green peach aphid.

Science.gov (United States)

Turcotte, Martin M; Reznick, David N; Daniel Hare, J

2013-05-01

An eco-evolutionary feedback loop is defined as the reciprocal impacts of ecology on evolutionary dynamics and evolution on ecological dynamics on contemporary timescales. We experimentally tested for an eco-evolutionary feedback loop in the green peach aphid, Myzus persicae, by manipulating initial densities and evolution. We found strong evidence that initial aphid density alters the rate and direction of evolution, as measured by changes in genotype frequencies through time. We also found that evolution of aphids within only 16 days, or approximately three generations, alters the rate of population growth and predicts density compared to nonevolving controls. The impact of evolution on population dynamics also depended on density. In one evolution treatment, evolution accelerated population growth by up to 10.3% at high initial density or reduced it by up to 6.4% at low initial density. The impact of evolution on population growth was as strong as or stronger than that caused by a threefold change in intraspecific density. We found that, taken together, ecological condition, here intraspecific density, alters evolutionary dynamics, which in turn alter concurrent population growth rate (ecological dynamics) in an eco-evolutionary feedback loop. Our results suggest that ignoring evolution in studies predicting population dynamics might lead us to over- or underestimate population density and that we cannot predict the evolutionary outcome within aphid populations without considering population size.

Experiential Learning in Vehicle Dynamics Education via Motion Simulation and Interactive Gaming

Directory of Open Access Journals (Sweden)

Kevin Hulme

2009-01-01

Full Text Available Creating active, student-centered learning situations in postsecondary education is an ongoing challenge for engineering educators. Contemporary students familiar with visually engaging and fast-paced games can find traditional classroom methods of lecture and guided laboratory experiments limiting. This paper presents a methodology that incorporates driving simulation, motion simulation, and educational practices into an engaging, gaming-inspired simulation framework for a vehicle dynamics curriculum. The approach is designed to promote active student participation in authentic engineering experiences that enhance learning about road vehicle dynamics. The paper presents the student use of physical simulation and large-scale visualization to discover the impact that design decisions have on vehicle design using a gaming interface. The approach is evaluated using two experiments incorporated into a sequence of two upper level mechanical engineering courses.

A quantitative evolutionary theory of adaptive behavior dynamics.

Science.gov (United States)

McDowell, J J

2013-10-01

The idea that behavior is selected by its consequences in a process analogous to organic evolution has been discussed for over 100 years. A recently proposed theory instantiates this idea by means of a genetic algorithm that operates on a population of potential behaviors. Behaviors in the population are represented by numbers in decimal integer (phenotypic) and binary bit string (genotypic) forms. One behavior from the population is emitted at random each time tick, after which a new population of potential behaviors is constructed by recombining parent behavior bit strings. If the emitted behavior produced a benefit to the organism, then parents are chosen on the basis of their phenotypic similarity to the emitted behavior; otherwise, they are chosen at random. After parent behavior recombination, the population is subjected to a small amount of mutation by flipping random bits in the population's bit strings. The behavior generated by this process of selection, reproduction, and mutation reaches equilibrium states that conform to every empirically valid equation of matching theory, exactly and without systematic error. These equations are known to describe the behavior of many vertebrate species, including humans, in a variety of experimental, naturalistic, natural, and social environments. The evolutionary theory also generates instantaneous dynamics and patterns of preference change in constantly changing environments that are consistent with the dynamics of live-organism behavior. These findings support the assertion that the world of behavior we observe and measure is generated by evolutionary dynamics. PsycINFO Database Record (c) 2013 APA, all rights reserved

Analysing Buyers' and Sellers' Strategic Interactions in Marketplaces: An Evolutionary Game Theoretic Approach

Science.gov (United States)

Vytelingum, Perukrishnen; Cliff, Dave; Jennings, Nicholas R.

We develop a new model to analyse the strategic behaviour of buyers and sellers in market mechanisms. In particular, we wish to understand how the different strategies they adopt affect their economic efficiency in the market and to understand the impact of these choices on the overall efficiency of the marketplace. To this end, we adopt a two-population evolutionary game theoretic approach, where we consider how the behaviours of both buyers and sellers evolve in marketplaces. In so doing, we address the shortcomings of the previous state-of-the-art analytical model that assumes that buyers and sellers have to adopt the same mixed strategy in the market. Finally, we apply our model in one of the most common market mechanisms, the Continuous Double Auction, and demonstrate how it allows us to provide new insights into the strategic interactions of such trading agents.

Dynamic Pricing of New Products in Competitive Markets: A Mean-Field Game Approach

OpenAIRE

Chenavaz, Régis; Paraschiv, Corina; Turinici, Gabriel

2017-01-01

Dynamic pricing of new products has been extensively studied in monopolistic and oligopolistic markets. But, the optimal control and differential game tools used to investigate the pricing behavior on markets with a finite number of firms are not well-suited to model competitive markets with an infinity of firms. Using a mean-field games approach, this paper examines dynamic pricing policies in competitive markets, where no firm exerts market power. The theoretical setting is based on a diffu...

Optimal dimensionality reduction of complex dynamics: the chess game as diffusion on a free-energy landscape.

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Krivov, Sergei V

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game--the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

Security Analysis of Dynamic SDN Architectures Based on Game Theory

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Chao Qi

2018-01-01

Full Text Available Security evaluation of SDN architectures is of critical importance to develop robust systems and address attacks. Focused on a novel-proposed dynamic SDN framework, a game-theoretic model is presented to analyze its security performance. This model can represent several kinds of players’ information, simulate approximate attack scenarios, and quantitatively estimate systems’ reliability. And we explore several typical game instances defined by system’s capability, players’ objects, and strategies. Experimental results illustrate that the system’s detection capability is not a decisive element to security enhancement as introduction of dynamism and redundancy into SDN can significantly improve security gain and compensate for its detection weakness. Moreover, we observe a range of common strategic actions across environmental conditions. And analysis reveals diverse defense mechanisms adopted in dynamic systems have different effect on security improvement. Besides, the existence of equilibrium in particular situations further proves the novel structure’s feasibility, flexibility, and its persistent ability against long-term attacks.

Evolutionary Dynamics of Tumor-Stroma Interactions in Multiple Myeloma.

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Javad Salimi Sartakhti

Full Text Available Cancer cells and stromal cells cooperate by exchanging diffusible factors that sustain tumor growth, a form of frequency-dependent selection that can be studied in the framework of evolutionary game theory. In the case of multiple myeloma, three types of cells (malignant plasma cells, osteoblasts and osteoclasts exchange growth factors with different effects, and tumor-stroma interactions have been analysed using a model of cooperation with pairwise interactions. Here we show that a model in which growth factors have autocrine and paracrine effects on multiple cells, a more realistic assumption for tumor-stroma interactions, leads to different results, with implications for disease progression and treatment. In particular, the model reveals that reducing the number of malignant plasma cells below a critical threshold can lead to their extinction and thus to restore a healthy balance between osteoclast and osteoblast, a result in line with current therapies against multiple myeloma.

The Evolutionary Dynamics of Biofuel Value Chains

DEFF Research Database (Denmark)

Ponte, Stefano

2014-01-01

In this paper I propose to push the frontier of global value chain (GVC) governance analysis through the concept of ‘polarity’. Much of the existing GVC literature has focused on ‘unipolar’ value chains, where one group of ‘lead firms’ inhabiting a specific function in a chain plays a dominant role...... in governing it. Some scholars have explored the dynamics of governance in GVCs characterized as ‘bipolar’, where two sets of actors in different functional positions both drive the chain. I expand this direction further to suggest conceptualizing governance within a continuum between unipolarity...... and multipolarity. Empirically, I do so by examining the evolutionary dynamics of governance in biofuel value chains, with specific focus on the key regulatory and institutional features that facilitated their emergence and expansion. First, I examine the formation, evolution, and governance of three national/regional...

Strategic interactions: Games of the Ju|'hoan.

Science.gov (United States)

de Voogt, Alex

2017-12-01

Three strategic games played by the Ju|'hoan-a board, a card, and a gesture game-complicate the rhetorics that suggest an evolutionary or psychological significance of play. They are mostly played by adults, although every individual adult does not necessarily engage in each game. The Ju|'hoan card and board game practices were transmitted through contact across large parts of Botswana and Namibia, while the gesture game n!àì has been known in other San communities. It suggests that the significance of strategic games is more likely found in its potential for social interaction (i.e., allowing to overcome cultural divides) than in evolution and psychology. Within the anthropological literature, strategy games were thought to be absent in egalitarian societies, such as that of the Ju|'hoan. Here, the roles of power, competition, and winning were thought to be disruptive and unwanted. A closer examination of the details behind the Ju|'hoan games shows that not only were strategy games adopted and adapted from neighboring societies but that the game of n!àì was developed by the Ju|'hoan into a competitive one. The evolutionary or psychological significance of play is informed by studies on individual play, children's play, and games with informal rules. When considering strategic games throughout history, it is their role of facilitator rather than the playing practice itself that makes games relevant across languages, cultural divides, and sociopolitical boundaries.

Attractive evolutionary equilibria

OpenAIRE

Roorda, Berend; Joosten, Reinoud

2011-01-01

We present attractiveness, a refinement criterion for evolutionary equilibria. Equilibria surviving this criterion are robust to small perturbations of the underlying payoff system or the dynamics at hand. Furthermore, certain attractive equilibria are equivalent to others for certain evolutionary dynamics. For instance, each attractive evolutionarily stable strategy is an attractive evolutionarily stable equilibrium for certain barycentric ray-projection dynamics, and vice versa.

Economics and Mathematical Theory of Games

OpenAIRE

Ajda Fosner

2012-01-01

The theory of games is a branch of applied mathematics that is used in economics, management, and other social sciences. Moreover, it is used also in military science, political science, international relations, computer science, evolutionary biology, and ecology. It is a field of mathematics in which games are studied. The aim of this article is to present matrix games and the game theory. After the introduction, we will explain the methodology and give some examples. We will show applicatio...

Direct sum matrix game with prisoner's dilemma and snowdrift game.

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Chengzhang Ma

Full Text Available A direct sum form is proposed for constructing a composite game from two 2 x 2 games, prisoner's dilemma and snowdrift game. This kind of direct sum form game is called a multiple roles game. The replicator dynamics of the multiple roles game with will-mixed populations is explored. The dynamical behaviors on square lattice are investigated by numerical simulation. It is found that the dynamical behaviors of population on square lattice depend on the mixing proportion of the two simple games. Mixing SD activities to pure PD population inhibits the proportion of cooperators in PD, and mixing PD activities to pure SD population stimulates the proportion of cooperators in SD. Besides spatial reciprocity, our results show that there are roles reciprocities between different types of individuals.

Promotion of cooperation induced by a self-questioning update rule in the spatial traveler's dilemma game

Science.gov (United States)

Miao, Qing; Wang, Juan; Hu, Meng-long; Zhang, Fan; Zhang, Qiu-shi; Xia, Cheng-yi

2014-01-01

In sociology and economics, evolutionary game theory has provided a powerful framework to illustrate the social dilemma's problems, and many evolutionary game models are presented, such as prisoner's dilemma game, snowdrift game, public goods game, and so on. In this paper, however, we focus on another typical pair-wise game model: Traveler's Dilemma Game (TDG), which has been deeply investigated in economics, but less attention has been paid to this topic within the physics community. We mainly discuss the influence of strategy update rules on the evolution of cooperation in the spatial TDG, and in detail explore the role of a novel self-questioning or self-learning update mechanism in the evolution of cooperation of the TDG model on the square lattice. In our self-questioning rule, each player does not imitate the strategy state of his or her nearest neighbors and simply plays the traveler's dilemma games twice with nearest neighbors: one is to calculate the actual payoff in the current game round; the other is to perform a virtual game which is used to obtain an intangible payoff if he or she adopts another random strategy. Then, the focal player decides to keep the current strategy or to change into that virtual strategy according to the Fermi-like dynamics. A great number of Monte Carlo simulations indicate that our self-questioning rule is a low information game decision-making mechanism which can greatly promote the evolution of cooperation for some specific conditions in the spatial TDG model. Furthermore, this novel rule can also be applied into the prisoner's dilemma game, and likewise the behavior of cooperation can be largely enhanced. Our results are of high importance to analyze and understand the emergence of cooperation within many real social and economical systems.

Evolutionary Design of Both Topologies and Parameters of a Hybrid Dynamical System

DEFF Research Database (Denmark)

Dupuis, Jean-Francois; Fan, Zhun; Goodman, Erik

2012-01-01

This paper investigates the issue of evolutionary design of open-ended plants for hybrid dynamical systems--i.e. both their topologies and parameters. Hybrid bond graphs are used to represent dynamical systems involving both continuous and discrete system dynamics. Genetic programming, with some...... of hybrid dynamical systems that fulfill predefined design specifications. A comprehensive investigation of a case study of DC-DC converter design demonstrates the feasibility and effectiveness of the HBGGP approach. Important characteristics of the approach are also discussed, with some future research...

Intention recognition, commitment and their roles in the evolution of cooperation from artificial intelligence techniques to evolutionary game theory models

CERN Document Server

Han, The Anh

2013-01-01

This original and timely monograph describes a unique self-contained excursion that reveals to the readers the roles of two basic cognitive abilities, i.e. intention recognition and arranging commitments, in the evolution of cooperative behavior. This book analyses intention recognition, an important ability that helps agents predict others’ behavior, in its artificial intelligence and evolutionary computational modeling aspects, and proposes a novel intention recognition method. Furthermore, the book presents a new framework for intention-based decision making and illustrates several ways in which an ability to recognize intentions of others can enhance a decision making process. By employing the new intention recognition method and the tools of evolutionary game theory, this book introduces computational models demonstrating that intention recognition promotes the emergence of cooperation within populations of self-regarding agents. Finally, the book describes how commitment provides a pathway to the evol...

Modeling and Generating Strategy Games Mechanics

DEFF Research Database (Denmark)

Mahlmann, Tobias

of the game is, how players may manipulate the game world, etc. We present the Strategy Games Description Language (SGDL), a tree-based approach to model the game mechanics of strategy games. SGDL allows game designers to rapid prototype their game ideas with the help of our customisable game engine. We...... their games to individual players’ preferences by creating game content adaptively to how the player plays (and likes) a game. W we extend the notion of “procedural game content generation” by “game mechanics”. Game mechanics herein refer to the way that objects in a game may interact, what the goal...... present several example games to demonstrate the capabilities of the language and how to model common strategy game elements. Furthermore, we present methods to procedurally generate and evaluate game mechanics modelled in SGDL in terms of enjoyability. We argue that an evolutionary process can be used...

Unexpected Nongenetic Individual Heterogeneity and Trait Covariance in Daphnia and Its Consequences for Ecological and Evolutionary Dynamics.

Science.gov (United States)

Cressler, Clayton E; Bengtson, Stefan; Nelson, William A

2017-07-01

Individual differences in genetics, age, or environment can cause tremendous differences in individual life-history traits. This individual heterogeneity generates demographic heterogeneity at the population level, which is predicted to have a strong impact on both ecological and evolutionary dynamics. However, we know surprisingly little about the sources of individual heterogeneity for particular taxa or how different sources scale up to impact ecological and evolutionary dynamics. Here we experimentally study the individual heterogeneity that emerges from both genetic and nongenetic sources in a species of freshwater zooplankton across a large gradient of food quality. Despite the tight control of environment, we still find that the variation from nongenetic sources is greater than that from genetic sources over a wide range of food quality and that this variation has strong positive covariance between growth and reproduction. We evaluate the general consequences of genetic and nongenetic covariance for ecological and evolutionary dynamics theoretically and find that increasing nongenetic variation slows evolution independent of the correlation in heritable life-history traits but that the impact on ecological dynamics depends on both nongenetic and genetic covariance. Our results demonstrate that variation in the relative magnitude of nongenetic versus genetic sources of variation impacts the predicted ecological and evolutionary dynamics.

Quantifying the Determinants of Evolutionary Dynamics Leading to Drug Resistance.

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Guillaume Chevereau

Full Text Available The emergence of drug resistant pathogens is a serious public health problem. It is a long-standing goal to predict rates of resistance evolution and design optimal treatment strategies accordingly. To this end, it is crucial to reveal the underlying causes of drug-specific differences in the evolutionary dynamics leading to resistance. However, it remains largely unknown why the rates of resistance evolution via spontaneous mutations and the diversity of mutational paths vary substantially between drugs. Here we comprehensively quantify the distribution of fitness effects (DFE of mutations, a key determinant of evolutionary dynamics, in the presence of eight antibiotics representing the main modes of action. Using precise high-throughput fitness measurements for genome-wide Escherichia coli gene deletion strains, we find that the width of the DFE varies dramatically between antibiotics and, contrary to conventional wisdom, for some drugs the DFE width is lower than in the absence of stress. We show that this previously underappreciated divergence in DFE width among antibiotics is largely caused by their distinct drug-specific dose-response characteristics. Unlike the DFE, the magnitude of the changes in tolerated drug concentration resulting from genome-wide mutations is similar for most drugs but exceptionally small for the antibiotic nitrofurantoin, i.e., mutations generally have considerably smaller resistance effects for nitrofurantoin than for other drugs. A population genetics model predicts that resistance evolution for drugs with this property is severely limited and confined to reproducible mutational paths. We tested this prediction in laboratory evolution experiments using the "morbidostat", a device for evolving bacteria in well-controlled drug environments. Nitrofurantoin resistance indeed evolved extremely slowly via reproducible mutations-an almost paradoxical behavior since this drug causes DNA damage and increases the mutation

Game Theory - Its Applications to Ethical Decision Making

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Cavagnetto Stefano

2014-01-01

Full Text Available The application of game theory according to Hargreaves-Heap and Varonfakis (1995 to understand human behaviour, and in particular ethical behaviour, is a valuable development, as game theory has gradually become one of the key frameworks to assist us in the understanding of social sciences. Esther (1982 and Aumann and Hart (1992 show that there are several studies that indicate the importance of a game theoretic framework in advancing our understanding of social behaviour and evolutionary sciences. Although the application of game theory in the above areas has largely been not formalised, its application in the fields of ethical conduct and human behaviour is at present developed in several respects with the gradual assistance of advances in related areas such as evolutionary biology and our understanding of group social behaviour.

Interplay between cooperation-enhancing mechanisms in evolutionary games with tag-mediated interactions

Science.gov (United States)

Hadzibeganovic, Tarik; Stauffer, Dietrich; Han, Xiao-Pu

2018-04-01

Cooperation is fundamental for the long-term survival of biological, social, and technological networks. Previously, mechanisms for the enhancement of cooperation, such as network reciprocity, have largely been studied in isolation and with often inconclusive findings. Here, we present an evolutionary, multiagent-based, and spatially explicit computer model to specifically address the interactive interplay between such mechanisms. We systematically investigate the effects of phenotypic diversity, network structure, and rewards on cooperative behavior emerging in a population of reproducing artificial decision makers playing tag-mediated evolutionary games. Cooperative interactions are rewarded such that both the benefits of recipients and costs of donators are affected by the reward size. The reward size is determined by the number of cooperative acts occurring within a given reward time frame. Our computational experiments reveal that small reward frames promote unconditional cooperation in populations with both low and high diversity, whereas large reward frames lead to cycles of conditional and unconditional strategies at high but not at low diversity. Moreover, an interaction between rewards and spatial structure shows that relative to small reward frames, there is a strong difference between the frequency of conditional cooperators populating rewired versus non-rewired networks when the reward frame is large. Notably, in a less diverse population, the total number of defections is comparable across different network topologies, whereas in more diverse environments defections become more frequent in a regularly structured than in a rewired, small-world network of contacts. Acknowledging the importance of such interaction effects in social dilemmas will have inevitable consequences for the future design of cooperation-enhancing protocols in large-scale, distributed, and decentralized systems such as peer-to-peer networks.

Cooperation guided by the coexistence of imitation dynamics and aspiration dynamics in structured populations

Science.gov (United States)

Xu, Kuangyi; Li, Kun; Cong, Rui; Wang, Long

2017-02-01

In the framework of the evolutionary game theory, two fundamentally different mechanisms, the imitation process and the aspiration-driven dynamics, can be adopted by players to update their strategies. In the former case, individuals imitate the strategy of a more successful peer, while in the latter case individuals change their strategies based on a comparison of payoffs they collect in the game to their own aspiration levels. Here we explore how cooperation evolves for the coexistence of these two dynamics. Intriguingly, cooperation reaches its lowest level when a certain moderate fraction of individuals pick aspiration-level-driven rule while the others choose pairwise comparison rule. Furthermore, when individuals can adjust their update rules besides their strategies, either imitation dynamics or aspiration-driven dynamics will finally take over the entire population, and the stationary cooperation level is determined by the outcome of competition between these two dynamics. We find that appropriate synergetic effects and moderate aspiration level boost the fixation probability of aspiration-driven dynamics most effectively. Our work may be helpful in understanding the cooperative behavior induced by the coexistence of imitation dynamics and aspiration dynamics in the society.

Structure coefficients and strategy selection in multiplayer games.

Science.gov (United States)

McAvoy, Alex; Hauert, Christoph

2016-01-01

Evolutionary processes based on two-player games such as the Prisoner's Dilemma or Snowdrift Game are abundant in evolutionary game theory. These processes, including those based on games with more than two strategies, have been studied extensively under the assumption that selection is weak. However, games involving more than two players have not received the same level of attention. To address this issue, and to relate two-player games to multiplayer games, we introduce a notion of reducibility for multiplayer games that captures what it means to break down a multiplayer game into a sequence of interactions with fewer players. We discuss the role of reducibility in structured populations, and we give examples of games that are irreducible in any population structure. Since the known conditions for strategy selection, otherwise known as [Formula: see text]-rules, have been established only for two-player games with multiple strategies and for multiplayer games with two strategies, we extend these rules to multiplayer games with many strategies to account for irreducible games that cannot be reduced to those simpler types of games. In particular, we show that the number of structure coefficients required for a symmetric game with [Formula: see text]-player interactions and [Formula: see text] strategies grows in [Formula: see text] like [Formula: see text]. Our results also cover a type of ecologically asymmetric game based on payoff values that are derived not only from the strategies of the players, but also from their spatial positions within the population.

Evolution of learned strategy choice in a frequency-dependent game.

Science.gov (United States)

Katsnelson, Edith; Motro, Uzi; Feldman, Marcus W; Lotem, Arnon

2012-03-22

In frequency-dependent games, strategy choice may be innate or learned. While experimental evidence in the producer-scrounger game suggests that learned strategy choice may be common, a recent theoretical analysis demonstrated that learning by only some individuals prevents learning from evolving in others. Here, however, we model learning explicitly, and demonstrate that learning can easily evolve in the whole population. We used an agent-based evolutionary simulation of the producer-scrounger game to test the success of two general learning rules for strategy choice. We found that learning was eventually acquired by all individuals under a sufficient degree of environmental fluctuation, and when players were phenotypically asymmetric. In the absence of sufficient environmental change or phenotypic asymmetries, the correct target for learning seems to be confounded by game dynamics, and innate strategy choice is likely to be fixed in the population. The results demonstrate that under biologically plausible conditions, learning can easily evolve in the whole population and that phenotypic asymmetry is important for the evolution of learned strategy choice, especially in a stable or mildly changing environment.

Dynamical instabilities in a simple minority game with discounting

International Nuclear Information System (INIS)

Challet, D; De Martino, A; Marsili, M

2008-01-01

We explore the effect of discounting and experimentation in a simple model of interacting adaptive agents. Agents belong to either of two types and each has to decide whether to participate in a game or not, the game being profitable when there is an excess of players of the other type. We find the emergence of large fluctuations as a result of the onset of a dynamical instability which may arise discontinuously (increasing the discount factor) or continuously (decreasing the experimentation rate). The phase diagram is characterized in detail and noise amplification close to a bifurcation point is identified as the physical mechanism behind the instability. (letter)

A Game-Theoretic Response Strategy for Coordinator Attack in Wireless Sensor Networks

Science.gov (United States)

Liu, Jianhua; Yue, Guangxue; Shang, Huiliang; Li, Hongjie

2014-01-01

The coordinator is a specific node that controls the whole network and has a significant impact on the performance in cooperative multihop ZigBee wireless sensor networks (ZWSNs). However, the malicious node attacks coordinator nodes in an effort to waste the resources and disrupt the operation of the network. Attacking leads to a failure of one round of communication between the source nodes and destination nodes. Coordinator selection is a technique that can considerably defend against attack and reduce the data delivery delay, and increase network performance of cooperative communications. In this paper, we propose an adaptive coordinator selection algorithm using game and fuzzy logic aiming at both minimizing the average number of hops and maximizing network lifetime. The proposed game model consists of two interrelated formulations: a stochastic game for dynamic defense and a best response policy using evolutionary game formulation for coordinator selection. The stable equilibrium best policy to response defense is obtained from this game model. It is shown that the proposed scheme can improve reliability and save energy during the network lifetime with respect to security. PMID:25105171

Dynamic Stackelberg game model for water rationalization in drought emergency

Science.gov (United States)

Kicsiny, R.; Piscopo, V.; Scarelli, A.; Varga, Z.

2014-09-01

In water resource management, in case of a limited resource, there is a conflict situation between different consumers. In this paper, a dynamic game-theoretical model is suggested for the solution of such conflict. Let us suppose that in a region, water supply is based on a given aquifer, from which a quantity of effective reserve can be used without damaging the aquifer, and a long drought is foreseen. The use of water is divided between the social sector represented by the local authority, and the production sector, in our case, simplified to a single agricultural producer using water for irrigation; they are the players in the game. For a fixed time period, every day, a given amount is available, from which first the authority, then the producer takes a proportion, which corresponds to the strategy choices of the players. A price function is given, which depends on the total available reserve, the payoffs of both players are quantified as their net incomes for the whole period: for the producer: profit from selling the product minus price of water and tax paid, for the authority: tax received plus the gain for the authority from selling the water bought to the social sector minus price of water purchased. A solution (equilibrium) of the game consists of such strategy choices of both players, with which each player maximizes her/his total payoff (over the whole time horizon of the game) provided that the other player also maximizes her/his own payoff. In the paper, in a mathematical model for the above conflict situation, a deterministic continuum-strategy two-player discrete-time dynamic Stackelberg game with fixed finite time duration and closed-loop information structure is proposed, where the authority is “leader” and the producer is “follower”. The algorithms for the solution of the game are based on recent theoretical results of the authors. Illustrative numerical examples are also given.

Coevolution of game and network structure with adjustable linking

Science.gov (United States)

Qin, Shao-Meng; Zhang, Guo-Yong; Chen, Yong

2009-12-01

Most papers about the evolutionary game on graph assume the statistic network structure. However, in the real world, social interaction could change the relationship among people. And the change of social structure will also affect people’s strategies. We build a coevolution model of prisoner’s dilemma game and network structure to study the dynamic interaction in the real world. Differing from other coevolution models, players rewire their network connections according to the density of cooperation and other players’ payoffs. We use a parameter α to control the effect of payoff in the process of rewiring. Based on the asynchronous update rule and Monte Carlo simulation, we find that, when players prefer to rewire their links to those who are richer, the temptation can increase the cooperation density.

A Dynamic Stackelberg Game of Supply Chain for a Corporate Social Responsibility

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Massimiliano Ferrara

2017-01-01

Full Text Available In this paper, we establish a dynamic game to allocate CSR (Corporate Social Responsibility to the members of a supply chain. We propose a model of a supply chain in a decentralized state which includes a supplier and a manufacturer. For analyzing supply chain performance in decentralized state and the relationships between the members of the supply chain, we formulate a model that crosses through multiperiods with the help of a dynamic discrete Stackelberg game which is made under two different information structures. We obtain an equilibrium point at which both the profits of members and the level of CSR taken up by supply chains are maximized.

Experiential Learning in Vehicle Dynamics Education via Motion Simulation and Interactive Gaming

OpenAIRE

Hulme, Kevin; Kasprzak, Edward; English, Ken; Moore-Russo, Deborah; Lewis, Kemper

2009-01-01

Creating active, student-centered learning situations in postsecondary education is an ongoing challenge for engineering educators. Contemporary students familiar with visually engaging and fast-paced games can find traditional classroom methods of lecture and guided laboratory experiments limiting. This paper presents a methodology that incorporates driving simulation, motion simulation, and educational practices into an engaging, gaming-inspired simulation framework for a vehicle dynamics c...

Application of network methods for understanding evolutionary dynamics in discrete habitats.

Science.gov (United States)

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

Optimizing Visual Properties of Game Content through Neuroevolution

DEFF Research Database (Denmark)

Liapis, Antonios; Yannakakis, Georgios N.; Togelius, Julian

This paper presents a search-based approach to generating game content that satisfies both gameplay requirements and user-expressed aesthetic criteria. Using evolutionary constraint satisfaction, we search for spaceships (for a space combat game) represented as compositional pattern...

Online Evolution for Multi-Action Adversarial Games

OpenAIRE

Justesen, Niels; Mahlmann, Tobias; Togelius, Julian

2016-01-01

We present Online Evolution, a novel method for playing turn-based multi-action adversarial games. Such games, which include most strategy games, have extremely high branching factors due to each turn having multiple actions. In Online Evolution, an evolutionary algorithm is used to evolve the combination of atomic actions that make up a single move, with a state evaluation function used for fitness. We implement Online Evolution for the turn-based multi-action game Hero Academy and compare i...

Spatial snowdrift game in heterogeneous agent systems with co-evolutionary strategies and updating rules

International Nuclear Information System (INIS)

Xia Hai-Jiang; Li Ping-Ping; Ke Jian-Hong; Lin Zhen-Quan

2015-01-01

We propose an evolutionary snowdrift game model for heterogeneous systems with two types of agents, in which the inner-directed agents adopt the memory-based updating rule while the copycat-like ones take the unconditional imitation rule; moreover, each agent can change his type to adopt another updating rule once the number he sequentially loses the game at is beyond his upper limit of tolerance. The cooperative behaviors of such heterogeneous systems are then investigated by Monte Carlo simulations. The numerical results show the equilibrium cooperation frequency and composition as functions of the cost-to-benefit ratio r are both of plateau structures with discontinuous steplike jumps, and the number of plateaux varies non-monotonically with the upper limit of tolerance ν T as well as the initial composition of agents f a0 . Besides, the quantities of the cooperation frequency and composition are dependent crucially on the system parameters including ν T , f a0 , and r. One intriguing observation is that when the upper limit of tolerance is small, the cooperation frequency will be abnormally enhanced with the increase of the cost-to-benefit ratio in the range of 0 < r < 1/4. We then probe into the relative cooperation frequencies of either type of agents, which are also of plateau structures dependent on the system parameters. Our results may be helpful to understand the cooperative behaviors of heterogenous agent systems. (paper)

How can we model selectively neutral density dependence in evolutionary games.

Science.gov (United States)

Argasinski, Krzysztof; Kozłowski, Jan

2008-03-01

The problem of density dependence appears in all approaches to the modelling of population dynamics. It is pertinent to classic models (i.e., Lotka-Volterra's), and also population genetics and game theoretical models related to the replicator dynamics. There is no density dependence in the classic formulation of replicator dynamics, which means that population size may grow to infinity. Therefore the question arises: How is unlimited population growth suppressed in frequency-dependent models? Two categories of solutions can be found in the literature. In the first, replicator dynamics is independent of background fitness. In the second type of solution, a multiplicative suppression coefficient is used, as in a logistic equation. Both approaches have disadvantages. The first one is incompatible with the methods of life history theory and basic probabilistic intuitions. The logistic type of suppression of per capita growth rate stops trajectories of selection when population size reaches the maximal value (carrying capacity); hence this method does not satisfy selective neutrality. To overcome these difficulties, we must explicitly consider turn-over of individuals dependent on mortality rate. This new approach leads to two interesting predictions. First, the equilibrium value of population size is lower than carrying capacity and depends on the mortality rate. Second, although the phase portrait of selection trajectories is the same as in density-independent replicator dynamics, pace of selection slows down when population size approaches equilibrium, and then remains constant and dependent on the rate of turn-over of individuals.

Promotion of cooperation induced by discriminators in the spatial multi-player donor-recipient game

Science.gov (United States)

Cui, Guang-Hai; Wang, Zhen; Ren, Jian-Kang; Lu, Kun; Li, Ming-Chu

2016-11-01

Although the two-player donor-recipient game has been used extensively in studying cooperation in social dilemmas, the scenario in which a donor can simultaneously donate resources to multiple recipients is also common in human societies, economic systems, and social networks. This paper formulates a model of the multi-player donor-recipient game considering a multi-recipient scenario. The promotion of cooperation is also studied by introducing a discriminative cooperation strategy into the game, which donates resources to recipients in proportion to their previous donations with a cost for the collection of information. The evolutionary dynamics of individual strategies are explored in homogeneous and heterogeneous scenarios by leveraging spatial evolutionary game theory. The results show that in a homogeneous scenario, defectors can dominate the network at the equilibrium state only when the cost-to-benefit ratio (R) of donated resources is large. In a heterogeneous scenario, three strategies can coexist all the time within the range of R that was studied, and the promotion of cooperation is more effective when the values of R are smaller. Results from a single node evolution and the formation of local patterns of interaction are provided, and it is analytically shown that discriminators can maintain fairness in resource donation and guarantee long-term cooperation when R is not too large.

Game Theory of Tumor–Stroma Interactions in Multiple Myeloma: Effect of Nonlinear Benefits

Directory of Open Access Journals (Sweden)

Javad Salimi Sartakhti

2018-05-01

Full Text Available Cancer cells and stromal cells often exchange growth factors with paracrine effects that promote cell growth: a form of cooperation that can be studied by evolutionary game theory. Previous models have assumed that interactions between cells are pairwise or that the benefit of a growth factor is a linear function of its concentration. Diffusible factors, however, affect multiple cells and generally have nonlinear effects, and these differences are known to have important consequences for evolutionary dynamics. Here, we study tumor–stroma paracrine signaling using a model with multiplayer collective interactions in which growth factors have nonlinear effects. We use multiple myeloma as an example, modelling interactions between malignant plasma cells, osteoblasts, and osteoclasts. Nonlinear benefits can lead to results not observed in linear models, including internal mixed stable equilibria and cyclical dynamics. Models with linear effects, therefore, do not lead to a meaningful characterization of the dynamics of tumor–stroma interactions. To understand the dynamics and the effect of therapies it is necessary to estimate the shape of the benefit functions experimentally and parametrize models based on these functions.

EDEN: evolutionary dynamics within environments

Science.gov (United States)

Münch, Philipp C.; Stecher, Bärbel; McHardy, Alice C.

2017-01-01

Abstract Summary Metagenomics revolutionized the field of microbial ecology, giving access to Gb-sized datasets of microbial communities under natural conditions. This enables fine-grained analyses of the functions of community members, studies of their association with phenotypes and environments, as well as of their microevolution and adaptation to changing environmental conditions. However, phylogenetic methods for studying adaptation and evolutionary dynamics are not able to cope with big data. EDEN is the first software for the rapid detection of protein families and regions under positive selection, as well as their associated biological processes, from meta- and pangenome data. It provides an interactive result visualization for detailed comparative analyses. Availability and implementation EDEN is available as a Docker installation under the GPL 3.0 license, allowing its use on common operating systems, at http://www.github.com/hzi-bifo/eden. Contact alice.mchardy@helmholtz-hzi.de Supplementary information Supplementary data are available at Bioinformatics online. PMID:28637301

Risk-Averse Evolutionary Game Model of Aviation Joint Emergency Response

Directory of Open Access Journals (Sweden)

Wei Pan

2016-01-01

Full Text Available We study effects of risk-averse attitude of both participators in aviation joint emergency response on the coevolution of cooperation mechanisms and individual preferences between airport and nonprofit organization. First, based on the current aviation joint emergency mechanism in China, we put forward two mechanisms to select the joint nonprofit organization, including reputation cooperation and bidding competition. Meanwhile, we consider two preferences including altruism and selfishness. Then we build replicator dynamics equations using the theory of conditional value-at-risk (CVaR taking risk aversion attitude into account. Finally, we introduce the factor of government and give all participators some suggestions. We show that the risk-averse attitude of the other game participator affects the one participator’s decision and the effects subject to some parameters.

Engagement and EMG in serious gaming : Experimenting with sound and dynamics in the levee patroller training game

NARCIS (Netherlands)

Schuurink, E.L.; Houtkamp, J.; Toet, A.

2008-01-01

We measured the effects of sound and visual dynamic elements on user experience of a serious game, with special interest in engagement and arousal. Engagement was measured through questionnaires and arousal through the SAM and electromyography (EMG). We adopted the EMG of the corrugator (frown

Mean-field games with logistic population dynamics

KAUST Repository

Gomes, Diogo A.; De Lima Ribeiro, Ricardo

2013-01-01

In its standard form, a mean-field game can be defined by coupled system of equations, a Hamilton-Jacobi equation for the value function of agents and a Fokker-Planck equation for the density of agents. Traditionally, the latter equation is adjoint to the linearization of the former. Since the Fokker-Planck equation models a population dynamic, we introduce natural features such as seeding and birth, and nonlinear death rates. In this paper we analyze a stationary meanfield game in one dimension, illustrating various techniques to obtain regularity of solutions in this class of systems. In particular we consider a logistic-type model for birth and death of the agents which is natural in problems where crowding affects the death rate of the agents. The introduction of these new terms requires a number of new ideas to obtain wellposedness. In a forthcoming publication we will address higher dimensional models. ©2013 IEEE.

Mean-field games with logistic population dynamics

KAUST Repository

Gomes, Diogo A.

2013-12-01

In its standard form, a mean-field game can be defined by coupled system of equations, a Hamilton-Jacobi equation for the value function of agents and a Fokker-Planck equation for the density of agents. Traditionally, the latter equation is adjoint to the linearization of the former. Since the Fokker-Planck equation models a population dynamic, we introduce natural features such as seeding and birth, and nonlinear death rates. In this paper we analyze a stationary meanfield game in one dimension, illustrating various techniques to obtain regularity of solutions in this class of systems. In particular we consider a logistic-type model for birth and death of the agents which is natural in problems where crowding affects the death rate of the agents. The introduction of these new terms requires a number of new ideas to obtain wellposedness. In a forthcoming publication we will address higher dimensional models. ©2013 IEEE.

Falsification of matching theory and confirmation of an evolutionary theory of behavior dynamics in a critical experiment.

Science.gov (United States)

McDowell, J J; Calvin, Olivia L; Hackett, Ryan; Klapes, Bryan

2017-07-01

Two competing predictions of matching theory and an evolutionary theory of behavior dynamics, and one additional prediction of the evolutionary theory, were tested in a critical experiment in which human participants worked on concurrent schedules for money (Dallery et al., 2005). The three predictions concerned the descriptive adequacy of matching theory equations, and of equations describing emergent equilibria of the evolutionary theory. Tests of the predictions falsified matching theory and supported the evolutionary theory. Copyright © 2017 Elsevier B.V. All rights reserved.

The influence of deterministic and stochastic waiting time for triggering mortality and colonization events on the coexistence of cooperators and defectors in an evolutionary game model

Directory of Open Access Journals (Sweden)

YouHua Chen

2014-06-01

waiting time, both defectors and cooperators could coexist, regardless of the types of waiting time for colonization events. Defense (or cooperation rewards could determine the persistence time of both game players. When the defense reward is low, cooperators could persist better in the simulation. But when the defense reward becomes sufficiently higher, defectors would persist better. Overall, non-coexistence of cooperators and defectors in the present evolutionary game model is dependent on the stochastic mortality events, but not colonization events. In conclusion, my present study quantifies the influence of the temporally fluctuating motility-colonization dynamic on modeling the coexistence of species in the spatial evolutionary game.

Zero-determinant strategy: An underway revolution in game theory

International Nuclear Information System (INIS)

Hao Dong; Rong Zhi-Hai; Zhou Tao

2014-01-01

Repeated games describe situations where players interact with each other in a dynamic pattern and make decisions according to outcomes of previous stage games. Very recently, Press and Dyson have revealed a new class of zero-determinant (ZD) strategies for the repeated games, which can enforce a fixed linear relationship between expected payoffs of two players, indicating that a smart player can control her unwitting co-player's payoff in a unilateral way [Proc. Acad. Natl. Sci. USA 109, 10409 (2012)]. The theory of ZD strategies provides a novel viewpoint to depict interactions among players, and fundamentally changes the research paradigm of game theory. In this brief survey, we first introduce the mathematical framework of ZD strategies, and review the properties and constrains of two specifications of ZD strategies, called pinning strategies and extortion strategies. Then we review some representative research progresses, including robustness analysis, cooperative ZD strategy analysis, and evolutionary stability analysis. Finally, we discuss some significant extensions to ZD strategies, including the multi-player ZD strategies, and ZD strategies under noise. Challenges in related research fields are also listed. (topical review - statistical physics and complex systems)

Effects of Some Topological Ingredients on the Evolutionary Ultimatum Game

International Nuclear Information System (INIS)

Deng Lili; Zhang Jianxiong; Tang Wansheng; Zhang Wei

2012-01-01

This study aims at figuring out the crucial topological ingredients which affect the outcomes of the ultimatum game located on different networks, encompassing the regular network, the random network, the small-world network, and the scale-free network. With the aid of random interchanging algorithm, we investigate the relations between the outcomes of the ultimatum game and some topological ingredients, including the average range, the clustering coefficient and the heterogeneity, and so forth. It is found that for the regular, random and small-work networks, the average range and the clustering coefficient have evident impacts on the ultimatum game, while for the scale-free network, the original degree heterogeneity and the underlying rich-club characterizations are the mainly important topological ingredients that influence the outcomes of ultimatum game substantially.

Pseudorandom numbers: evolutionary models in image processing, biology, and nonlinear dynamic systems

Science.gov (United States)

Yaroslavsky, Leonid P.

1996-11-01

We show that one can treat pseudo-random generators, evolutionary models of texture images, iterative local adaptive filters for image restoration and enhancement and growth models in biology and material sciences in a unified way as special cases of dynamic systems with a nonlinear feedback.

The co-evolutionary dynamics of directed network of spin market agents

Science.gov (United States)

Horváth, Denis; Kuscsik, Zoltán; Gmitra, Martin

2006-09-01

The spin market model [S. Bornholdt, Int. J. Mod. Phys. C 12 (2001) 667] is generalized by employing co-evolutionary principles, where strategies of the interacting and competitive traders are represented by local and global couplings between the nodes of dynamic directed stochastic network. The co-evolutionary principles are applied in the frame of Bak-Sneppen self-organized dynamics [P. Bak, K. Sneppen, Phys. Rev. Lett. 71 (1993) 4083] that includes the processes of selection and extinction actuated by the local (node) fitness. The local fitness is related to orientation of spin agent with respect to the instant magnetization. The stationary regime is formed due to the interplay of self-organization and adaptivity effects. The fat tailed distributions of log-price returns are identified numerically. The non-trivial model consequence is the evidence of the long time market memory indicated by the power-law range of the autocorrelation function of volatility with exponent smaller than one. The simulations yield network topology with broad-scale node degree distribution characterized by the range of exponents 1.3social networks.

Natural games

International Nuclear Information System (INIS)

Anttila, Jani; Annila, Arto

2011-01-01

A course of a game is formulated as a physical process that will consume free energy in the least time. Accordingly, the rate of entropy increase is the payoff function that will subsume all forms of free energy that motivate diverse decisions. Also other concepts of game theory are related to their profound physical counterparts. When the physical portrayal of behavior is mathematically analyzed, the course of a game is found to be inherently unpredictable because each move affects motives in the future. Despite the non-holonomic character of the natural process, the objective of consuming free energy in the least time will direct an extensive-form game toward a Lyapunov-stable point that satisfies the minimax theorem. -- Highlights: → Behavior in the context of game theory is described as a natural process. → The rate of entropy increase, derived from statistical physics of open systems, is identified as the payoff function. → Entropy as the payoff function also clarifies motives of collaboration and subjective nature of decision making. → Evolutionary equation of motion that accounts for the course of a game is inherently unpredictable.

Dynamic Lighting for Tension in Games

OpenAIRE

Seif El-Nasr, Magy; Niedenthal, Simon; Kenz, Igor; Almeida, Priya; Zupko, Joseph

2006-01-01

Video and computer games are among the most complex forms of interactive media. Games simulate many elements of traditional media, such as plot, characters, sound and music, lighting and mise-en-scene. However, games are digital artifacts played through graphic interfaces and controllers. As interactive experiences, games are a host of player challenges ranging from more deliberate decision-making and problem solving strategies, to the immediate charge of reflex action. Games, thus, draw upon...

Game Studies

NARCIS (Netherlands)

Raessens, J.F.F.

2016-01-01

This entry describes game studies as a dynamic interdisciplinary field of academic study and research that focuses on digital games and play in a wide variety of social and cultural contexts. It examines the history of game studies from its prehistory, when games were looked at as part of other

The state of the art in static and dynamic games

NARCIS (Netherlands)

De Giovanni, P.

2009-01-01

Purpose - The purpose of this paper is to investigate the state of the art in static and dynamic games (or inter-firm relationships). This research area has changed significantly over the last 25 years through the development of phenomena such as the supply chain and the progressive overcoming of

Ancient Origin of the Tryptophan Operon and the Dynamics of Evolutionary Change†

Science.gov (United States)

Xie, Gary; Keyhani, Nemat O.; Bonner; Jensen, Roy A.

2003-01-01

The seven conserved enzymatic domains required for tryptophan (Trp) biosynthesis are encoded in seven genetic regions that are organized differently (whole-pathway operons, multiple partial-pathway operons, and dispersed genes) in prokaryotes. A comparative bioinformatics evaluation of the conservation and organization of the genes of Trp biosynthesis in prokaryotic operons should serve as an excellent model for assessing the feasibility of predicting the evolutionary histories of genes and operons associated with other biochemical pathways. These comparisons should provide a better understanding of possible explanations for differences in operon organization in different organisms at a genomics level. These analyses may also permit identification of some of the prevailing forces that dictated specific gene rearrangements during the course of evolution. Operons concerned with Trp biosynthesis in prokaryotes have been in a dynamic state of flux. Analysis of closely related organisms among the Bacteria at various phylogenetic nodes reveals many examples of operon scission, gene dispersal, gene fusion, gene scrambling, and gene loss from which the direction of evolutionary events can be deduced. Two milestone evolutionary events have been mapped to the 16S rRNA tree of Bacteria, one splitting the operon in two, and the other rejoining it by gene fusion. The Archaea, though less resolved due to a lesser genome representation, appear to exhibit more gene scrambling than the Bacteria. The trp operon appears to have been an ancient innovation; it was already present in the common ancestor of Bacteria and Archaea. Although the operon has been subjected, even in recent times, to dynamic changes in gene rearrangement, the ancestral gene order can be deduced with confidence. The evolutionary history of the genes of the pathway is discernible in rough outline as a vertical line of descent, with events of lateral gene transfer or paralogy enriching the analysis as interesting

Ancient origin of the tryptophan operon and the dynamics of evolutionary change.

Science.gov (United States)

Xie, Gary; Keyhani, Nemat O; Bonner, Carol A; Jensen, Roy A

2003-09-01

The seven conserved enzymatic domains required for tryptophan (Trp) biosynthesis are encoded in seven genetic regions that are organized differently (whole-pathway operons, multiple partial-pathway operons, and dispersed genes) in prokaryotes. A comparative bioinformatics evaluation of the conservation and organization of the genes of Trp biosynthesis in prokaryotic operons should serve as an excellent model for assessing the feasibility of predicting the evolutionary histories of genes and operons associated with other biochemical pathways. These comparisons should provide a better understanding of possible explanations for differences in operon organization in different organisms at a genomics level. These analyses may also permit identification of some of the prevailing forces that dictated specific gene rearrangements during the course of evolution. Operons concerned with Trp biosynthesis in prokaryotes have been in a dynamic state of flux. Analysis of closely related organisms among the Bacteria at various phylogenetic nodes reveals many examples of operon scission, gene dispersal, gene fusion, gene scrambling, and gene loss from which the direction of evolutionary events can be deduced. Two milestone evolutionary events have been mapped to the 16S rRNA tree of Bacteria, one splitting the operon in two, and the other rejoining it by gene fusion. The Archaea, though less resolved due to a lesser genome representation, appear to exhibit more gene scrambling than the Bacteria. The trp operon appears to have been an ancient innovation; it was already present in the common ancestor of Bacteria and Archaea. Although the operon has been subjected, even in recent times, to dynamic changes in gene rearrangement, the ancestral gene order can be deduced with confidence. The evolutionary history of the genes of the pathway is discernible in rough outline as a vertical line of descent, with events of lateral gene transfer or paralogy enriching the analysis as interesting

Adaptive game AI with dynamic scripting

NARCIS (Netherlands)

Spronck, P.; Ponsen, M.J.V.; Sprinkhuizen-Kuyper, I.G.; Postma, E.O.

2006-01-01

Online learning in commercial computer games allows computer-controlled opponents to adapt to the way the game is being played. As such it provides a mechanism to deal with weaknesses in the game AI, and to respond to changes in human player tactics.We argue that online learning of game AI should

Weight of fitness deviation governs strict physical chaos in replicator dynamics

Science.gov (United States)

Pandit, Varun; Mukhopadhyay, Archan; Chakraborty, Sagar

2018-03-01

Replicator equation—a paradigm equation in evolutionary game dynamics—mathematizes the frequency dependent selection of competing strategies vying to enhance their fitness (quantified by the average payoffs) with respect to the average fitnesses of the evolving population under consideration. In this paper, we deal with two discrete versions of the replicator equation employed to study evolution in a population where any two players' interaction is modelled by a two-strategy symmetric normal-form game. There are twelve distinct classes of such games, each typified by a particular ordinal relationship among the elements of the corresponding payoff matrix. Here, we find the sufficient conditions for the existence of asymptotic solutions of the replicator equations such that the solutions—fixed points, periodic orbits, and chaotic trajectories—are all strictly physical, meaning that the frequency of any strategy lies inside the closed interval zero to one at all times. Thus, we elaborate on which of the twelve types of games are capable of showing meaningful physical solutions and for which of the two types of replicator equation. Subsequently, we introduce the concept of the weight of fitness deviation that is the scaling factor in a positive affine transformation connecting two payoff matrices such that the corresponding one-shot games have exactly same Nash equilibria and evolutionary stable states. The weight also quantifies how much the excess of fitness of a strategy over the average fitness of the population affects the per capita change in the frequency of the strategy. Intriguingly, the weight's variation is capable of making the Nash equilibria and the evolutionary stable states, useless by introducing strict physical chaos in the replicator dynamics based on the normal-form game.

Discrete Control Processes, Dynamic Games and Multicriterion Control Problems

Directory of Open Access Journals (Sweden)

Dumitru Lozovanu

2002-07-01

Full Text Available The discrete control processes with state evaluation in time of dynamical system is considered. A general model of control problems with integral-time cost criterion by a trajectory is studied and a general scheme for solving such classes of problems is proposed. In addition the game-theoretical and multicriterion models for control problems are formulated and studied.

Recovery after mass extinction: evolutionary assembly in large-scale biosphere dynamics.

Science.gov (United States)

Solé, Ricard V; Montoya, José M; Erwin, Douglas H

2002-01-01

Biotic recoveries following mass extinctions are characterized by a process in which whole ecologies are reconstructed from low-diversity systems, often characterized by opportunistic groups. The recovery process provides an unexpected window to ecosystem dynamics. In many aspects, recovery is very similar to ecological succession, but important differences are also apparently linked to the innovative patterns of niche construction observed in the fossil record. In this paper, we analyse the similarities and differences between ecological succession and evolutionary recovery to provide a preliminary ecological theory of recoveries. A simple evolutionary model with three trophic levels is presented, and its properties (closely resembling those observed in the fossil record) are compared with characteristic patterns of ecological response to disturbances in continuous models of three-level ecosystems. PMID:12079530

Cooperation in two-dimensional mixed-games

International Nuclear Information System (INIS)

Amaral, Marco A; Silva, Jafferson K L da; Wardil, Lucas

2015-01-01

Evolutionary game theory is a common framework to study the evolution of cooperation, where it is usually assumed that the same game is played in all interactions. Here, we investigate a model where the game that is played by two individuals is uniformly drawn from a sample of two different games. Using the master equation approach we show that the random mixture of two games is equivalent to play the average game when (i) the strategies are statistically independent of the game distribution and (ii) the transition rates are linear functions of the payoffs. We also use Monte-Carlo simulations in a two-dimensional lattice and mean-field techniques to investigate the scenario when the two above conditions do not hold. We find that even outside of such conditions, several quantities characterizing the mixed-games are still the same as the ones obtained in the average game when the two games are not very different. (paper)

Evolution of fairness and coalition formation in three-person ultimatum games.

Science.gov (United States)

Nishimura, Takeshi; Okada, Akira; Shirata, Yasuhiro

2017-05-07

We consider the evolution of fairness and coalition formation in a three-person ultimatum game in which the coalition value depends on its size. Traditional game theory, which assumes selfish and rational players, predicts the largest and efficient coalition with a proposer exploiting most of the total value. In a stochastic evolutionary model (the frequency-dependent Moran process with mutations) where players make errors in estimating the payoffs and strategies of others, evolutionary selection favors the formation of a two-person subcoalition under weak selection and in the low mutation limit if and only if its coalition value exceeds a high proportion (0.7) of that of the largest coalition. Proposers offer 30-35% of the subcoalition value to a coalition member, excluding a non-member. Multilateral bargaining is critically different from the bilateral one. Coalition-forming behavior may cause economic inefficiency and social exclusion. Stochastic evolutionary game theory thus provides theoretical support to explain the behavior of human subjects in economic experiments of a three-person ultimatum game. Copyright © 2017 Elsevier Ltd. All rights reserved.

FCJ-199 Modelling Systemic Racism: Mobilising the Dynamics of Race and Games in Everyday Racism

Directory of Open Access Journals (Sweden)

Robbie Fordyce

2016-03-01

Full Text Available This article is concerned with attempts to pose videogames as solutions to systemic racism. The mobile app, Everyday Racism, is one such game. Its method is to directly address players as subjects of racism interpellating them as victims of racist language and behaviour within Australian society, implicating the impact of racism on mental health and wellbeing. While the game has politically laudable goals, its effectiveness is undermined by several issues themselves attributable to the dynamics of race and games. This paper will spell out those issues by addressing three separate facets of the game: the problematic relationship between the player and their elected avatar; the pedagogic compromises that are made in modelling racism as a game; finally, the superliminal narrative that attempts to transcend the limited diegetic world of the game.

Dynamic Game Behavior of Retailers Considering the Quality of Substitute Products Based on Delay Decision

Science.gov (United States)

Bao, Binshuo; Ma, Junhai

2017-12-01

Motivated by the Silk Road Economic Belt and the 21st-Century Maritime Silk Road project, i.e. the Belt and Road (B&R), more goods will flow around the world. With this trading platform, people can buy products at relatively cheap prices, and it is easier for people to buy various goods. The quality and quantity of products thus attract more and more attention in the supply chains. This paper discusses the quantity decision by considering the product quality in parallel supply chains where two manufacturers produce substitute products and then sell them to their downstream retailers separately. In terms of the changing quantity, as well as the different quality, this paper establishes a dynamic game model to explore the dynamic behavior when the optimal profits of two retailers have been calculated. The dynamic behaviors of the system, such as stable region, bifurcation and chaos, strange attractors and the largest Lyapunov exponents (LLE) are analyzed. The effect of the quantity adjustment parameter on the stability of the supply chain system is investigated through numerical simulations. Furthermore, a dynamic game model is established based on the quality delay decision, to investigate the influence of the quality delay parameter on the dynamic game model and the profits. Finally, the optimal decisions are obtained and analyzed.

Cooperation among cancer cells as public goods games on Voronoi networks.

Science.gov (United States)

Archetti, Marco

2016-05-07

Cancer cells produce growth factors that diffuse and sustain tumour proliferation, a form of cooperation that can be studied using mathematical models of public goods in the framework of evolutionary game theory. Cell populations, however, form heterogeneous networks that cannot be described by regular lattices or scale-free networks, the types of graphs generally used in the study of cooperation. To describe the dynamics of growth factor production in populations of cancer cells, I study public goods games on Voronoi networks, using a range of non-linear benefits that account for the known properties of growth factors, and different types of diffusion gradients. The results are surprisingly similar to those obtained on regular graphs and different from results on scale-free networks, revealing that network heterogeneity per se does not promote cooperation when public goods diffuse beyond one-step neighbours. The exact shape of the diffusion gradient is not crucial, however, whereas the type of non-linear benefit is an essential determinant of the dynamics. Public goods games on Voronoi networks can shed light on intra-tumour heterogeneity, the evolution of resistance to therapies that target growth factors, and new types of cell therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Attractive evolutionary equilibria

NARCIS (Netherlands)

Joosten, Reinoud A.M.G.; Roorda, Berend

2011-01-01

We present attractiveness, a refinement criterion for evolutionary equilibria. Equilibria surviving this criterion are robust to small perturbations of the underlying payoff system or the dynamics at hand. Furthermore, certain attractive equilibria are equivalent to others for certain evolutionary

Epigenetic battle of the sexes. Comment on: ;Epigenetic game theory: How to compute the epigenetic control of maternal-to-zygotic transition; by Qian Wang et al.

Science.gov (United States)

Wu, Song

2017-03-01

Qian Wang et al. present an interesting framework, named epigenetic game theory, for modeling sex-based epigenetic dynamics during embryogenesis from a new viewpoint of evolutionary game theory [1]. That is, epigenomes of sperms and oocytes may coordinate through either cooperation or competition, or both, to affect the fitness of embryos. The work uses a set of ordinary differential equations (ODEs) to describe longitudinal trajectories of DNA methylation levels in both parental and maternal gametes and their dependence on each other. The insights gained from this review, i.e. dynamic methylation profiles and their interaction are potentially important to many fields, such as biomedicine and agriculture.

Differential Neural Networks for Identification and Filtering in Nonlinear Dynamic Games

Directory of Open Access Journals (Sweden)

Emmanuel García

2014-01-01

Full Text Available This paper deals with the problem of identifying and filtering a class of continuous-time nonlinear dynamic games (nonlinear differential games subject to additive and undesired deterministic perturbations. Moreover, the mathematical model of this class is completely unknown with the exception of the control actions of each player, and even though the deterministic noises are known, their power (or their effect is not. Therefore, two differential neural networks are designed in order to obtain a feedback (perfect state information pattern for the mentioned class of games. In this way, the stability conditions for two state identification errors and for a filtering error are established, the upper bounds of these errors are obtained, and two new learning laws for each neural network are suggested. Finally, an illustrating example shows the applicability of this approach.

Pattern formation, social forces, and diffusion instability in games with success-driven motion

Science.gov (United States)

Helbing, Dirk

2009-02-01

A local agglomeration of cooperators can support the survival or spreading of cooperation, even when cooperation is predicted to die out according to the replicator equation, which is often used in evolutionary game theory to study the spreading and disappearance of strategies. In this paper, it is shown that success-driven motion can trigger such local agglomeration and may, therefore, be used to supplement other mechanisms supporting cooperation, like reputation or punishment. Success-driven motion is formulated here as a function of the game-theoretical payoffs. It can change the outcome and dynamics of spatial games dramatically, in particular as it causes attractive or repulsive interaction forces. These forces act when the spatial distributions of strategies are inhomogeneous. However, even when starting with homogeneous initial conditions, small perturbations can trigger large inhomogeneities by a pattern-formation instability, when certain conditions are fulfilled. Here, these instability conditions are studied for the prisoner’s dilemma and the snowdrift game. Furthermore, it is demonstrated that asymmetrical diffusion can drive social, economic, and biological systems into the unstable regime, if these would be stable without diffusion.

Home and away- the evolutionary dynamics of homing endonucleases

Directory of Open Access Journals (Sweden)

Barzel Adi

2011-11-01

Full Text Available Abstract Background Homing endonucleases (HEases are a large and diverse group of site-specific DNAases. They reside within self-splicing introns and inteins, and promote their horizontal dissemination. In recent years, HEases have been the focus of extensive research due to their promising potential use in gene targeting procedures for the treatment of genetic diseases and for the genetic engineering of crop, animal models and cell lines. Results Using mathematical analysis and computational modeling, we present here a novel account for the evolution and population dynamics of HEase genes (HEGs. We describe HEGs as paradoxical selfish elements whose long-term persistence in a single population relies on low transmission rates and a positive correlation between transmission efficiency and toxicity. Conclusion Plausible conditions allow HEGs to sustain at high frequency through long evolutionary periods, with the endonuclease frequency being either at equilibrium or periodically oscillating. The predictions of our model may prove important not only for evolutionary theory but also for gene therapy and bio-engineering applications of HEases.

Dynamics of a spherical minority game

International Nuclear Information System (INIS)

Galla, T; Coolen, A C C; Sherrington, D

2003-01-01

We present an exact dynamical solution of a spherical version of the batch minority game (MG) with random external information. The control parameters in this model are the ratio of the number of possible values for the public information over the number of agents, and the radius of the spherical constraint on the microscopic degrees of freedom. We find a phase diagram with three phases: two without anomalous response (an oscillating versus a frozen state) and a further frozen phase with divergent integrated response. In contrast to standard MG versions, we can also calculate the volatility exactly. Our study reveals similarities between the spherical and the conventional MG, but also intriguing differences. Numerical simulations confirm our analytical results

Adaptive game AI with dynamic scripting

OpenAIRE

Spronck, P.; Ponsen, M.J.V.; Sprinkhuizen-Kuyper, I.G.; Postma, E.O.

2006-01-01

Online learning in commercial computer games allows computer-controlled opponents to adapt to the way the game is being played. As such it provides a mechanism to deal with weaknesses in the game AI, and to respond to changes in human player tactics.We argue that online learning of game AI should meet four computational and four functional requirements. The computational requirements are speed, effectiveness, robustness and ef- ficiency. The functional requirements are clarity, variety, consi...

Game theory in the death galaxy: interaction of cancer and stromal cells in tumour microenvironment.

Science.gov (United States)

Wu, Amy; Liao, David; Tlsty, Thea D; Sturm, James C; Austin, Robert H

2014-08-06

Preventing relapse is the major challenge to effective therapy in cancer. Within the tumour, stromal (ST) cells play an important role in cancer progression and the emergence of drug resistance. During cancer treatment, the fitness of cancer cells can be enhanced by ST cells because their molecular signalling interaction delays the drug-induced apoptosis of cancer cells. On the other hand, competition among cancer and ST cells for space or resources should not be ignored. We explore the population dynamics of multiple myeloma (MM) versus bone marrow ST cells by using an experimental microecology that we call the death galaxy, with a stable drug gradient and connected microhabitats. Evolutionary game theory is a quantitative way to capture the frequency-dependent nature of interactive populations. Therefore, we use evolutionary game theory to model the populations in the death galaxy with the gradients of pay-offs and successfully predict the future densities of MM and ST cells. We discuss the possible clinical use of such analysis for predicting cancer progression.

Effects of noise on convergent game-learning dynamics

International Nuclear Information System (INIS)

Sanders, James B T; Galla, Tobias; Shapiro, Jonathan L

2012-01-01

We study stochastic effects on the lagging anchor dynamics, a reinforcement learning algorithm used to learn successful strategies in iterated games, which is known to converge to Nash points in the absence of noise. The dynamics is stochastic when players only have limited information about their opponents’ strategic propensities. The effects of this noise are studied analytically in the case where it is small but finite, and we show that the statistics and correlation properties of fluctuations can be computed to a high accuracy. We find that the system can exhibit quasicycles, driven by intrinsic noise. If players are asymmetric and use different parameters for their learning, a net payoff advantage can be achieved due to these stochastic oscillations around the deterministic equilibrium. (paper)

Teaching physics with Angry Birds: exploring the kinematics and dynamics of the game

Science.gov (United States)

Rodrigues, M.; Simeão Carvalho, P.

2013-07-01

In this paper, we present classroom strategies for teaching kinematics at middle and high school levels, using Rovio’s famous game Angry Birds and the video analyser software Tracker. We show how to take advantage of this entertaining video game, by recording appropriate motions of birds that students can explore by manipulating data, characterizing the red bird’s motion and fitting results to physical models. A dynamic approach is also addressed to link gravitational force to projectile trajectories.

Evolutionary stability in the asymmetric volunteer's dilemma.

Directory of Open Access Journals (Sweden)

Jun-Zhou He

Full Text Available It is often assumed that in public goods games, contributors are either strong or weak players and each individual has an equal probability of exhibiting cooperation. It is difficult to explain why the public good is produced by strong individuals in some cooperation systems, and by weak individuals in others. Viewing the asymmetric volunteer's dilemma game as an evolutionary game, we find that whether the strong or the weak players produce the public good depends on the initial condition (i.e., phenotype or initial strategy of individuals. These different evolutionarily stable strategies (ESS associated with different initial conditions, can be interpreted as the production modes of public goods of different cooperation systems. A further analysis revealed that the strong player adopts a pure strategy but mixed strategies for the weak players to produce the public good, and that the probability of volunteering by weak players decreases with increasing group size or decreasing cost-benefit ratio. Our model shows that the defection probability of a "strong" player is greater than the "weak" players in the model of Diekmann (1993. This contradicts Selten's (1980 model that public goods can only be produced by a strong player, is not an evolutionarily stable strategy, and will therefore disappear over evolutionary time. Our public good model with ESS has thus extended previous interpretations that the public good can only be produced by strong players in an asymmetric game.

Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

KAUST Repository

Jaleel, Hassan

2018-04-08

Stochastic stability is a popular solution concept for stochastic learning dynamics in games. However, a critical limitation of this solution concept is its inability to distinguish between different learning rules that lead to the same steady-state behavior. We address this limitation for the first time and develop a framework for the comparative analysis of stochastic learning dynamics with different update rules but same steady-state behavior. We present the framework in the context of two learning dynamics: Log-Linear Learning (LLL) and Metropolis Learning (ML). Although both of these dynamics have the same stochastically stable states, LLL and ML correspond to different behavioral models for decision making. Moreover, we demonstrate through an example setup of sensor coverage game that for each of these dynamics, the paths to stochastically stable states exhibit distinctive behaviors. Therefore, we propose multiple criteria to analyze and quantify the differences in the short and medium run behavior of stochastic learning dynamics. We derive and compare upper bounds on the expected hitting time to the set of Nash equilibria for both LLL and ML. For the medium to long-run behavior, we identify a set of tools from the theory of perturbed Markov chains that result in a hierarchical decomposition of the state space into collections of states called cycles. We compare LLL and ML based on the proposed criteria and develop invaluable insights into the comparative behavior of the two dynamics.

Goal-based dictator game

Science.gov (United States)

Zaibidi, Nerda Zura; Ibrahim, Adyda; Abidin, Norhaslinda Zainal

2014-12-01

A considerable number of studies have been conducted to study fairness issues using two-player game. Dictator Game is one of the two-player games that receive much attention. In this paper, we develop an evolutionary approach to the Dictator Game by using Goal programming to build a model of human decision-making for cooperation. The model is formulated based on the theories of cognitive neuroscience that is capable in capturing a more realistic fairness concerns between players in the games. We show that fairness will evolve by taking into account players' aspirations and preferences explicitly in terms of profit and fairness concerns. The model is then simulated to investigate any possible effective strategy for people in economics to deal with fairness coalition. Parallels are drawn between the approach and concepts of human decision making from the field of cognitive neuroscience and psychology. The proposed model is also able to help decision makers to plan or enhance the effective strategies for business purposes.

Strategic tradeoffs in competitor dynamics on adaptive networks.

Science.gov (United States)

Hébert-Dufresne, Laurent; Allard, Antoine; Noël, Pierre-André; Young, Jean-Gabriel; Libby, Eric

2017-08-08

Recent empirical work highlights the heterogeneity of social competitions such as political campaigns: proponents of some ideologies seek debate and conversation, others create echo chambers. While symmetric and static network structure is typically used as a substrate to study such competitor dynamics, network structure can instead be interpreted as a signature of the competitor strategies, yielding competition dynamics on adaptive networks. Here we demonstrate that tradeoffs between aggressiveness and defensiveness (i.e., targeting adversaries vs. targeting like-minded individuals) creates paradoxical behaviour such as non-transitive dynamics. And while there is an optimal strategy in a two competitor system, three competitor systems have no such solution; the introduction of extreme strategies can easily affect the outcome of a competition, even if the extreme strategies have no chance of winning. Not only are these results reminiscent of classic paradoxical results from evolutionary game theory, but the structure of social networks created by our model can be mapped to particular forms of payoff matrices. Consequently, social structure can act as a measurable metric for social games which in turn allows us to provide a game theoretical perspective on online political debates.

Le Chatelier's principle in replicator dynamics

Science.gov (United States)

Allahverdyan, Armen E.; Galstyan, Aram

2011-10-01

The Le Chatelier principle states that physical equilibria are not only stable, but they also resist external perturbations via short-time negative-feedback mechanisms: a perturbation induces processes tending to diminish its results. The principle has deep roots, e.g., in thermodynamics it is closely related to the second law and the positivity of the entropy production. Here we study the applicability of the Le Chatelier principle to evolutionary game theory, i.e., to perturbations of a Nash equilibrium within the replicator dynamics. We show that the principle can be reformulated as a majorization relation. This defines a stability notion that generalizes the concept of evolutionary stability. We determine criteria for a Nash equilibrium to satisfy the Le Chatelier principle and relate them to mutualistic interactions (game-theoretical anticoordination) showing in which sense mutualistic replicators can be more stable than (say) competing ones. There are globally stable Nash equilibria, where the Le Chatelier principle is violated even locally: in contrast to the thermodynamic equilibrium a Nash equilibrium can amplify small perturbations, though both types of equilibria satisfy the detailed balance condition.

Information visualization of the minority game

Science.gov (United States)

Jiang, W.; Herbert, R. D.; Webber, R.

2008-02-01

Many dynamical systems produce large quantities of data. How can the system be understood from the output data? Often people are simply overwhelmed by the data. Traditional tools such as tables and plots are often not adequate, and new techniques are needed to help people to analyze the system. In this paper, we propose the use of two spacefilling visualization tools to examine the output from a complex agent-based financial model. We measure the effectiveness and performance of these tools through usability experiments. Based on the experimental results, we develop two new visualization techniques that combine the advantages and discard the disadvantages of the information visualization tools. The model we use is an evolutionary version of the Minority Game which simulates a financial market.

Information visualization of the minority game

International Nuclear Information System (INIS)

Jiang, W; Herbert, R D; Webber, R

2008-01-01

Many dynamical systems produce large quantities of data. How can the system be understood from the output data? Often people are simply overwhelmed by the data. Traditional tools such as tables and plots are often not adequate, and new techniques are needed to help people to analyze the system. In this paper, we propose the use of two spacefilling visualization tools to examine the output from a complex agent-based financial model. We measure the effectiveness and performance of these tools through usability experiments. Based on the experimental results, we develop two new visualization techniques that combine the advantages and discard the disadvantages of the information visualization tools. The model we use is an evolutionary version of the Minority Game which simulates a financial market

Evolutionary dynamics of consumers' crowdfunding strategies based on replicator dynamics%基于复制动态的消费者众筹策略演化动态

Institute of Scientific and Technical Information of China (English)

王先甲; 何奇龙; 全吉

2017-01-01

Use large group repeated game-replicator dynamics research on consumer groups who are bounded rationality got through imitating and learning to update their strategies supporting or nonsupporting crowdfunding under two scenarios fairness and altruism contribution rule.Established two people mult-strategy evolutionary game dynamic equations.Through analyzing the change of different parameters how to influence on the evolutionary stable equilibrium and the basin of attraction of the system,considering the failure of crowdfunding bringing regrets this paper researched the effects of crowdfunding success from different factors.The study find that under the fair contribution mechanism and without regard to regrets,supporting is the dominant strategy.Considering the failure of crowdfunding bringing regrets and generating negative benefit to consumer,when the target is smaller,the higher of the product quality level,the bigger of consumer's preferences and group benefits,the more beneficial to the crowdfunding evolutionary success.But the increasing of issued shares brings consumer's free-riding behavior,thus it restrains the success of crowdfunding.Under the altruism behavior,the bigger of consumer's preferences and group benefits,the higher of product quality level,the more beneficial to the crowdfunding evolutionary success.When financing target is fixed and the issued shares is increased,free-rider behavior don't increase,instead the success probability of crowdfunding be enhanced.%采用大群体反复博弈-复制动态演化博弈,在公平贡献和利他主义两种情景下,建立了有限理性的消费者群体通过模仿学习不断调整支持众筹和不支持众筹两策略多人博弈的演化系统.通过对不�

Wherever Hardware, There’ll be Games. The evolution of hardware and shifting industrial leadership in the gaming industry 1968-2004

OpenAIRE

Jörnmark, Jan

2005-01-01

Video game was the first truly digital entertainment medium, requiring processing power both in the production and consumption stage. Born out of the transistor, it was also intimately connected with its logic: the doubling of the processor capacity every 18th month or the halving of the price for the same processing capacity in the same time. Transistor technology and video games have been able to conquer society in an evolutionary process. Hence, video games have had an unprecedented abilit...

Psychology of Game Playing: Introduction to a Special Issue

Directory of Open Access Journals (Sweden)

Andrew M. Colman

2015-12-01

Full Text Available Game theory has focused attention on different problems at different times in its history. Currently, attention is devoted to investigating how human decision makers with bounded rationality choose strategies in interactive decisions. Behavioral economics, and more generally experimental games, have appeared in the literature with accelerating frequency since 1990, and this cannot continue indefinitely without a proportional expansion of journal space. This Special Issue includes contributions to behavioral economics, experimental games, and evolutionary game theory, using theoretical, experimental, and agent-based modeling techniques.

International conference on dynamical systems and game theory in honor of Mauricio Peixoto and David Rand

CERN Document Server

Peixoto, Mauricio Matos; Rand, David A J; Dynamics, Games and Science I

2011-01-01

"Dynamics, Games and Science I and II" are a selection of surveys and research articles written by leading researchers in mathematics and its applications to the sciences. The majority of the contributions are on dynamical systems and game theory, focusing either on some of their most fundamental and theoretical developments or on their applications to modeling in biology, economics, engineering, finances and psychology. The aim of these books is to present cutting-edge research in these areas that can encourage graduate students and researchers in mathematics to develop them further

Learning and anticipation in online dynamic optimization with evolutionary algorithms: The stochastic case

NARCIS (Netherlands)

P.A.N. Bosman (Peter); J.A. La Poutré (Han); D. Thierens (Dirk)

2007-01-01

htmlabstractThe focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, the EA must not only be capable of tracking shifting optima, it must also take into account the future

Evolutionary game theory and criticality

Science.gov (United States)

Mahmoodi, Korosh; Grigolini, Paolo

2017-01-01

We study a regular two-dimensional network of individuals playing the Prisonner’s Dilemma game with their neighbors, assigning to each individual the adoption of two different criteria to make a choice between cooperation and defection. For a fraction q  incentive to cheat yields the extinction of cooperation and a modest one leads to the survival of cooperation. We show that for K={{K}\\text{c}} the adoption of a very small value of ɛ exerts a bias in favor of either cooperation or defection, as a form of criticality-induced intelligence, which leads the system to select either the cooperation or the defection branch, when K>{{K}\\text{c}} . Intermediate values of ɛ annihilated criticality-induced cognition and, as consequence, may favor defection choice even in the case when a wise payoff consideration is expected to yield the emergence of cooperation.

Costly punishment and cooperation in the evolutionary snowdrift game

Science.gov (United States)

Xu, C.; Ji, M.; Yap, Yee Jiun; Zheng, Da-Fang; Hui, P. M.

2011-05-01

The role of punishments in promoting cooperation is an important issue. We incorporate costly punishments into the snowdrift game (SG) by introducing a third punishing (P) character, and study the effects. The punishers, who carry basically a cooperative (C) character, are willing to pay a cost α so as to punish a non-cooperative (D) opponent by β. Depending on the initial fractions of the characters, α, β, and the cost-to-benefit ratio r in the SG, the three-character system evolves into a steady state consisting either only of C and P characters or only of C and D characters, in a well-mixed population. The former situation represents an enhancement in cooperation relative to the SG, while the latter is similar to the SG. The dynamics in approaching these different steady states are found to be different. Analytically, the key features in the dynamics and the steady states observed in simulations are captured by a set of differential equations. The sensitivity to the initial distribution of characters is studied by depicting the flow in a phase portrait and analyzing the nature of fixed points. The analysis also shows the role of P-character agents in preventing a system from invasion by D-character agents. Starting from a population consisting only of C and P agents, a D-character agent intended to invade the system cannot survive when the initial fraction of P agents is greater than r/β. Our model, defined intentionally as a simulation algorithm, can be readily generalized to incorporate many interesting effects, such as those in a networked population.

Agents, games and evolution strategies at work and play

CERN Document Server

Kimbrough, Steven Orla

2011-01-01

StartersContexts of Strategic InteractionGames in the Wild and the Problems of PlayMixed MotivesPlaying Prisoner's DilemmaFanning Out: 2x2 Games and ModelsStag HuntPareto versus NashAffording CooperationMarkets and ApplicationsCompetitive MarketsMonopoly StoriesOligopoly: Cournot CompetitionOligopoly: Bertrand CompetitionSupply Curve BiddingTwo-Sided MatchingIDS GamesOrganizational AmbidexterityBargainingTopics in Strategic AnalysisLying and Related AbusesEvolutionary ModelsBackward InductionSumming UpAppendicesGame ConceptsUseful Mathematical ResultsFurther Arguments on the Surprise ExamResources on the WebBibliographyIndex.

Finite-horizon differential games for missile-target interception system using adaptive dynamic programming with input constraints

Science.gov (United States)

Sun, Jingliang; Liu, Chunsheng

2018-01-01

In this paper, the problem of intercepting a manoeuvring target within a fixed final time is posed in a non-linear constrained zero-sum differential game framework. The Nash equilibrium solution is found by solving the finite-horizon constrained differential game problem via adaptive dynamic programming technique. Besides, a suitable non-quadratic functional is utilised to encode the control constraints into a differential game problem. The single critic network with constant weights and time-varying activation functions is constructed to approximate the solution of associated time-varying Hamilton-Jacobi-Isaacs equation online. To properly satisfy the terminal constraint, an additional error term is incorporated in a novel weight-updating law such that the terminal constraint error is also minimised over time. By utilising Lyapunov's direct method, the closed-loop differential game system and the estimation weight error of the critic network are proved to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is demonstrated by using a simple non-linear system and a non-linear missile-target interception system, assuming first-order dynamics for the interceptor and target.

The role of IDH1 mutated tumour cells in secondary glioblastomas: an evolutionary game theoretical view

International Nuclear Information System (INIS)

Basanta, David; Scott, Jacob G; Anderson, Alexander R A; Rockne, Russ; Swanson, Kristin R

2011-01-01

Recent advances in clinical medicine have elucidated two significantly different subtypes of glioblastoma which carry very different prognoses, both defined by mutations in isocitrate dehydrogenase-1 (IDH-1). The mechanistic consequences of this mutation have not yet been fully clarified, with conflicting opinions existing in the literature; however, IDH-1 mutation may be used as a surrogate marker to distinguish between primary and secondary glioblastoma multiforme (sGBM) from malignant progression of a lower grade glioma. We develop a mathematical model of IDH-1 mutated secondary glioblastoma using evolutionary game theory to investigate the interactions between four different phenotypic populations within the tumor: autonomous growth, invasive, glycolytic, and the hybrid invasive/glycolytic cells. Our model recapitulates glioblastoma behavior well and is able to reproduce two recent experimental findings, as well as make novel predictions concerning the rate of invasive growth as a function of vascularity, and fluctuations in the proportions of phenotypic populations that a glioblastoma will experience under different microenvironmental constraints

The role of IDH1 mutated tumour cells in secondary glioblastomas: an evolutionary game theoretical view

Science.gov (United States)

Basanta, David; Scott, Jacob G.; Rockne, Russ; Swanson, Kristin R.; Anderson, Alexander R. A.

2011-02-01

Recent advances in clinical medicine have elucidated two significantly different subtypes of glioblastoma which carry very different prognoses, both defined by mutations in isocitrate dehydrogenase-1 (IDH-1). The mechanistic consequences of this mutation have not yet been fully clarified, with conflicting opinions existing in the literature; however, IDH-1 mutation may be used as a surrogate marker to distinguish between primary and secondary glioblastoma multiforme (sGBM) from malignant progression of a lower grade glioma. We develop a mathematical model of IDH-1 mutated secondary glioblastoma using evolutionary game theory to investigate the interactions between four different phenotypic populations within the tumor: autonomous growth, invasive, glycolytic, and the hybrid invasive/glycolytic cells. Our model recapitulates glioblastoma behavior well and is able to reproduce two recent experimental findings, as well as make novel predictions concerning the rate of invasive growth as a function of vascularity, and fluctuations in the proportions of phenotypic populations that a glioblastoma will experience under different microenvironmental constraints.

Motion depending on the strategies of players enhances cooperation in a co-evolutionary prisoner's dilemma game

International Nuclear Information System (INIS)

Cheng Hongyan; Li Haihong; Dai Qionglin; Zhu Yun; Yang Junzhong

2010-01-01

In the evolution of cooperation, the motion of players plays an important role. In this paper, we incorporate, into an evolutionary prisoner dilemma's game on networks, a new factor that cooperators and defectors move with different probabilities. By investigating the dependence of the cooperator frequency on the moving probabilities of cooperators and defectors, μ c and μ d , we find that cooperation is greatly enhanced in the parameter regime of μ c d . The snapshots of strategy pattern and the evolutions of cooperator clusters and defector clusters reveal that either the fast motion of defectors or the slow motion of cooperators always favors the formation of large cooperator clusters. The model is investigated on different types of networks such as square lattices, Erdoes-Renyi networks and scale-free networks and with different types of strategy-updating rules such as the richest-following rule and the Fermi rule. The numerical results show that the observed phenomena are robust to different networks and to different strategy-updating rules.

Fast stochastic algorithm for simulating evolutionary population dynamics

Science.gov (United States)

Tsimring, Lev; Hasty, Jeff; Mather, William

2012-02-01

Evolution and co-evolution of ecological communities are stochastic processes often characterized by vastly different rates of reproduction and mutation and a coexistence of very large and very small sub-populations of co-evolving species. This creates serious difficulties for accurate statistical modeling of evolutionary dynamics. In this talk, we introduce a new exact algorithm for fast fully stochastic simulations of birth/death/mutation processes. It produces a significant speedup compared to the direct stochastic simulation algorithm in a typical case when the total population size is large and the mutation rates are much smaller than birth/death rates. We illustrate the performance of the algorithm on several representative examples: evolution on a smooth fitness landscape, NK model, and stochastic predator-prey system.

Strong solutions and instability for the fitness gradient system in evolutionary games between two populations

Science.gov (United States)

Xu, Qiuju; Belmonte, Andrew; deForest, Russ; Liu, Chun; Tan, Zhong

2017-04-01

In this paper, we study a fitness gradient system for two populations interacting via a symmetric game. The population dynamics are governed by a conservation law, with a spatial migration flux determined by the fitness. By applying the Galerkin method, we establish the existence, regularity and uniqueness of global solutions to an approximate system, which retains most of the interesting mathematical properties of the original fitness gradient system. Furthermore, we show that a Turing instability occurs for equilibrium states of the fitness gradient system, and its approximations.

Lighting effects for mobile games

DEFF Research Database (Denmark)

Frisvad, Jeppe Revall; Christensen, Niels Jørgen; Falster, Peter

2005-01-01

lighting. Textures are merely plastered onto the tiles. A recent game release has, however, shown that effects such as dynamic light sources can spice up a mobile game of this type quite a bit. In this paper we carry the idea of dynamic lighting effects for tile-based 2D games even further. In particular...

Examples of equilibrium and non-equilibrium behavior in evolutionary systems

Science.gov (United States)

Soulier, Arne

With this thesis, we want to shed some light into the darkness of our understanding of simply defined statistical mechanics systems and the surprisingly complex dynamical behavior they exhibit. We will do so by presenting in turn one equilibrium and then one non-equilibrium system with evolutionary dynamics. In part 1, we will present the seceder-model, a newly developed system that cannot equilibrate. We will then study several properties of the system and obtain an idea of the richness of the dynamics of the seceder model, which is particular impressive given the minimal amount of modeling necessary in its setup. In part 2, we will present extensions to the directed polymer in random media problem on a hypercube and its connection to the Eigen model of evolution. Our main interest will be the influence of time-dependent and time-independent changes in the fitness landscape viewed by an evolving population. This part contains the equilibrium dynamics. The stochastic models and the topic of evolution and non-equilibrium in general will allow us to point out similarities to the various lines of thought in game theory.

Evolutionary robotics simulations help explain why reciprocity is rare in nature.

Science.gov (United States)