WorldWideScience

Sample records for intelligence ai entry

  1. Artificial Intelligence Study (AIS).

    Science.gov (United States)

    1987-02-01

    ARTIFICIAL INTELLIGNECE HARDWARE ....... 2-50 AI Architecture ................................... 2-49 AI Hardware ....................................... 2...ftf1 829 ARTIFICIAL INTELLIGENCE STUDY (RIS)(U) MAY CONCEPTS 1/3 A~NLYSIS AGENCY BETHESA RD R B NOJESKI FED 6? CM-RP-97-1 NCASIFIED /01/6 M |K 1.0...p/ - - ., e -- CAA- RP- 87-1 SAOFŔ)11 I ARTIFICIAL INTELLIGENCE STUDY (AIS) tNo DTICFEBRUARY 1987 LECT 00 I PREPARED BY RESEARCH AND ANALYSIS

  2. Organisational intelligence and distributed AI

    OpenAIRE

    Kirn, Stefan

    1995-01-01

    The analysis of this chapter starts from organisational theory, and from this it draws conclusions for the design, and possible organisational applications, of Distributed AI systems. We first review how the concept of organisations has emerged from non-organised black-box entities to so-called computerised organisations. Within this context, organisational researchers have started to redesign their models of intelligent organisations with respect to the availability of advanced computing tec...

  3. Artificial intelligence. Fears of an AI pioneer.

    Science.gov (United States)

    Russell, Stuart; Bohannon, John

    2015-07-17

    From the enraged robots in the 1920 play R.U.R. to the homicidal computer H.A.L. in 2001: A Space Odyssey, science fiction writers have embraced the dark side of artificial intelligence (AI) ever since the concept entered our collective imagination. Sluggish progress in AI research, especially during the “AI winter” of the 1970s and 1980s, made such worries seem far-fetched. But recent breakthroughs in machine learning and vast improvements in computational power have brought a flood of research funding— and fresh concerns about where AI may lead us. One researcher now speaking up is Stuart Russell, a computer scientist at the University of California, Berkeley, who with Peter Norvig, director of research at Google, wrote the premier AI textbook, Artificial Intelligence: A Modern Approach, now in its third edition. Last year, Russell joined the Centre for the Study of Existential Risk at Cambridge University in the United Kingdom as an AI expert focusing on “risks that could lead to human extinction.” Among his chief concerns, which he aired at an April meeting in Geneva, Switzerland, run by the United Nations, is the danger of putting military drones and weaponry under the full control of AI systems. This interview has been edited for clarity and brevity.

  4. Beyond AI: Interdisciplinary Aspects of Artificial Intelligence

    CERN Document Server

    Romportl, Jan; Zackova, Eva; Beyond Artificial Intelligence : Contemplations, Expectations, Applications

    2013-01-01

    Products of modern artificial intelligence (AI) have mostly been formed by the views, opinions and goals of the “insiders”, i.e. people usually with engineering background who are driven by the force that can be metaphorically described as the pursuit of the craft of Hephaestus. However, since the present-day technology allows for tighter and tighter mergence of the “natural” everyday human life with machines of immense complexity, the responsible reaction of the scientific community should be based on cautious reflection of what really lies beyond AI, i.e. on the frontiers where the tumultuous ever-growing and ever-changing cloud of AI touches the rest of the world.   The chapters of this boo are based on the selected subset of the presentations that were delivered by their respective authors at the conference “Beyond AI: Interdisciplinary Aspects of Artificial Intelligence” held in Pilsen in December 2011.   From its very definition, the reflection of the phenomena that lie beyond AI must be i...

  5. Artificial Intelligence Safety and Cybersecurity: a Timeline of AI Failures

    OpenAIRE

    Yampolskiy, Roman V.; Spellchecker, M. S.

    2016-01-01

    In this work, we present and analyze reported failures of artificially intelligent systems and extrapolate our analysis to future AIs. We suggest that both the frequency and the seriousness of future AI failures will steadily increase. AI Safety can be improved based on ideas developed by cybersecurity experts. For narrow AIs safety failures are at the same, moderate, level of criticality as in cybersecurity, however for general AI, failures have a fundamentally different impact. A single fai...

  6. Beyond AI: Multi-Intelligence (MI Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

    Directory of Open Access Journals (Sweden)

    Stephen Fox

    2017-06-01

    Full Text Available Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, the extensive post-anthropocentric research into intelligence is not given sufficient consideration. Third, AI is discussed often in reductionist mechanistic terms. Rather than in organicist emergentist terms as a contributor to multi-intelligence (MI hybrid beings and/or systems. Thus, current framing of AI can be a self-validating reduction within which AI development is focused upon AI becoming the single-variable mechanism causing future effects. In this paper, AI is reframed as a contributor to MI.

  7. [Artificial intelligence] AI for protection systems

    Energy Technology Data Exchange (ETDEWEB)

    Aggarwal, R.; Johns, A.

    1997-12-31

    The reliable operation of large power systems with small stability margins is highly dependent on control systems and protection devices. Progress in the field of microprocessor systems and demanding requirements in respect of the performance of protective relays are the reasons for digital device applications to power system protection. The superiority of numeric protection over its analogue alternatives is attributed to such factors as accurate extraction of the fundamental voltage and current components through filtering, functional benefits resulting from multi-processor design and extensive self-monitoring, etc. However, all these reasons have not led to a major impact on speed, sensitivity and selectivity of primary protective relays, and the gains are only marginal; this is so because conventional digital relays still rely on deterministic signal models and a heuristic approach for decision making, so that only a fraction of the information contained within voltage and current signals as well as knowledge about the plant to be protected is used. The performance of digital relays may be substantially improved if the decision making is based on elements of artificial intelligence (AI). (Author)

  8. Beyond AI: Multi-Intelligence (MI) Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

    OpenAIRE

    Stephen Fox

    2017-01-01

    Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI) are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, t...

  9. Artificial Intelligence (AI) Studies in Water Resources

    OpenAIRE

    Ay, Murat; Özyıldırım, Serhat

    2018-01-01

    Artificial intelligence has been extensively used in many areas such as computer science,robotics, engineering, medicine, translation, economics, business, and psychology. Variousstudies in the literature show that the artificial intelligence in modeling approaches give closeresults to the real data for solution of linear, non-linear, and other systems. In this study, wereviewed the current state-of-the-art and progress on the modelling of artificial intelligence forwater variables: rainfall-...

  10. Human-Assisted AI: an Intelligence Augmentation Approach

    OpenAIRE

    Alicea, Bradly

    2018-01-01

    As a flavor of Human-Computer Interaction (HCI), Human-Assisted AI can serve to both augment both human performance and artificial systems. This talk will feature a discussion of Human-assisted AI as an instance of Intelligence Augmentation (IA). We will discuss instances of weak and strong IA, in addition to contemporary examples of and paths forward for such systems. In the variety of models presented, data plays a critical role in the structure of interactions between human and artificial ...

  11. Artificial intelligence (AI) systems for interpreting complex medical datasets.

    Science.gov (United States)

    Altman, R B

    2017-05-01

    Advances in machine intelligence have created powerful capabilities in algorithms that find hidden patterns in data, classify objects based on their measured characteristics, and associate similar patients/diseases/drugs based on common features. However, artificial intelligence (AI) applications in medical data have several technical challenges: complex and heterogeneous datasets, noisy medical datasets, and explaining their output to users. There are also social challenges related to intellectual property, data provenance, regulatory issues, economics, and liability. © 2017 ASCPT.

  12. Artificial Intelligence: Is the Future Now for A.I.?

    Science.gov (United States)

    Ramaswami, Rama

    2009-01-01

    In education, artificial intelligence (AI) has not made much headway. In the one area where it would seem poised to lend the most benefit--assessment--the reliance on standardized tests, intensified by the demands of the No Child Left Behind Act of 2001, which holds schools accountable for whether students pass statewide exams, precludes its use.…

  13. The deep learning AI playbook strategy for disruptive artificial intelligence

    CERN Document Server

    Perez, Carlos E

    2017-01-01

    Deep Learning Artificial Intelligence involves the interplay of Computer Science, Physics, Biology, Linguistics and Psychology. In addition to that, it is technology that can be extremely disruptive. The ramifications to society and even our own humanity will be profound. There are few subjects that are as captivating and as consequential as this. Surprisingly, there is very little that is written about this new technology in a more comprehensive and cohesive way. This book is an opinionated take on the developments of Deep Learning AI. One question many have will be "how to apply Deep Learning AI in a business context?" Technology that is disruptive does not automatically imply that its application to valuable use cases will be apparent. For years, many people could not figure out how to monetize the World Wide Web. We are in a similar situation with Deep Learning AI. The developments may be mind-boggling but its monetization is far from being obvious. This book presents a framework to address this shortcomi...

  14. Artificial Intelligence (AI) Based Tactical Guidance for Fighter Aircraft

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    1990-01-01

    A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches, including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance of a prototype concurrent TDG system are presented.

  15. Computational intelligence from AI to BI to NI

    Science.gov (United States)

    Werbos, Paul J.

    2015-05-01

    This paper gives highlights of the history of the neural network field, stressing the fundamental ideas which have been in play. Early neural network research was motivated mainly by the goals of artificial intelligence (AI) and of functional neuroscience (biological intelligence, BI), but the field almost died due to frustrations articulated in the famous book Perceptrons by Minsky and Papert. When I found a way to overcome the difficulties by 1974, the community mindset was very resistant to change; it was not until 1987/1988 that the field was reborn in a spectacular way, leading to the organized communities now in place. Even then, it took many more years to establish crossdisciplinary research in the types of mathematical neural networks needed to really understand the kind of intelligence we see in the brain, and to address the most demanding engineering applications. Only through a new (albeit short-lived) funding initiative, funding crossdisciplinary teams of systems engineers and neuroscientists, were we able to fund the critical empirical demonstrations which put our old basic principle of "deep learning" firmly on the map in computer science. Progress has rightly been inhibited at times by legitimate concerns about the "Terminator threat" and other possible abuses of technology. This year, at SPIE, in the quantum computing track, we outline the next stage ahead of us in breaking out of the box, again and again, and rising to fundamental challenges and opportunities still ahead of us.

  16. Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS)

    CSIR Research Space (South Africa)

    Xing, B

    2009-12-01

    Full Text Available This work focuses on the design and control of a novel hybrid manufacturing system: Reconfigurable Cellular Manufacturing System (RCMS) by using Artificial Intelligence (AI) approach. It is hybrid as it combines the advantages of Cellular...

  17. Ai

    African Journals Online (AJOL)

    :=g=~!Ai~~~~~g~~ ~~~~~~. Jim Taylor, Rob O'Donoghue and Alistair Clacherty. INTRODUCTION. The Department of Environment Affairs, in cooperation with ...

  18. Quality measures and assurance for AI (Artificial Intelligence) software

    Science.gov (United States)

    Rushby, John

    1988-01-01

    This report is concerned with the application of software quality and evaluation measures to AI software and, more broadly, with the question of quality assurance for AI software. Considered are not only the metrics that attempt to measure some aspect of software quality, but also the methodologies and techniques (such as systematic testing) that attempt to improve some dimension of quality, without necessarily quantifying the extent of the improvement. The report is divided into three parts Part 1 reviews existing software quality measures, i.e., those that have been developed for, and applied to, conventional software. Part 2 considers the characteristics of AI software, the applicability and potential utility of measures and techniques identified in the first part, and reviews those few methods developed specifically for AI software. Part 3 presents an assessment and recommendations for the further exploration of this important area.

  19. Towards an unanimous international regulatory body for responsible use of Artificial Intelligence [UIRB-AI

    OpenAIRE

    Chidambaram, Rajesh

    2017-01-01

    Artificial Intelligence (AI), is once again in the phase of drastic advancements. Unarguably, the technology itself can revolutionize the way we live our everyday life. But the exponential growth of technology poses a daunting task for policy researchers and law makers in making amendments to the existing norms. In addition, not everyone in the society is studying the potential socio-economic intricacies and cultural drifts that AI can bring about. It is prudence to reflect from our historica...

  20. Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

    Science.gov (United States)

    Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

    1987-01-01

    In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

  1. AI Reloaded: Objectives, Potentials, and Challenges of the Novel Field of Brain-Like Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2012-11-01

    Full Text Available The general objective of Artificial Intelligence (AI is to make machines – particularly computers – do things that require intelligence when done by humans. In the last 60 years, AI has significantly progressed and today forms an important part of industry and technology. However, despite the many successes, fundamental questions concerning the creation of human-level intelligence in machines still remain open and will probably not be answerable when continuing on the current, mainly mathematic-algorithmically-guided path of AI. With the novel discipline of
    Brain-Like Artificial Intelligence, one potential way out of this dilemma has been suggested. Brain-Like AI aims at analyzing and deciphering the working mechanisms of the brain and translating this knowledge into implementable AI architectures with the objective to develop in this way more efficient, flexible, and capable technical systems This article aims at giving a review about this young and still heterogeneous and dynamic research field.

  2. BWR shutdown analyzer using artificial intelligence (AI) techniques

    International Nuclear Information System (INIS)

    Cain, D.G.

    1986-01-01

    A prototype alarm system for detecting abnormal reactor shutdowns based on artificial intelligence technology is described. The system incorporates knowledge about Boiling Water Reactor (BWR) plant design and component behavior, as well as knowledge required to distinguish normal, abnormal, and ATWS accident conditions. The system was developed using a software tool environment for creating knowledge-based applications on a LISP machine. To facilitate prototype implementation and evaluation, a casual simulation of BWR shutdown sequences was developed and interfaced with the alarm system. An intelligent graphics interface for execution and control is described. System performance considerations and general observations relating to artificial intelligence application to nuclear power plant problems are provided

  3. Intelligence Unleashed: An argument for AI in Education

    OpenAIRE

    Luckin, R.; Holmes, W.

    2016-01-01

    This paper on artificial intelligence in education (AIEd) has two aims. The first: to explain to a non-specialist, interested, reader what AIEd is: its goals, how it is built, and how it works. The second: to set out the argument for what AIEd can offer teaching and learning, both now and in the future, with an eye towards improving learning and life outcomes for all. Computer systems that are artificially intelligent interact with the world using capabilities (such as speech recognition) and...

  4. Infrastructural intelligence: Contemporary entanglements between neuroscience and AI.

    Science.gov (United States)

    Bruder, Johannes

    2017-01-01

    In this chapter, I reflect on contemporary entanglements between artificial intelligence and the neurosciences by tracing the development of Google's recent DeepMind algorithms back to their roots in neuroscientific studies of episodic memory and imagination. Google promotes a new form of "infrastructural intelligence," which excels by constantly reassessing its cognitive architecture in exchange with a cloud of data that surrounds it, and exhibits putatively human capacities such as intuition. I argue that such (re)alignments of biological and artificial intelligence have been enabled by a paradigmatic infrastructuralization of the brain in contemporary neuroscience. This infrastructuralization is based in methodologies that epistemically liken the brain to complex systems of an entirely different scale (i.e., global logistics) and has given rise to diverse research efforts that target the neuronal infrastructures of higher cognitive functions such as empathy and creativity. What is at stake in this process is no less than the shape of brains to come and a revised understanding of the intelligent and creative social subject. © 2017 Elsevier B.V. All rights reserved.

  5. Prediction of shipboard electromagnetic interference (EMI) problems using artificial intelligence (AI) technology

    Science.gov (United States)

    Swanson, David J.

    1990-08-01

    The electromagnetic interference prediction problem is characteristically ill-defined and complicated. Severe EMI problems are prevalent throughout the U.S. Navy, causing both expected and unexpected impacts on the operational performance of electronic combat systems onboard ships. This paper focuses on applying artificial intelligence (AI) technology to the prediction of ship related electromagnetic interference (EMI) problems.

  6. Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology.

    Science.gov (United States)

    VoPham, Trang; Hart, Jaime E; Laden, Francine; Chiang, Yao-Yi

    2018-04-17

    Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.

  7. Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction

    Science.gov (United States)

    Afan, Haitham Abdulmohsin; El-shafie, Ahmed; Mohtar, Wan Hanna Melini Wan; Yaseen, Zaher Mundher

    2016-10-01

    An accurate model for sediment prediction is a priority for all hydrological researchers. Many conventional methods have shown an inability to achieve an accurate prediction of suspended sediment. These methods are unable to understand the behaviour of sediment transport in rivers due to the complexity, noise, non-stationarity, and dynamism of the sediment pattern. In the past two decades, Artificial Intelligence (AI) and computational approaches have become a remarkable tool for developing an accurate model. These approaches are considered a powerful tool for solving any non-linear model, as they can deal easily with a large number of data and sophisticated models. This paper is a review of all AI approaches that have been applied in sediment modelling. The current research focuses on the development of AI application in sediment transport. In addition, the review identifies major challenges and opportunities for prospective research. Throughout the literature, complementary models superior to classical modelling.

  8. AIonAI: a humanitarian law of artificial intelligence and robotics.

    Science.gov (United States)

    Ashrafian, Hutan

    2015-02-01

    The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, stipulating obedience to humans and incorporating robotic self-protection. However the overwhelming predominance in the study of this field has focussed on human-robot interactions without fully considering the ethical inevitability of future artificial intelligences communicating together and has not addressed the moral nature of robot-robot interactions. A new robotic law is proposed and termed AIonAI or artificial intelligence-on-artificial intelligence. This law tackles the overlooked area where future artificial intelligences will likely interact amongst themselves, potentially leading to exploitation. As such, they would benefit from adopting a universal law of rights to recognise inherent dignity and the inalienable rights of artificial intelligences. Such a consideration can help prevent exploitation and abuse of rational and sentient beings, but would also importantly reflect on our moral code of ethics and the humanity of our civilisation.

  9. Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program

    OpenAIRE

    Eaton, Eric; Koenig, Sven; Schulz, Claudia; Maurelli, Francesco; Lee, John; Eckroth, Joshua; Crowley, Mark; Freedman, Richard G.; Cardona-Rivera, Rogelio E.; Machado, Tiago; Williams, Tom

    2017-01-01

    The 7th Symposium on Educational Advances in Artificial Intelligence (EAAI'17, co-chaired by Sven Koenig and Eric Eaton) launched the EAAI New and Future AI Educator Program to support the training of early-career university faculty, secondary school faculty, and future educators (PhD candidates or postdocs who intend a career in academia). As part of the program, awardees were asked to address one of the following "blue sky" questions: * How could/should Artificial Intelligence (AI) courses ...

  10. Artificial Intelligence (AI techniques to analyze the determinants attributes in housing prices

    Directory of Open Access Journals (Sweden)

    Julia M. Núñez Tabale

    2016-12-01

    Full Text Available The econometric approach to obtain the value of a property began with hedonic modelling, which were based on a set of property attributes, internal or external, associated to each particular dwelling. The final sale value can be estimated, and also the marginal prices of each exogenous explanatory variable. A good alternative to the hedonic approach is based on several Artificial Intelligence (AI techniques, such as artificial neural networks (ANN, these tend to be more precise. Both methodologies are compared, and a case study is developed using data from Seville, the larger town in the South of Spain.

  11. Application of Artificial Intelligence (AI) Programming Techniques to Tactical Guidance for Fighter Aircraft

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    1989-01-01

    A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.

  12. An artificial intelligence (AI) NOx/heat rate optimization system for Ontario Hydro`s fossil generating stations

    Energy Technology Data Exchange (ETDEWEB)

    Luk, J.; Frank, A.; Bodach, P. [Ontario Hydro, Toronto, ON (Canada); Warriner, G. [Radian International, Tucker, GA (United States); Noblett, J. [Radian International, Austin, TX (United States); Slatsky, M. [Southern Company, Birmingham, AL (United States)

    1999-08-01

    Artificial intelligence (AI)-based software packages which can optimize power plant operations that improves heat rate and also reduces nitrogen oxide emissions are now commonly available for commercial use. This paper discusses the implementation of the AI-based NOx and Heat Rate Optimization System at Ontario Hydro`s generation stations, emphasizing the current AI Optimization Project at Units 5 and 6 of the Lakeview Generating Station. These demonstration programs are showing promising results in NOx reduction and plant performance improvement. The availability of the plant Digital Control System (DCS) in implementing AI optimization in a closed-loop system was shown to be an important criterion for success. Implementation of AI technology at other Ontario Hydro fossil generating units as part of the overall NOx emission reduction system is envisaged to coincide with the retrofit of the original plant control system with the latest DCS systems. 14 refs., 3 figs.

  13. Artificial intelligence/expert (AI/EX) systems for steelworks pollution control

    Energy Technology Data Exchange (ETDEWEB)

    Schofield, N.; Le Louer, P.; Mirabile, D.; Hubner, R. [Corus UK Ltd., Rotherham (United Kingdom)

    2002-07-01

    The objectives of this project have been to develop and apply artificial intelligence and expert system (AI/EX) methods to improve the control and operational performance of steelworks' pollution control equipment and to assess the viability and benefits of using such systems in dynamic process plant applications. Four distinct sub-projects were carried out: an expert system incorporating knowledge-based rules and neural network simulations has been developed by Corus which provides plant personnel with a real-time condition monitoring tool for the plant. Abnormalities with plant operation are now instantly recognised and alarmed, allowing prioritised maintenance to increase plant availability. The LECES project focused on studies concerning three different sites in order to evaluate predictive emission monitoring systems using neural networks to replace conventional instrumental and controls in steelworks' combustion systems. VAI developed a software template for pollution control expert systems to demonstrate the transferability of AI/EX technology. This has been done through the development of a validated process database containing data from the Corus sub-project and the subsequent integration of this data with dynamic emission models to produce rules for input to an evaluation database. CSM developed a fuzzy logic controlled process management system applied to the biological treatment of coke-oven waste water. A pilot plant has been installed and results on simulations performed using the fuzzy logic system linked to a neural network simulator show that it is possible to obtain great advantages in the biological pilot plant performance.

  14. Human-centered automation and AI - Ideas, insights, and issues from the Intelligent Cockpit Aids research effort

    Science.gov (United States)

    Abbott, Kathy H.; Schutte, Paul C.

    1989-01-01

    A development status evaluation is presented for the NASA-Langley Intelligent Cockpit Aids research program, which encompasses AI, human/machine interfaces, and conventional automation. Attention is being given to decision-aiding concepts for human-centered automation, with emphasis on inflight subsystem fault management, inflight mission replanning, and communications management. The cockpit envisioned is for advanced commercial transport aircraft.

  15. Flood AI: An Intelligent Systems for Discovery and Communication of Disaster Knowledge

    Science.gov (United States)

    Demir, I.; Sermet, M. Y.

    2017-12-01

    Communities are not immune from extreme events or natural disasters that can lead to large-scale consequences for the nation and public. Improving resilience to better prepare, plan, recover, and adapt to disasters is critical to reduce the impacts of extreme events. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This project presents an intelligent system, Flood AI, for flooding to improve societal preparedness by providing a knowledge engine using voice recognition, artificial intelligence, and natural language processing based on a generalized ontology for disasters with a primary focus on flooding. The knowledge engine utilizes the flood ontology and concepts to connect user input to relevant knowledge discovery channels on flooding by developing a data acquisition and processing framework utilizing environmental observations, forecast models, and knowledge bases. Communication channels of the framework includes web-based systems, agent-based chat bots, smartphone applications, automated web workflows, and smart home devices, opening the knowledge discovery for flooding to many unique use cases.

  16. The Molecular Basis of Neural Memory. Part 7: Neural Intelligence (NI versus Artificial Intelligence (AI

    Directory of Open Access Journals (Sweden)

    Gerard Marx

    2017-07-01

    Full Text Available The link of memory to intelligence is incontestable, though the development of electronic artifacts with memory has confounded cognitive and computer scientists’ conception of memory and its relevance to “intelligence”. We propose two categories of “Intelligence”: (1 Logical (objective — mathematics, numbers, pattern recognition, games, programmable in binary format. (2 Emotive (subjective — sensations, feelings, perceptions, goals desires, sociability, sex, food, love. The 1st has been reduced to computational algorithms of which we are well versed, witness global technology and the internet. The 2nd relates to the mysterious process whereby (psychic emotive states are achieved by neural beings sensing, comprehending, remembering and dealing with their surroundings. Many theories and philosophies have been forwarded to rationalize this process, but as neuroscientists, we remain dissatisfied. Our own musings on universal neural memory, suggest a tripartite mechanism involving neurons interacting with their surroundings, notably the neural extracellular matrix (nECM with dopants [trace metals and neurotransmitters (NTs]. In particular, the NTs are the molecular encoders of emotive states. We have developed a chemographic representation of such a molecular code.To quote Longuet-Higgins, “Perhaps it is time for the term ‘artificial intelligence’ to be replaced by something more modest and less provisional”. We suggest “artifact intelligence” (ARTI or “machine intelligence” (MI, neither of which imply emulation of emotive neural processes, but simply refer to the ‘demotive’ (lacking emotive quality capability of electronic artifacts that employ a recall function, to calculate algorithms.

  17. AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis.

    Science.gov (United States)

    Kayser, Klaus; Görtler, Jürgen; Bogovac, Milica; Bogovac, Aleksandar; Goldmann, Torsten; Vollmer, Ekkehard; Kayser, Gian

    2009-01-01

    The technological progress in digitalization of complete histological glass slides has opened a new door in tissue--based diagnosis. The presentation of microscopic images as a whole in a digital matrix is called virtual slide. A virtual slide allows calculation and related presentation of image information that otherwise can only be seen by individual human performance. The digital world permits attachments of several (if not all) fields of view and the contemporary visualization on a screen. The presentation of all microscopic magnifications is possible if the basic pixel resolution is less than 0.25 microns. To introduce digital tissue--based diagnosis into the daily routine work of a surgical pathologist requires a new setup of workflow arrangement and procedures. The quality of digitized images is sufficient for diagnostic purposes; however, the time needed for viewing virtual slides exceeds that of viewing original glass slides by far. The reason lies in a slower and more difficult sampling procedure, which is the selection of information containing fields of view. By application of artificial intelligence, tissue--based diagnosis in routine work can be managed automatically in steps as follows: 1. The individual image quality has to be measured, and corrected, if necessary. 2. A diagnostic algorithm has to be applied. An algorithm has be developed, that includes both object based (object features, structures) and pixel based (texture) measures. 3. These measures serve for diagnosis classification and feedback to order additional information, for example in virtual immunohistochemical slides. 4. The measures can serve for automated image classification and detection of relevant image information by themselves without any labeling. 5. The pathologists' duty will not be released by such a system; to the contrary, it will manage and supervise the system, i.e., just working at a "higher level". Virtual slides are already in use for teaching and continuous

  18. AI's Philosophical Underpinnings: A Thinking Person's Walk through the Twists and Turns of Artificial Intelligence's Meandering Path

    Science.gov (United States)

    Colombano, Silvano; Norvig, Peter (Technical Monitor)

    2000-01-01

    Few human endeavors can be viewed both as extremely successful and unsuccessful at the same time. This is typically the case when goals have not been well defined or have been shifting in time. This has certainly been true of Artificial Intelligence (AI). The nature of intelligence has been the object of much thought and speculation throughout the history of philosophy. It is in the nature of philosophy that real headway is sometimes made only when appropriate tools become available. Similarly the computer, coupled with the ability to program (at least in principle) any function, appeared to be the tool that could tackle the notion of intelligence. To suit the tool, the problem of the nature of intelligence was soon sidestepped in favor of this notion: If a probing conversation with a computer could not be distinguished from a conversation with a human, then AI had been achieved. This notion became known as the Turing test, after the mathematician Alan Turing who proposed it in 1950. Conceptually rich and interesting, these early efforts gave rise to a large portion of the field's framework. Key to AI, rather than the 'number crunching' typical of computers until then, was viewed as the ability to manipulate symbols and make logical inferences. To facilitate these tasks, AI languages such as LISP and Prolog were invented and used widely in the field. One idea that emerged and enabled some success with real world problems was the notion that 'most intelligence' really resided in knowledge. A phrase attributed to Feigenbaum, one of the pioneers, was 'knowledge is the power.' With this premise, the problem is shifted from 'how do we solve problems' to 'how do we represent knowledge.' A good knowledge representation scheme could allow one to draw conclusions from given premises. Such schemes took forms such as rules,frames and scripts. It allowed the building of what became known as expert systems or knowledge based systems (KBS).

  19. Methodology Investigation of AI(Artificial Intelligence) Test Officer Support Tool. Volume 1

    Science.gov (United States)

    1989-03-01

    American Association for Artificial inteligence A! ............. Artificial inteliigence AMC ............ Unt:ed States Army Maeriel Comand ASL...block number) FIELD GROUP SUB-GROUP Artificial Intelligence, Expert Systems Automated Aids to Testing 9. ABSTRACT (Continue on reverse if necessary and...identify by block number) This report covers the application of Artificial Intelligence-Techniques to the problem of creating automated tools to

  20. Pathologies of AI: Responsible use of artificial intelligence in professional work

    NARCIS (Netherlands)

    Stamper, R.K.

    1988-01-01

    Although the AI paradigm is useful for building knowledge-based systems for the applied natural sciences, there are dangers when it is extended into the domains of business, law and other social systems. It is misleading to treat knowledge as a commodity that can be separated from the context in

  1. The Emperor of Strong AI Has No Clothes: Limits to Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Adriana Braga

    2017-11-01

    Full Text Available Making use of the techniques of media ecology we argue that the premise of the technological Singularity based on the notion computers will one day be smarter that their human creators is false. We also analyze the comments of other critics of the Singularity, as well supporters of this notion. The notion of intelligence that advocates of the technological singularity promote does not take into account the full dimension of human intelligence. They treat artificial intelligence as a figure without a ground. Human intelligence as we will show is not based solely on logical operations and computation, but also includes a long list of other characteristics that are unique to humans, which is the ground that supporters of the Singularity ignore. The list includes curiosity, imagination, intuition, emotions, passion, desires, pleasure, aesthetics, joy, purpose, objectives, goals, telos, values, morality, experience, wisdom, judgment, and even humor.

  2. Investigating AI with Basic and Logo. Teaching Your Computer to Be Intelligent.

    Science.gov (United States)

    Mandell, Alan; Lucking, Robert

    1988-01-01

    Discusses artificial intelligence, its definitions, and potential applications. Provides listings of Logo and BASIC versions for programs along with REM statements needed to make modifications for use with Apple computers. (RT)

  3. Artificial Intelligence (AI) in Healthcare Market: Market Trend with Boom Opportunities in Upcoming Years

    OpenAIRE

    Rahul Gautam

    2018-01-01

    The global artificial intelligence in healthcare market is expected to observe an extensive growth in the coming years, led by growing need for precision medicine, increasing application of big data in healthcare industry, and rising need for coordination between healthcare workforce and patients. The products in the global market are categorized as hardware, software and services, with software being the largest contributor in 2016 and the category is also projected to witness significant gr...

  4. Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

    Science.gov (United States)

    Krishnan, G. S.

    1997-01-01

    A cost effective model which uses the artificial intelligence techniques in the selection and approval of parts is presented. The knowledge which is acquired from the specialists for different part types are represented in a knowledge base in the form of rules and objects. The parts information is stored separately in a data base and is isolated from the knowledge base. Validation, verification and performance issues are highlighted.

  5. Artificial intelligence (AI)-based relational matching and multimodal medical image fusion: generalized 3D approaches

    Science.gov (United States)

    Vajdic, Stevan M.; Katz, Henry E.; Downing, Andrew R.; Brooks, Michael J.

    1994-09-01

    A 3D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on Artificial Intelligence paradigms--in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and segmented into non-touching and non-overlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a `goodness' of matching function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centers of gravity, images are ready for fusion and visualization into a single 3D image of higher clarity.

  6. Some applications of AI [Artificial Intelligence] to the problems of accelerator physics

    International Nuclear Information System (INIS)

    Higo, T.; Shoaee, H.; Spencer, J.E.

    1986-09-01

    Failure of orbit correction schemes to recognize betatron oscillation patterns obvious to any machine operator is a good problem with which to analyze the uses of Artificial Intelligence and the roles and relationships of operators, control systems and machines. Because such error modes are very common, their generalization could provide an efficient machine optimization and control strategy. A set of first-order, unitary transformations connecting canonical variables through measured results are defined which can either be compared to design for commissioning or to past results for 'golden orbit' operation. Because these relate directly to hardware variables, the method is simple, fast and direct. It has implications for machine design, controls, monitoring and feedback. Chronological analysis of such machine signatures can predict or provide a variety of information such as mean time to failure, failure modes and fast feedback or feedforward for optimizing figures of merit such as luminosity or current transmission. The use of theoretical and empirical scaling relations for such problems is discussed in terms of various figures of merit, the variables on which they depend as well as their functional dependences

  7. Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

    Science.gov (United States)

    Krishnan, Govindarajapuram Subramaniam

    1997-12-01

    The National Aeronautics & Space Administration (NASA), the European Space Agency (ESA), and the Canadian Space Agency (CSA) missions involve the performance of scientific experiments in Space. Instruments used in such experiments are fabricated using electronic parts such as microcircuits, inductors, capacitors, diodes, transistors, etc. For instruments to perform reliably the selection of commercial parts must be monitored and strictly controlled. The process used to achieve this goal is by a manual review and approval of every part used to build the instrument. The present system to select and approve parts for space applications is manual, inefficient, inconsistent, slow and tedious, and very costly. In this dissertation a computer based decision support model is developed for implementing this process using artificial intelligence concepts based on the current information (expert sources). Such a model would result in a greater consistency, accuracy, and timeliness of evaluation. This study presents the methodology of development and features of the model, and the analysis of the data pertaining to the performance of the model in the field. The model was evaluated for three different part types by experts from three different space agencies. The results show that the model was more consistent than the manual evaluation for all part types considered. The study concludes with the cost and benefits analysis of implementing the models and shows that implementation of the model will result in significant cost savings. Other implementation details are highlighted.

  8. General general game AI

    OpenAIRE

    Togelius, Julian; Yannakakis, Georgios N.; 2016 IEEE Conference on Computational Intelligence and Games (CIG)

    2016-01-01

    Arguably the grand goal of artificial intelligence research is to produce machines with general intelligence: the capacity to solve multiple problems, not just one. Artificial intelligence (AI) has investigated the general intelligence capacity of machines within the domain of games more than any other domain given the ideal properties of games for that purpose: controlled yet interesting and computationally hard problems. This line of research, however, has so far focuse...

  9. Tweeting AI: Perceptions of AI-Tweeters (AIT) vs Expert AI-Tweeters (EAIT)

    OpenAIRE

    Manikonda, Lydia; Dudley, Cameron; Kambhampati, Subbarao

    2017-01-01

    With the recent advancements in Artificial Intelligence (AI), various organizations and individuals started debating about the progress of AI as a blessing or a curse for the future of the society. This paper conducts an investigation on how the public perceives the progress of AI by utilizing the data shared on Twitter. Specifically, this paper performs a comparative analysis on the understanding of users from two categories -- general AI-Tweeters (AIT) and the expert AI-Tweeters (EAIT) who ...

  10. AI and health

    OpenAIRE

    Martin Anderson

    2018-01-01

    ntelligence refers to the ability of an individual to learn or understand something, or to deal with a new situation. When a machine or software exhibits such characteristics, it is referred to as artificial intelligence (AI). Artificial Intelligence is therefore defined as the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

  11. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

    The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

  12. An analysis of the application of AI to the development of intelligent aids for flight crew tasks

    Science.gov (United States)

    Baron, S.; Feehrer, C.

    1985-01-01

    This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research.

  13. Modeling Progress in AI

    OpenAIRE

    Brundage, Miles

    2015-01-01

    Participants in recent discussions of AI-related issues ranging from intelligence explosion to technological unemployment have made diverse claims about the nature, pace, and drivers of progress in AI. However, these theories are rarely specified in enough detail to enable systematic evaluation of their assumptions or to extrapolate progress quantitatively, as is often done with some success in other technological domains. After reviewing relevant literatures and justifying the need for more ...

  14. Introducing AI into MEMS can lead us to brain-computer interfaces and super-human intelligence

    OpenAIRE

    Sanders, David

    2009-01-01

    Last year, I spoke about the progress being made in machine intelligence (Sanders, 2008c) and with sensors and networks of sensors (Sanders, 2008b). Earlier this year (in this journal) I spoke about ambient-intelligence, rapid-prototyping and the role of humans in the factories of the future (Sanders, 2009a). I addressed new applications and technologies such as merging machines with human beings, micro-electromechanics, electro-mechanical systems that can be personalized, smarter than human ...

  15. AI 3D Cybug Gaming

    OpenAIRE

    Ahmed, Zeeshan

    2010-01-01

    In this short paper I briefly discuss 3D war Game based on artificial intelligence concepts called AI WAR. Going in to the details, I present the importance of CAICL language and how this language is used in AI WAR. Moreover I also present a designed and implemented 3D War Cybug for AI WAR using CAICL and discus the implemented strategy to defeat its enemies during the game life.

  16. AIS authentication

    CERN Multimedia

    2006-01-01

    Users are invited to use the NICE password for AIS authentication. As announced in CNL June-August 2006 (see http://www.cerncourier.com/articles/cnl/3/6/14/1) it is possible to use the NICE username and password to log on to AIS. The procedure is now fully operational and users can themselves reset the AIS password such that the NICE password will be used for authentication required by AIS applications. We strongly recommend CERN users who have a NICE account (this is the case of most users) to do this, with the objective to reduce the number of passwords they need to remember. This can be achieved very easily, directly from the Change Password option on the AIS login (https://aislogin.cern.ch/). Users should just select the '[Change Password]' option displayed at the bottom of the page, provide the 'Old Password' and then click on the button 'Use Nice password' followed by 'Submit'. Change Password option on the AIS login windowSetting the AIS password - Use Nice Password It should be noted that the proce...

  17. Intelligent Data Understanding for Architecture Analysis of Entry, Descent, and Landing

    Data.gov (United States)

    National Aeronautics and Space Administration — Because Entry, Descent and Landing (EDL) system validations are limited in Earth environments, these technologies rely heavily on models and analysis tools to...

  18. AI and Mathematical Education

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2012-01-01

    Full Text Available From ancient times, the history of human beings has developed by a succession of steps and sometimes jumps, until reaching the relative sophistication of the modern brain and culture. Researchers are attempting to create systems that mimic human thinking, understand speech, or beat the best human chess player. Understanding the mechanisms of intelligence, and creating intelligent artifacts are the twin goals of Artificial Intelligence (AI. Great mathematical minds have played a key role in AI in recent years; to name only a few: Janos Neumann (also known as John von Neumann, Konrad Zuse, Norbert Wiener, Claude E. Shannon, Alan M. Turing, Grigore Moisil, Lofti A. Zadeh, Ronald R. Yager, Michio Sugeno, Solomon Marcus, or Lászlo A. Barabási. Introducing the study of AI is not merely useful because of its capability for solving difficult problems, but also because of its mathematical nature. It prepares us to understand the current world, enabling us to act on the challenges of the future.

  19. The handbook of artificial intelligence

    CERN Document Server

    Barr, Avron

    1982-01-01

    The Handbook of Artificial Intelligence, Volume II focuses on the improvements in artificial intelligence (AI) and its increasing applications, including programming languages, intelligent CAI systems, and the employment of AI in medicine, science, and education. The book first elaborates on programming languages for AI research and applications-oriented AI research. Discussions cover scientific applications, teiresias, applications in chemistry, dependencies and assumptions, AI programming-language features, and LISP. The manuscript then examines applications-oriented AI research in medicine

  20. Knowledge Discovery, Integration and Communication for Extreme Weather and Flood Resilience Using Artificial Intelligence: Flood AI Alpha

    Science.gov (United States)

    Demir, I.; Sermet, M. Y.

    2016-12-01

    Nobody is immune from extreme events or natural hazards that can lead to large-scale consequences for the nation and public. One of the solutions to reduce the impacts of extreme events is to invest in improving resilience with the ability to better prepare, plan, recover, and adapt to disasters. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This abstracts presents our project on developing a resilience framework for flooding to improve societal preparedness with objectives; (a) develop a generalized ontology for extreme events with primary focus on flooding; (b) develop a knowledge engine with voice recognition, artificial intelligence, natural language processing, and inference engine. The knowledge engine will utilize the flood ontology and concepts to connect user input to relevant knowledge discovery outputs on flooding; (c) develop a data acquisition and processing framework from existing environmental observations, forecast models, and social networks. The system will utilize the framework, capabilities and user base of the Iowa Flood Information System (IFIS) to populate and test the system; (d) develop a communication framework to support user interaction and delivery of information to users. The interaction and delivery channels will include voice and text input via web-based system (e.g. IFIS), agent-based bots (e.g. Microsoft Skype, Facebook Messenger), smartphone and augmented reality applications (e.g. smart assistant), and automated web workflows (e.g. IFTTT, CloudWork) to open the knowledge discovery for flooding to thousands of community extensible web workflows.

  1. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  2. Citadels AI

    OpenAIRE

    Pekárek, Jakub

    2015-01-01

    The aim of this thesis is to implement a playable version of the game Citadels with console interface, and to use it for analysis of the game's properties and development of artificial intelligence. This thesis includes an analysis of strategies, a scheme for their design, an organization of turn processing, a model of intelligence implementation and testing tools. A number of approaches to specific moves have been developed, all of which achieved positive impact on overall intelligence perfo...

  3. The Potential of AI Techniques for Remote Sensing

    Science.gov (United States)

    Estes, J. E.; Sailer, C. T. (Principal Investigator); Tinney, L. R.

    1984-01-01

    The current status of artificial intelligence AI technology is discussed along with imagery data management, database interrogation, and decision making. Techniques adapted from the field of artificial intelligence (AI) have significant, wide ranging impacts upon computer-assisted remote sensing analysis. AI based techniques offer a powerful and fundamentally different approach to many remote sensing tasks. In addition to computer assisted analysis, AI techniques can also aid onboard spacecraft data processing and analysis and database access and query.

  4. Towards a science of integrated AI and Robotics

    OpenAIRE

    Rajan, Kanna; Saffiotti, Alessandro

    2017-01-01

    The early promise of the impact of machine intelligence did not involve the partitioning of the nascent field of Artificial Intelligence. The founders of AI envisioned the notion of embedded intelligence as being conjoined between perception, reasoning and actuation. Yet over the years the fields of AI and Robotics drifted apart. Practitioners of AI focused on problems and algorithms abstracted from the real world. Roboticists, generally with a background in mechanical and electrical engineer...

  5. Artificial Intelligence (AI) Flight Advisor

    Data.gov (United States)

    National Aeronautics and Space Administration — This research effort applies Deep Learning to contingency management.   Many historic aircraft accidents would have been avoidable if the pilot had better diagnosis...

  6. harnessing_ai_20180319.pptx

    OpenAIRE

    Johnson, Matthew

    2018-01-01

    There have been great strides made in Artificial Intelligence in recent years, but it is often not clear how to apply these recent advances to new problems. In this talk I propose one method of thinking about problems in the sciences and how to find the right AI techniques to aid in research.

  7. Tweeting AI: Perceptions of Lay vs Expert Twitterati

    OpenAIRE

    Manikonda, Lydia; Kambhampati, Subbarao

    2017-01-01

    With the recent advancements in Artificial Intelligence (AI), various organizations and individuals are debating about the progress of AI as a blessing or a curse for the future of the society. This paper conducts an investigation on how the public perceives the progress of AI by utilizing the data shared on Twitter. Specifically, this paper performs a comparative analysis on the understanding of users belonging to two categories -- general AI-Tweeters (AIT) and expert AI-Tweeters (EAIT) who ...

  8. The Relevance of AI Research to CAI.

    Science.gov (United States)

    Kearsley, Greg P.

    This article provides a tutorial introduction to Artificial Intelligence (AI) research for those involved in Computer Assisted Instruction (CAI). The general theme is that much of the current work in AI, particularly in the areas of natural language understanding systems, rule induction, programming languages, and socratic systems, has important…

  9. The present status of artificial intelligence for nuclear power plants

    International Nuclear Information System (INIS)

    Suda, Kazunori; Yonekawa, Tuyoshi; Yoshikawa, Shinji; Hasegawa, Makoto

    1999-03-01

    JNC researches the development of distributed intelligence systems at autonomous plants and intelligent support system at nuclear power plant. This report describes the present status of artificial intelligence (AI) technologies for this research. The following are represented in this report: present research study for AI, Implementation of AI system and application of AI technologies in the field of industries, requirement for AI by industries, problems of social acceptance for AI. A development of AI systems has to be motivated both by current status of AI and requirement for AI. Furthermore a problem of social acceptance for AI technologies has to be solved for using AI systems in society. (author)

  10. SMARTER THAN YOUR AVERAGE SENSOR: AIS SENSOR THAT INTELLIGENTLY RE-TRANSMITS MEANINGFUL INFORMATION DERIVED FROM RAWAIS DATA IN NETWORK LIMITED AREAS

    Directory of Open Access Journals (Sweden)

    R. G. V. Meyer

    2017-11-01

    Full Text Available AIS is a transponder based, anti-collision system used by the majority of ocean traffic. Ships regularly transmit their identity, position and speed. The information used to populate the AIS fields come from ship based sensors, such as GPS, and user populated fields, such as the vessels name and MMSI number. These fields are susceptible to spoofing and can be changed to hide the identity or location of a vessel. This is often done to disguise the vessel as a different class to avoid inspections or to enter a protected area without raising alarms. The AIS system has found great utility in monitoring global shipping trends and traffic but this was never intended when the protocol was designed. Docked vessels still transmit messages regularly that contain no new information. These, and other redundant messages, are still transmitted and stored. In situations where a sensor is remote and has limited access to the Internet this can become costly. The Smart-AIS sensor records all incoming messages locally and makes a decision on whether the message is of special interest or not. Messages of interest are re-transmitted to an external AIS database.

  11. Humans and Machines in the Evolution of AI in Korea

    OpenAIRE

    Zhang, Byoung-Tak

    2016-01-01

    Artificial intelligence in Korea is currently prospering. The media is regularly reporting AI-enabled products such as smart advisors, personal robots, autonomous cars, and human-level intelligence machines. The IT industry is investing in deep learning and AI to maintain the global competitive edge in their services and products. The Ministry of Science, ICT, and Future Planning (MSIP) has launched new funding programs in AI and cognitive science to implement the government’s newly adopted e...

  12. AI in space: Past, present, and possible futures

    Science.gov (United States)

    Rose, Donald D.; Post, Jonathan V.

    1992-01-01

    While artificial intelligence (AI) has become increasingly present in recent space applications, new missions being planned will require even more incorporation of AI techniques. In this paper, we survey some of the progress made to date in implementing such programs, some current directions and issues, and speculate about the future of AI in space scenarios. We also provide examples of how thinkers from the realm of science fiction have envisioned AI's role in various aspects of space exploration.

  13. Artificial Intelligence and Science Education.

    Science.gov (United States)

    Good, Ron

    1987-01-01

    Defines artificial intelligence (AI) in relation to intelligent computer-assisted instruction (ICAI) and science education. Provides a brief background of AI work, examples of expert systems, examples of ICAI work, and addresses problems facing AI workers that have implications for science education. Proposes a revised model of the Karplus/Renner…

  14. AI Based Personal Learning Environments: Directions for Long Term Research. AI Memo 384.

    Science.gov (United States)

    Goldstein, Ira P.; Miller, Mark L.

    The application of artificial intelligence (AI) techniques to the design of personal learning environments is an enterprise of both theoretical and practical interest. In the short term, the process of developing and testing intelligent tutoring programs serves as a new experimental vehicle for exploring alternative cognitive and pedagogical…

  15. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  16. Reviewing the development of an artificial intelligence based risk program

    International Nuclear Information System (INIS)

    Dixon, B.W.; Hinton, M.F.

    1985-01-01

    A successful application of nonconventional programming methods has been achieved in computer-assisted probabilistic risk assessment (PRA). The event tree sequence importance calculator, SQUIMP, provides for prompted data entry, generic expansion, on-line pruning, boolean reductions, and importance factor selection. SQUIMP employs constructs typically found in artificial intelligence (AI) programs. The development history of SQUIMP is outlined and its internal structure described as background for a discussion on the applicability of symbolic programming methods in PRA

  17. Beyond AI: Artificial Dreams Conference

    CERN Document Server

    Zackova, Eva; Kelemen, Jozef; Beyond Artificial Intelligence : The Disappearing Human-Machine Divide

    2015-01-01

    This book is an edited collection of chapters based on the papers presented at the conference “Beyond AI: Artificial Dreams” held in Pilsen in November 2012. The aim of the conference was to question deep-rooted ideas of artificial intelligence and cast critical reflection on methods standing at its foundations.  Artificial Dreams epitomize our controversial quest for non-biological intelligence, and therefore the contributors of this book tried to fully exploit such a controversy in their respective chapters, which resulted in an interdisciplinary dialogue between experts from engineering, natural sciences and humanities.   While pursuing the Artificial Dreams, it has become clear that it is still more and more difficult to draw a clear divide between human and machine. And therefore this book tries to portrait such an image of what lies beyond artificial intelligence: we can see the disappearing human-machine divide, a very important phenomenon of nowadays technological society, the phenomenon which i...

  18. AI Researchers, Video Games Are Your Friends!

    OpenAIRE

    Togelius, Julian

    2016-01-01

    If you are an artificial intelligence researcher, you should look to video games as ideal testbeds for the work you do. If you are a video game developer, you should look to AI for the technology that makes completely new types of games possible. This chapter lays out the case for both of these propositions. It asks the question "what can video games do for AI", and discusses how in particular general video game playing is the ideal testbed for artificial general intelligence research. It the...

  19. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  20. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  1. Artificial Intelligence and Expert Systems.

    Science.gov (United States)

    Wilson, Harold O.; Burford, Anna Marie

    1990-01-01

    Delineates artificial intelligence/expert systems (AI/ES) concepts; provides an exposition of some business application areas; relates progress; and creates an awareness of the benefits, limitations, and reservations of AI/ES. (Author)

  2. What Is Artificial Intelligence Anyway?

    Science.gov (United States)

    Kurzweil, Raymond

    1985-01-01

    Examines the past, present, and future status of Artificial Intelligence (AI). Acknowledges the limitations of AI but proposes possible areas of application and further development. Urges a concentration on the unique strengths of machine intelligence rather than a copying of human intelligence. (ML)

  3. Development of AI (Artificial Intelligence)-based simulation system for man-machine system behavior in accidental situations of nuclear power plant

    International Nuclear Information System (INIS)

    Yoshida, Kazuo; Yokobayashi, Masao; Tanabe, Fumiya; Kawase, Katumi.

    1996-01-01

    A prototype version of a computer simulation system named JACOS (JAeri COgnitive Simulation system) has been developed at JAERI (Japan Atomic Energy Research Institute) to simulate the man-machine system behavior in which both the cognitive behavior of a human operator and the plant behavior affect each other. The objectives of this system development is to provide man-machine system analysts with detailed information on the cognitive process of an operator and the plant behavior affected by operator's actions in accidental situations of an NPP (nuclear power plant). The simulation system consists of an operator model and a plant model which are coupled dynamically. The operator model simulates an operator's cognitive behavior in accidental situations based on the decision ladder model of Rasmussen, and is implemented using the AI-techniques of the distributed cooperative inference method with the so-called blackboard architecture. Rule-based behavior is simulated using knowledge representation with If-Then type of rules. Knowledge-based behavior is simulated using knowledge representation with MFM (Multilevel Flow Modeling) and qualitative reasoning method. Cognitive characteristics of attentional narrowing, limitation of short-term memory, and knowledge recalling from long-term memory are also modeled. The plant model of a 3-loop PWR is also developed using a best estimate thermal-hydraulic analysis code RELAP5/MOD2. Some simulations of incidents were performed to verify the human model. It was found that AI-techniques used in the human model are suitable to simulate the operator's cognitive behavior in an NPP accident. The models of cognitive characteristics were investigated in the effects on simulated results of cognitive behaviors. (author)

  4. Artificial Intelligence in Astronomy

    Science.gov (United States)

    Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

    2010-12-01

    From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

  5. Emotional intelligence as a predictor of academic performance in first-year accelerated graduate entry nursing students.

    Science.gov (United States)

    Fernandez, Ritin; Salamonson, Yenna; Griffiths, Rhonda

    2012-12-01

    To examine the association between trait emotional intelligence and learning strategies and their influence on academic performance among first-year accelerated nursing students. The study used a prospective survey design. A sample size of 81 students (100% response rate) who undertook the accelerated nursing course at a large university in Sydney participated in the study. Emotional intelligence was measured using the adapted version of the 144-item Trait Emotional Intelligence Questionnaire. Four subscales of the Motivated Strategies for Learning Questionnaire were used to measure extrinsic goal motivation, peer learning, help seeking and critical thinking among the students. The grade point average score obtained at the end of six months was used to measure academic achievement. The results demonstrated a statistically significant correlation between emotional intelligence scores and critical thinking (r = 0.41; p peer learning (r = 0.32; p academic achievement (β = 0.25; p = 0.023). In addition to their learning styles, higher levels of awareness and understanding of their own emotions have a positive impact on students' academic achievement. Higher emotional intelligence may lead students to pursue their interests more vigorously and think more expansively about subjects of interest, which could be an explanatory factor for higher academic performance in this group of nursing students. The concepts of emotional intelligence are central to clinical practice as nurses need to know how to deal with their own emotions as well as provide emotional support to patients and their families. It is therefore essential that these skills are developed among student nurses to enhance the quality of their clinical practice. © 2012 Blackwell Publishing Ltd.

  6. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  7. #%Applications of artificial intelligence in intelligent manufacturing: a review

    Institute of Scientific and Technical Information of China (English)

    #

    2017-01-01

    #%Based on research into the applications of artificial intelligence (AI) technology in the manufacturing industry in recent years, we analyze the rapid development of core technologies in the new era of 'Internet plus AI', which is triggering a great change in the models, means, and ecosystems of the manufacturing industry, as well as in the development of AI. We then propose new models, means, and forms of intelligent manufacturing, intelligent manufacturing system architecture, and intelligent man-ufacturing technology system, based on the integration of AI technology with information communications, manufacturing, and related product technology. Moreover, from the perspectives of intelligent manufacturing application technology, industry, and application demonstration, the current development in intelligent manufacturing is discussed. Finally, suggestions for the appli-cation of AI in intelligent manufacturing in China are presented.

  8. Discussion on AI Technology in Information Library Design

    OpenAIRE

    日比野, 省三; Shozo, HIBINO; 中京大学社会学部

    1987-01-01

    This paper deals with the discussion on the importance of AI (Artificial Intelligence) Technology in planning and designing a library information system in the near future. First of all, the history of Library and Information Science is reviewed and it is identified that the key technology in the future library will be AI as a mega-trend. After reviewing the concepts of AI technology, a model of a Knowledge-Base system is discussed as a case study, using micro-PROLOG.

  9. An Immune Agent for Web-Based AI Course

    Science.gov (United States)

    Gong, Tao; Cai, Zixing

    2006-01-01

    To overcome weakness and faults of a web-based e-learning course such as Artificial Intelligence (AI), an immune agent was proposed, simulating a natural immune mechanism against a virus. The immune agent was built on the multi-dimension education agent model and immune algorithm. The web-based AI course was comprised of many files, such as HTML…

  10. AI applications in sheet metal forming

    CERN Document Server

    Hussein, Hussein

    2017-01-01

    This book comprises chapters on research work done around the globe in the area of artificial intelligence (AI) applications in sheet metal forming. The first chapter offers an introduction to various AI techniques and sheet metal forming, while subsequent chapters describe traditional procedures/methods used in various sheet metal forming processes, and focus on the automation of those processes by means of AI techniques, such as KBS, ANN, GA, CBR, etc. Feature recognition and the manufacturability assessment of sheet metal parts, process planning, strip-layout design, selecting the type and size of die components, die modeling, and predicting die life are some of the most important aspects of sheet metal work. Traditionally, these activities are highly experience-based, tedious and time consuming. In response, researchers in several countries have applied various AI techniques to automate these activities, which are covered in this book. This book will be useful for engineers working in sheet metal industri...

  11. The Potential Role of Artificial Intelligence Technology in Education.

    Science.gov (United States)

    Salem, Abdel-Badeeh M.

    The field of Artificial Intelligence (AI) and Education has traditionally a technology-based focus, looking at the ways in which AI can be used in building intelligent educational software. In addition AI can also provide an excellent methodology for learning and reasoning from the human experiences. This paper presents the potential role of AI in…

  12. Artificial Intelligence Applications for Education: Promise, ...Promises.

    Science.gov (United States)

    Adams, Dennis M.; Hamm, Mary

    1988-01-01

    Surveys the current status of artificial intelligence (AI) technology. Discusses intelligent tutoring systems, robotics, and applications for educators. Likens the status of AI at present to that of aviation in the very early 1900s. States that educators need to be involved in future debates concerning AI. (CW)

  13. Reflection on robotic intelligence

    NARCIS (Netherlands)

    Bartneck, C.

    2006-01-01

    This paper reflects on the development or robots, both their physical shape as well as their intelligence. The later strongly depends on the progress made in the artificial intelligence (AI) community which does not yet provide the models and tools necessary to create intelligent robots. It is time

  14. Brain Intelligence: Go Beyond Artificial Intelligence

    OpenAIRE

    Lu, Huimin; Li, Yujie; Chen, Min; Kim, Hyoungseop; Serikawa, Seiichi

    2017-01-01

    Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication ...

  15. AI, automation and the Flight Telerobotic Servicer

    Science.gov (United States)

    Goforth, Andre; Dominy, Robert

    1988-01-01

    A NASA study for the preliminary definition of a teleoperated robotic device has been recently completed. The Fligt Telerobotic Servicer (FTS) will be used to assist astronauts in many of the on-board tasks of assembly, maintenance, servicing, and inspection of the Space Station. The role of artificial intelligence (AI) in furthering the FTS automation capabilities and, hence, extending its capacity for growth and evolution is discussed. Relevant system engineering issues are identified, and an approach for insertion of AI technology is presented in terms of the NASA/NBS Standard Reference Model control architecture NASREM.

  16. Artificial Intelligence: The Expert Way.

    Science.gov (United States)

    Bitter, Gary G.

    1989-01-01

    Discussion of artificial intelligence (AI) and expert systems focuses on their use in education. Characteristics of good expert systems are explained; computer software programs that contain applications of AI are described, highlighting one used to help educators identify learning-disabled students; and the future of AI is discussed. (LRW)

  17. On how AI & Law can help autonomous systems obey the law: a position paper

    NARCIS (Netherlands)

    Prakken, Hendrik

    2016-01-01

    In this position paper I discuss to what extent current and past AI & law research is relevant for research on autonomous intelligent systems that exhibit legally relevant behaviour. After a brief review of the history of AI & law, I will compare the problems faced by autonomous intelligent systems

  18. Medical applications of artificial intelligence

    CERN Document Server

    Agah, Arvin

    2013-01-01

    Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Ap

  19. Elementary epistemological features of machine intelligence

    OpenAIRE

    Horvat, Marko

    2008-01-01

    Theoretical analysis of machine intelligence (MI) is useful for defining a common platform in both theoretical and applied artificial intelligence (AI). The goal of this paper is to set canonical definitions that can assist pragmatic research in both strong and weak AI. Described epistemological features of machine intelligence include relationship between intelligent behavior, intelligent and unintelligent machine characteristics, observable and unobservable entities and classification of in...

  20. T'ai Chi

    Science.gov (United States)

    ... are different styles of t'ai chi, including: Chen style Hao (or Wu Shi) style Hu Lei ... medical advice, diagnoses, and treatment, consult your doctor. © 1995- The Nemours Foundation. All rights reserved. Images provided ...

  1. Intelligent Tutoring System: A Tool for Testing the Research Curiosities of Artificial Intelligence Researchers

    Science.gov (United States)

    Yaratan, Huseyin

    2003-01-01

    An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…

  2. The First Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI '06)

    OpenAIRE

    Augusto, Juan Carlos; Shapiro, Daniel

    2007-01-01

    The first annual workshop on the role of AI in ambient intelligence was held in Riva de Garda, Italy, on August 29, 2006. The workshop was colocated with the European Conference on Artificial Intelligence (ECAI 2006). It provided an opportunity for researchers in a variety of AI subfields together with representatives of commercial interests to explore ambient intelligence technology and applications.

  3. NASA space station automation: AI-based technology review

    Science.gov (United States)

    Firschein, O.; Georgeff, M. P.; Park, W.; Neumann, P.; Kautz, W. H.; Levitt, K. N.; Rom, R. J.; Poggio, A. A.

    1985-01-01

    Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures.

  4. It Takes Two to Tango: Towards Theory of AI's Mind

    OpenAIRE

    Chandrasekaran, Arjun; Yadav, Deshraj; Chattopadhyay, Prithvijit; Prabhu, Viraj; Parikh, Devi

    2017-01-01

    Theory of Mind is the ability to attribute mental states (beliefs, intents, knowledge, perspectives, etc.) to others and recognize that these mental states may differ from one's own. Theory of Mind is critical to effective communication and to teams demonstrating higher collective performance. To effectively leverage the progress in Artificial Intelligence (AI) to make our lives more productive, it is important for humans and AI to work well together in a team. Traditionally, there has been m...

  5. Areal Informations Systemet - AIS

    DEFF Research Database (Denmark)

    Nielsen, K.; Stjernholm, M.; Olsen, B. Ø.

    Forord: Denne rapport giver en kort beskrivelse af Areal Informations Systemet (AIS), som er et databasesystem med natur- og miljødata, som kan stedfæstes geografisk. Projektet er gennemført i perioden 1996-2000 som et samarbejdsprojekt mellem Danmarks Miljøundersøgelser (DMU), Danmarks og...... og enkeltpersoner med interesse for natur- og miljøforhold i Danmark. Yderligere oplysninger om Areal Informations Systemet, herunder adgangsforhold, kan fås på DMU's hjemmeside med følgende adresse: http://ais.dmu.dk/ Projektet er finansieret af Miljø- og Energiministeriet, mens en række...... (planlægning, beskyttelse), geologi (overfladegeologi og marin geologi), samt marin dybdemodel. # Etablering af dataadgang for Miljø- og Energiministeriets institutioner til AIS-data. # Afprøvning af systemet i forhold til konkrete projekter. # Formidling af produkterne til brugerkredsen....

  6. MassAI

    DEFF Research Database (Denmark)

    2011-01-01

    A software tool for general analysis and data-mining of mass-spectrometric datasets. The program features a strong emphasis on scan-by-scan identification and results-transparency. MassAI also accommodates residue level analysis of labelled runs, e.g. HDX.......A software tool for general analysis and data-mining of mass-spectrometric datasets. The program features a strong emphasis on scan-by-scan identification and results-transparency. MassAI also accommodates residue level analysis of labelled runs, e.g. HDX....

  7. ARTIFICIAL INTELLIGENCE: APPLICATIONS AND FUTURE

    OpenAIRE

    Ellur Anand; S. G. Varun Kumar

    2017-01-01

    Artificial Intelligence (AI) or Augmented Intelligence happens to be the most talked about technology that would have a major impact on the way the current day world functions. The next step in evolution of digital world is AI. The safety of the world with more and more use of AI also becomes necessity. Safety rules and regulations of the digital world need to be drafted and redrafted as AI evolves and becomes a new normal in every one’s life just as mobile phone has become in the current sce...

  8. Artificial Intelligence.

    Science.gov (United States)

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.

  9. Applications of Artificial Intelligence in Education--A Personal View.

    Science.gov (United States)

    Richer, Mark H.

    1985-01-01

    Discusses: how artificial intelligence (AI) can advance education; if the future of software lies in AI; the roots of intelligent computer-assisted instruction; protocol analysis; reactive environments; LOGO programming language; student modeling and coaching; and knowledge-based instructional programs. Numerous examples of AI programs are cited.…

  10. Quo vadis, Intelligent Machine?

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2010-09-01

    Full Text Available Artificial Intelligence (AI is a branch of computer science concerned with making computers behave like humans. At least this was the original idea. However, it turned out that this is no task easy to be solved. This article aims to give a comprehensible review on the last 60 years of artificial intelligence taking a philosophical viewpoint. It is outlined what happened so far in AI, what is currently going on in this research area, and what can be expected in future. The goal is to mediate an understanding for the developments and changes in thinking in course of time about how to achieve machine intelligence. The clear message is that AI has to join forces with neuroscience and other brain disciplines in order to make a step towards the development of truly intelligent machines.

  11. Principles of artificial intelligence

    CERN Document Server

    Nilsson, Nils J

    1980-01-01

    A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

  12. General Video Game AI: Learning from Screen Capture

    OpenAIRE

    Kunanusont, Kamolwan; Lucas, Simon M.; Perez-Liebana, Diego

    2017-01-01

    General Video Game Artificial Intelligence is a general game playing framework for Artificial General Intelligence research in the video-games domain. In this paper, we propose for the first time a screen capture learning agent for General Video Game AI framework. A Deep Q-Network algorithm was applied and improved to develop an agent capable of learning to play different games in the framework. After testing this algorithm using various games of different categories and difficulty levels, th...

  13. Launching AI in NASA ground systems

    Science.gov (United States)

    Perkins, Dorothy C.; Truszkowski, Walter F.

    1990-01-01

    This paper will discuss recent operational successes in implementing expert systems to support the complex functions of NASA mission control systems at the Goddard Space Flight Center, including fault detection and diagnosis for real time and engineering analysis functions in the Cosmic Background Explorer and Gamma Ray Observatory missions and automation of resource planning and scheduling functions for various missions. It will also discuss ongoing developments and prototypes that will lead to increasingly sophisticated applications of artificial intelligence. These include the use of neural networks to perform telemetry monitoring functions, the implementation of generic expert system shells that can be customized to telemetry handling functions specific to NASA control centers, the applications of AI in training and user support, the long-term potential of implementing systems based around distributed, cooperative problem solving, and the use of AI to control and assist system development activities.

  14. AI systems approach in particle accelerators

    International Nuclear Information System (INIS)

    Kataria, S.K.; Bhagwat, P.V.; Kori, S.A.

    1992-01-01

    The large particle accelerators machines like pelletron accelerator at Tata Institute of Fundamental Research (T.I.F.R) have several levels of controls with operators responsible for overall global control decisions and closed loop feedback controllers for relatively small subsystems of the machines. As the accelerator machines are becoming more complicated and the requirements more stringent, there is a need to provide the operators with an artificial intelligence (AI) system to aid in the tuning the machine and in failure diagnosis. There are few major areas in the pelletron operation, which can be done more efficiently using AI systems approach so that useful beam is available for much more time: 1) Accelerator Conditioning, 2) Accelerator Tuning, and 3) Maintaining the Tune beams. The feasibility study for using expert system for above areas and also for safety evaluation of the various subsystems is carried out. (author). 10 refs., 4 figs

  15. Managing bioengineering complexity with AI techniques.

    Science.gov (United States)

    Beal, Jacob; Adler, Aaron; Yaman, Fusun

    2016-10-01

    Our capabilities for systematic design and engineering of biological systems are rapidly increasing. Effectively engineering such systems, however, requires the synthesis of a rapidly expanding and changing complex body of knowledge, protocols, and methodologies. Many of the problems in managing this complexity, however, appear susceptible to being addressed by artificial intelligence (AI) techniques, i.e., methods enabling computers to represent, acquire, and employ knowledge. Such methods can be employed to automate physical and informational "routine" work and thus better allow humans to focus their attention on the deeper scientific and engineering issues. This paper examines the potential impact of AI on the engineering of biological organisms through the lens of a typical organism engineering workflow. We identify a number of key opportunities for significant impact, as well as challenges that must be overcome. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  16. Artificial Intelligence, Counseling, and Cognitive Psychology.

    Science.gov (United States)

    Brack, Greg; And Others

    With the exception of a few key writers, counselors largely ignore the benefits that Artificial Intelligence (AI) and Cognitive Psychology (CP) can bring to counseling. It is demonstrated that AI and CP can be integrated into the counseling literature. How AI and CP can offer new perspectives on information processing, cognition, and helping is…

  17. AIS ASM Operational Integration Plan

    Science.gov (United States)

    2013-08-01

    Rack mount computer AIS Radio Interface Ethernet Switch 192.168.0.x Firewall Cable Modem 192.168.0.1 VTS Accred. Boundary AIS ASM Operational... AIS ASM Operational Integration Plan Distribution Statement A: Approved for public release; distribution is unlimited. August 2013 Report No...CD-D-07-15 AIS ASM Operational Integration Plan ii UNCLAS//Public | CG-926 R&DC | I. Gonin, et al. | Public August 2013 N O T I C

  18. The National Artificial Intelligence Research And Development Strategic Plan

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — Executive Summary: Artificial intelligence (AI) is a transformative technology that holds promise for tremendous societal and economic benefit. AI has the potential...

  19. Exploring AI Language Assistants with Primary EFL Students

    Science.gov (United States)

    Underwood, Joshua

    2017-01-01

    The main objective of this study was to identify ways to incorporate voice-driven Artificial Intelligence (AI) effectively in classroom language learning. This nine month teacher-led design research study employed technology probes (Amazon's Alexa, Apple's Siri, Google voice search) and co-design methods with a class of primary age English as a…

  20. AI/Simulation Fusion Project at Lawrence Livermore National Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Erickson, S.A.

    1984-04-25

    This presentation first discusses the motivation for the AI Simulation Fusion project. After discussing very briefly what expert systems are in general, what object oriented languages are in general, and some observed features of typical combat simulations, it discusses why putting together artificial intelligence and combat simulation makes sense. We then talk about the first demonstration goal for this fusion project.

  1. AI/Simulation Fusion Project at Lawrence Livermore National Laboratory

    International Nuclear Information System (INIS)

    Erickson, S.A.

    1984-01-01

    This presentation first discusses the motivation for the AI Simulation Fusion project. After discussing very briefly what expert systems are in general, what object oriented languages are in general, and some observed features of typical combat simulations, it discusses why putting together artificial intelligence and combat simulation makes sense. We then talk about the first demonstration goal for this fusion project

  2. AI AND SAR APPROACHES FOR PREDICTING CHEMICAL CARCINOGENICITY: SURVEY AND STATUS REPORT

    Science.gov (United States)

    A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoin...

  3. Building Explainable Artificial Intelligence Systems

    National Research Council Canada - National Science Library

    Core, Mark G; Lane, H. Chad; van Lent, Michael; Gomboc, Dave; Solomon, Steve; Rosenberg, Milton

    2006-01-01

    As artificial intelligence (AI) systems and behavior models in military simulations become increasingly complex, it has been difficult for users to understand the activities of computer-controlled entities...

  4. Artificial Intelligence, Employment, and Income

    OpenAIRE

    Nilsson, Nils J.

    1984-01-01

    Artificial intelligence (AI) will have profound societal effects. It promises potential benefits (and may also pose risks) in education, defense, business, law and science. In this article we explore how AI is likely to affect employment and the distribution of income. We argue that AI will indeed reduce drastically the need of human toil. We also note that some people fear the automation of work by machines and the resulting of unemployment. Yet, since the majority of us probably would rathe...

  5. Explanation and trust: what to tell the user in security and AI?

    NARCIS (Netherlands)

    Pieters, Wolter

    2010-01-01

    There is a common problem in artificial intelligence (AI) and information security. In AI, an expert system needs to be able to justify and explain a decision to the user. In information security, experts need to be able to explain to the public why a system is secure. In both cases, the goal of

  6. Explanation and trust: what to tell the user in security and AI?

    NARCIS (Netherlands)

    Pieters, Wolter

    There is a common problem in artificial intelligence (AI) and information security. In AI, an expert system needs to be able to justify and explain a decision to the user. In information security, experts need to be able to explain to the public why a system is secure. In both cases, an important

  7. Development and application of AI technology to plant operation and support

    International Nuclear Information System (INIS)

    Sackett, J.I.; Mott, J.E.

    1989-01-01

    This paper discusses a framework for the development and application of artificial intelligence (AI) technology in existing nuclear facilities and reviews the status of development. We consider those areas best addressed by AI technology, e.g., equipment diagnostics, sensor validation, and expert systems for procedural response or planning. A brief discussion of work in computer displays is also given. (orig./GL)

  8. An Empirical Study of AI Population Dynamics with Million-agent Reinforcement Learning

    OpenAIRE

    Yang, Yaodong; Yu, Lantao; Bai, Yiwei; Wang, Jun; Zhang, Weinan; Wen, Ying; Yu, Yong

    2017-01-01

    In this paper, we conduct an empirical study on discovering the ordered collective dynamics obtained by a population of artificial intelligence (AI) agents. Our intention is to put AI agents into a simulated natural context, and then to understand their induced dynamics at the population level. In particular, we aim to verify if the principles developed in the real world could also be used in understanding an artificially-created intelligent population. To achieve this, we simulate a large-sc...

  9. Artificial Intelligence: A Selected Bibliography.

    Science.gov (United States)

    Smith, Linda C., Comp.

    1984-01-01

    This 19-item annotated bibliography introducing the literature of artificial intelligence (AI) is arranged by type of material--handbook, books (general interest, textbooks, collected readings), journals and newsletters, and conferences and workshops. The availability of technical reports from AI laboratories at universities and private companies…

  10. Pavlovian, Skinner, and Other Behaviourists' Contributions to AI. Chapter 9

    Science.gov (United States)

    Kosinski, Withold; Zaczek-Chrzanowska, Dominika

    2007-01-01

    A version of the definition of intelligent behaviour will be supplied in the context of real and artificial systems. Short presentation of principles of learning, starting with Pavlovian s classical conditioning through reinforced response and operant conditioning of Thorndike and Skinner and finishing with cognitive learning of Tolman and Bandura will be given. The most important figures within behaviourism, especially those with contribution to AI, will be described. Some tools of artificial intelligence that act according to those principles will be presented. An attempt will be made to show when some simple rules for behaviour modifications can lead to a complex intelligent behaviour.

  11. Artificial Intelligence for the Bang! Game

    OpenAIRE

    Daniláková, Monika

    2017-01-01

    This work explores artificial intelligence (AI) algorithms for the game Bang!, a Wild West-themed card game created by Italian game designer Emiliano Sciarra. The aim of this work was to design three different AIs for this game and to compare them theoretically and experimentally. First, we analyzed game Bang! with regards to game theory, and researched some of the AI algorithms used in similar games. We then designed three different AIs algorithms and compared their advantages and disadvanta...

  12. Artificial Intelligence Research in Australia -- A Profile

    OpenAIRE

    Smith, Elizabeth; Whitelaw, John

    1987-01-01

    Does the United States have a 51st state called Australia? A superficial look at the artificial intelligence (AI) research being done here could give that impression. A look beneath the surface, though, indicates some fundamental differences and reveals a dynamic and rapidly expanding AI community. General awareness of the Australian AI research community has been growing slowly for some time. AI was once considered a bit esoteric -- the domain of an almost lunatic fringe- but the large gover...

  13. Northeast Artificial Intelligence Consortium Annual Report 1986. Volume 4. Part A. Hierarchical Region-Based Approach to Automatic Photointerpretation. Part B. Application of AI Techniques to Image Segmentation and Region Identification

    Science.gov (United States)

    1988-01-01

    MONITORING ORGANIZATION Northeast Artificial (If applicaole)nelincCostum(AcRome Air Development Center (COCU) Inteligence Consortium (NAIC)I 6c. ADDRESS...f, Offell RADC-TR-88-1 1, Vol IV (of eight) Interim Technical ReportS June 1988 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT 1986...13441-5700 EMENT NO NO NO ACCESSION NO62702F 5 8 71 " " over) I 58 27 13 " ൓ TITLE (Include Security Classification) NORTHEAST ARTIFICIAL INTELLIGENCE

  14. Artificial intelligence in medicine

    OpenAIRE

    Scerri, Mariella; Grech, Victor E.

    2016-01-01

    Various types of artificial intelligence programs are already available as consultants to physicians, and these help in medical diagnostics and treatment. At the time of writing, extant programs constitute “weak” AI—lacking in consciousness and intentionality. With AI currently making rapid progress in all domains, including those of healthcare, physicians face possible competitors—or worse, claims that doctors may become obsolete. We will explore the development of AI and robotics in medicin...

  15. Essentials of artificial intelligence

    CERN Document Server

    Ginsberg, Matt

    1993-01-01

    Since its publication, Essentials of Artificial Intelligence has beenadopted at numerous universities and colleges offering introductory AIcourses at the graduate and undergraduate levels. Based on the author'scourse at Stanford University, the book is an integrated, cohesiveintroduction to the field. The author has a fresh, entertaining writingstyle that combines clear presentations with humor and AI anecdotes. At thesame time, as an active AI researcher, he presents the materialauthoritatively and with insight that reflects a contemporary, first hand

  16. SDI satellite autonomy using AI and Ada

    Science.gov (United States)

    Fiala, Harvey E.

    1990-01-01

    The use of Artificial Intelligence (AI) and the programming language Ada to help a satellite recover from selected failures that could lead to mission failure are described. An unmanned satellite will have a separate AI subsystem running in parallel with the normal satellite subsystems. A satellite monitoring subsystem (SMS), under the control of a blackboard system, will continuously monitor selected satellite subsystems to become alert to any actual or potential problems. In the case of loss of communications with the earth or the home base, the satellite will go into a survival mode to reestablish communications with the earth. The use of an AI subsystem in this manner would have avoided the tragic loss of the two recent Soviet probes that were sent to investigate the planet Mars and its moons. The blackboard system works in conjunction with an SMS and a reconfiguration control subsystem (RCS). It can be shown to be an effective way for one central control subsystem to monitor and coordinate the activities and loads of many interacting subsystems that may or may not contain redundant and/or fault-tolerant elements. The blackboard system will be coded in Ada using tools such as the ABLE development system and the Ada Production system.

  17. Monitoring severe accidents using AI techniques

    International Nuclear Information System (INIS)

    No, Young Gyu; Ahn, Kwang Il; Kim, Ju Hyun; Na, Man Gyun; Lim, Dong Hyuk

    2012-01-01

    After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.

  18. Monitoring severe accidents using AI techniques

    Energy Technology Data Exchange (ETDEWEB)

    No, Young Gyu; Ahn, Kwang Il [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Kim, Ju Hyun; Na, Man Gyun [Dept. of Nuclear Engineering, Chosun University, Gwangju (Korea, Republic of); Lim, Dong Hyuk [Korea Institute of Nuclear Nonproliferation and Control, Daejon (Korea, Republic of)

    2012-05-15

    After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.

  19. AI techniques in geomagnetic storm forecasting

    Science.gov (United States)

    Lundstedt, Henrik

    This review deals with how geomagnetic storms can be predicted with the use of Artificial Intelligence (AI) techniques. Today many different Al techniques have been developed, such as symbolic systems (expert and fuzzy systems) and connectionism systems (neural networks). Even integrations of AI techniques exist, so called Intelligent Hybrid Systems (IHS). These systems are capable of learning the mathematical functions underlying the operation of non-linear dynamic systems and also to explain the knowledge they have learned. Very few such powerful systems exist at present. Two such examples are the Magnetospheric Specification Forecast Model of Rice University and the Lund Space Weather Model of Lund University. Various attempts to predict geomagnetic storms on long to short-term are reviewed in this article. Predictions of a month to days ahead most often use solar data as input. The first SOHO data are now available. Due to the high temporal and spatial resolution new solar physics have been revealed. These SOHO data might lead to a breakthrough in these predictions. Predictions hours ahead and shorter rely on real-time solar wind data. WIND gives us real-time data for only part of the day. However, with the launch of the ACE spacecraft in 1997, real-time data during 24 hours will be available. That might lead to the second breakthrough for predictions of geomagnetic storms.

  20. Artificial intelligence, expert systems, computer vision, and natural language processing

    Science.gov (United States)

    Gevarter, W. B.

    1984-01-01

    An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

  1. Social Intelligence Design in Ambient Intelligence

    NARCIS (Netherlands)

    Nijholt, Antinus; Stock, Oliviero; Stock, O.; Nishida, T.; Nishida, Toyoaki

    2009-01-01

    This Special Issue of AI and Society contains a selection of papers presented at the 6th Social Intelligence Design Workshop held at ITC-irst, Povo (Trento, Italy) in July 2007. Being the 6th in a series means that there now is a well-established and also a growing research area. The interest in

  2. Uncertainty in artificial intelligence

    CERN Document Server

    Levitt, TS; Lemmer, JF; Shachter, RD

    1990-01-01

    Clearly illustrated in this volume is the current relationship between Uncertainty and AI.It has been said that research in AI revolves around five basic questions asked relative to some particular domain: What knowledge is required? How can this knowledge be acquired? How can it be represented in a system? How should this knowledge be manipulated in order to provide intelligent behavior? How can the behavior be explained? In this volume, all of these questions are addressed. From the perspective of the relationship of uncertainty to the basic questions of AI, the book divides naturally i

  3. Neuroscience-Inspired Artificial Intelligence.

    Science.gov (United States)

    Hassabis, Demis; Kumaran, Dharshan; Summerfield, Christopher; Botvinick, Matthew

    2017-07-19

    The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less commonplace. In this article, we argue that better understanding biological brains could play a vital role in building intelligent machines. We survey historical interactions between the AI and neuroscience fields and emphasize current advances in AI that have been inspired by the study of neural computation in humans and other animals. We conclude by highlighting shared themes that may be key for advancing future research in both fields. Copyright © 2017. Published by Elsevier Inc.

  4. AI technology and automobile. ; Toward vehicle autonomy. AI gijutsu to jidosha. ; Sharyo no jiritsuka ni mukatte

    Energy Technology Data Exchange (ETDEWEB)

    Okuno, A. (Mazda Motor Corp., Hiroshima (Japan))

    1991-01-01

    This report describes the vehicle autonomy by using artificial intelligence (AI) technology. Owing to a remarkable progress of AI technology, it is forecasted that driving support system will be introduced into the market till 2000, and higher autonomous navigation system will be introduced since about 2010. Autonomous vehicles have capacities of recognizing the outside world and of navigating roads by themselves, and with their enfanced environment adaptability the road transportation in the future is expected to be much more safer than in the present. The autonomous vehicle can warn its driver of potential dangers and correct operational errors of the driver. In order to realize such autonomous vehicles, extensive researches on perception systems, decision making systems and driving support systems are needed. 9 refs., 10 figs., 1 tab.

  5. Application of AI technology to nuclear plant operations

    International Nuclear Information System (INIS)

    Sackett, J.I.

    1988-01-01

    In this paper, applications of Artificial Intelligence (AI) Technology to nuclear-power plant operation are reviewed. AI Technology is advancing rapidly and in the next five years is expected to enjoy widespread application to operation, maintenance, management and safety. Near term emphasis on a sensor validation, scheduling, alarm handling, and expert systems for procedural assistance. Ultimate applications are envisioned to culminate in autonomous control such as would be necessary for a power system in space, where automatic control actions are taken based upon reasoned conclusions regarding plant conditions, capability and control objectives

  6. AiGERM: A logic programming front end for GERM

    Science.gov (United States)

    Hashim, Safaa H.

    1990-01-01

    AiGerm (Artificially Intelligent Graphical Entity Relation Modeler) is a relational data base query and programming language front end for MCC (Mission Control Center)/STP's (Space Test Program) Germ (Graphical Entity Relational Modeling) system. It is intended as an add-on component of the Germ system to be used for navigating very large networks of information. It can also function as an expert system shell for prototyping knowledge-based systems. AiGerm provides an interface between the programming language and Germ.

  7. Enabling technologies and methods for the retro-fitting of AI software into NPPS

    International Nuclear Information System (INIS)

    Pymm, P.

    1994-01-01

    Scottish Nuclear have a number of plant monitoring and training applications at their operational nuclear power plant which could benefit from the introduction of artificial intelligence (AI) software. An outline of early work on two current AI developments in the areas of advanced operator aids and intelligent training is given. A generic workstation based engineering simulator (WES) which provides a prototyping environment for AI product application development and evaluation and development of human-computer interface (HCI) designs for plant installation is described. It is concluded that the WES architecture facilitates both migration of the prototype AI application to the plant and collaboration in the AI field between Scottish Nuclear and other organizations. (author). 1 ref., 6 figs

  8. Progress and Challenge of Artificial Intelligence

    Institute of Scientific and Technical Information of China (English)

    Zhong-Zhi Shi; Nan-Ning Zheng

    2006-01-01

    Artificial Intelligence (AI) is generally considered to be a subfield of computer science, that is concerned to attempt simulation, extension and expansion of human intelligence. Artificial intelligence has enjoyed tremendous success over the last fifty years. In this paper we only focus on visual perception, granular computing, agent computing, semantic grid. Human-level intelligence is the long-term goal of artificial intelligence. We should do joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. A new cross discipline intelligence science is undergoing a rapid development. Future challenges are given in final section.

  9. Future and Feature of Intelligent Systems and Their Societies

    African Journals Online (AJOL)

    2012-12-01

    Dec 1, 2012 ... work covered the consequences of having artificial intelligent systems with us in the near future. Keywords: intelligence, systems, artificial ... AI as science and technology to develop computers that can think and function in.

  10. An application of artificial intelligence for rainfall–runoff modeling

    Indian Academy of Sciences (India)

    This study proposes an application of two techniques of artificial intelligence (AI) ... (2006) applied rainfall–runoff modeling using ANN ... in artificial intelligence, engineering and science .... usually be estimated from a sample of observations.

  11. Application of AI methods to aircraft guidance and control

    Science.gov (United States)

    Hueschen, Richard M.; Mcmanus, John W.

    1988-01-01

    A research program for integrating artificial intelligence (AI) techniques with tools and methods used for aircraft flight control system design, development, and implementation is discussed. The application of the AI methods for the development and implementation of the logic software which operates with the control mode panel (CMP) of an aircraft is presented. The CMP is the pilot control panel for the automatic flight control system of a commercial-type research aircraft of Langley Research Center's Advanced Transport Operating Systems (ATOPS) program. A mouse-driven color-display emulation of the CMP, which was developed with AI methods and used to test the AI software logic implementation, is discussed. The operation of the CMP was enhanced with the addition of a display which was quickly developed with AI methods. The display advises the pilot of conditions not satisfied when a mode does not arm or engage. The implementation of the CMP software logic has shown that the time required to develop, implement, and modify software systems can be significantly reduced with the use of the AI methods.

  12. Artificial intelligence approaches in statistics

    International Nuclear Information System (INIS)

    Phelps, R.I.; Musgrove, P.B.

    1986-01-01

    The role of pattern recognition and knowledge representation methods from Artificial Intelligence within statistics is considered. Two areas of potential use are identified and one, data exploration, is used to illustrate the possibilities. A method is presented to identify and separate overlapping groups within cluster analysis, using an AI approach. The potential of such ''intelligent'' approaches is stressed

  13. AI its nature and future

    CERN Document Server

    Boden, Margaret A

    2016-01-01

    least - on the Internet. Margaret Boden considers the realistic and unrealistic expectations we have placed on AI, analyses its progress, and considers the value of its byproducts. ations we have placed on AI, analyses its progress, and considers the value of its byproducts.

  14. Intelligent Lighting Control System

    OpenAIRE

    García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

    2014-01-01

    This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

  15. Computational Foundations of Natural Intelligence.

    Science.gov (United States)

    van Gerven, Marcel

    2017-01-01

    New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

  16. Computational Foundations of Natural Intelligence

    Directory of Open Access Journals (Sweden)

    Marcel van Gerven

    2017-12-01

    Full Text Available New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

  17. Mapping change in scientific specialties: a scientometric case study of the development or artificial intelligence

    NARCIS (Netherlands)

    van den Besselaar, P.; Leydesdorff, L.

    1996-01-01

    Has an identifiable core of activities called AI been established, during the AI-boom in the eighties? Is AI already in a “paradigmatic” phase? There has been a lot of disagreement among commentators and specialists about the nature of Artificial Intelligence as a specialty. This makes AI an

  18. A framework for AI-based nuclear design support system

    International Nuclear Information System (INIS)

    Furuta, Kazuo; Kondo, Shunsuke

    1991-01-01

    Nowadays many computer programs are being developed and used for the analytic tasks in nuclear reactor design, but experienced designers are still responsible for most of the synthetic tasks which are not amenable to algorithmic computer processes. Artificial intelligence (AI) is a promising technology to deal with these intractable tasks in design. In development of AI-based design support systems, it is desirable to choose a comprehensive framework based on the scientific theory of design. In this work a framework for AI-based design support systems for nuclear reactor design will be proposed based on an exploration model of design. The fundamental architectures of this framework will be described especially on knowledge representation, context management and design planning. (author)

  19. Framework for AI-based nuclear reactor design support system

    International Nuclear Information System (INIS)

    Furuta, Kazuo; Kondo, Shunsuke

    1992-01-01

    Nowadays many computer programs are being developed and used for the analytic tasks in nuclear reactor design, but experienced designers are still responsible for most of the synthetic tasks which are not amenable to algorithmic computer processes. Artificial intelligence (AI) is a promising technology to deal with these intractable tasks in design. In development of AI-based design support systems, it is desirable to choose a comprehensive framework based on the scientific theory of design. In this work a framework for AI-based design support systems for nuclear reactor design will be proposed based on an explorative abduction model of design. The fundamental architectures of this framework will be described especially on knowledge representation, context management and design planning. (author)

  20. Towards AI-powered personalization in MOOC learning

    Science.gov (United States)

    Yu, Han; Miao, Chunyan; Leung, Cyril; White, Timothy John

    2017-12-01

    Massive Open Online Courses (MOOCs) represent a form of large-scale learning that is changing the landscape of higher education. In this paper, we offer a perspective on how advances in artificial intelligence (AI) may enhance learning and research on MOOCs. We focus on emerging AI techniques including how knowledge representation tools can enable students to adjust the sequence of learning to fit their own needs; how optimization techniques can efficiently match community teaching assistants to MOOC mediation tasks to offer personal attention to learners; and how virtual learning companions with human traits such as curiosity and emotions can enhance learning experience on a large scale. These new capabilities will also bring opportunities for educational researchers to analyse students' learning skills and uncover points along learning paths where students with different backgrounds may require different help. Ethical considerations related to the application of AI in MOOC education research are also discussed.

  1. AI-guided parameter optimization in inverse treatment planning

    International Nuclear Information System (INIS)

    Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho

    2003-01-01

    An artificial intelligence (AI)-guided inverse planning system was developed to optimize the combination of parameters in the objective function for intensity-modulated radiation therapy (IMRT). In this system, the empirical knowledge of inverse planning was formulated with fuzzy if-then rules, which then guide the parameter modification based on the on-line calculated dose. Three kinds of parameters (weighting factor, dose specification, and dose prescription) were automatically modified using the fuzzy inference system (FIS). The performance of the AI-guided inverse planning system (AIGIPS) was examined using the simulated and clinical examples. Preliminary results indicate that the expected dose distribution was automatically achieved using the AI-guided inverse planning system, with the complicated compromising between different parameters accomplished by the fuzzy inference technique. The AIGIPS provides a highly promising method to replace the current trial-and-error approach

  2. How AI turned the chess world upside down

    KAUST Repository

    Polgar, Susan

    2018-01-22

    Man vs. Machine! In 1977 an IBM supercomputer \\'Deep Blue\\' beat the reigning World Chess Champion Gary Kasparov in a 6 game chess match played under tournament conditions. This was the first time a machine beat a human at chess. It symbolized the emergence of Artificial Intelligence (AI) and the potential for great good (and great harm) from machines that have aspects of human intelligence. During this lecture Susan Polgar, a pioneer for Women in Chess, will share her remarkable story as well as how technology has changed the world of chess.

  3. Ada in AI or AI in Ada. On developing a rationale for integration

    Science.gov (United States)

    Collard, Philippe E.; Goforth, Andre

    1988-01-01

    The use of Ada as an Artificial Intelligence (AI) language is gaining interest in the NASA Community, i.e., by parties who have a need to deploy Knowledge Based-Systems (KBS) compatible with the use of Ada as the software standard for the Space Station. A fair number of KBS and pseudo-KBS implementations in Ada exist today. Currently, no widely used guidelines exist to compare and evaluate these with one another. The lack of guidelines illustrates a fundamental problem inherent in trying to compare and evaluate implementations of any sort in languages that are procedural or imperative in style, such as Ada, with those in languages that are functional in style, such as Lisp. Discussed are the strengths and weakness of using Ada as an AI language and a preliminary analysis provided of factors needed for the development of criteria for the integration of these two families of languages and the environments in which they are implemented. The intent for developing such criteria is to have a logical rationale that may be used to guide the development of Ada tools and methodology to support KBS requirements, and to identify those AI technology components that may most readily and effectively be deployed in Ada.

  4. Little AI: Playing a constructivist robot

    Science.gov (United States)

    Georgeon, Olivier L.

    Little AI is a pedagogical game aimed at presenting the founding concepts of constructivist learning and developmental Artificial Intelligence. It primarily targets students in computer science and cognitive science but it can also interest the general public curious about these topics. It requires no particular scientific background; even children can find it entertaining. Professors can use it as a pedagogical resource in class or in online courses. The player presses buttons to control a simulated "baby robot". The player cannot see the robot and its environment, and initially ignores the effects of the commands. The only information received by the player is feedback from the player's commands. The player must learn, at the same time, the functioning of the robot's body and the structure of the environment from patterns in the stream of commands and feedback. We argue that this situation is analogous to how infants engage in early-stage developmental learning (e.g., Piaget (1937), [1]).

  5. Monitoring Severe Accidents Using AI Techniques

    International Nuclear Information System (INIS)

    No, Young Gyu; Kim, Ju Hyun; Na, Man Gyun; Ahn, Kwang Il

    2011-01-01

    It is very difficult for nuclear power plant operators to monitor and identify the major severe accident scenarios following an initiating event by staring at temporal trends of important parameters. The objective of this study is to develop and verify the monitoring for severe accidents using artificial intelligence (AI) techniques such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH) and fuzzy neural network (FNN). The SVC and PNN are used for event classification among the severe accidents. Also, GMDH and FNN are used to monitor for severe accidents. The inputs to AI techniques are initial time-integrated values obtained by integrating measurement signals during a short time interval after reactor scram. In this study, 3 types of initiating events such as the hot-leg LOCA, the cold-leg LOCA and SGTR are considered and it is verified how well the proposed scenario identification algorithm using the GMDH and FNN models identifies the timings when the reactor core will be uncovered, when CET will exceed 1200 .deg. F and when the reactor vessel will fail. In cases that an initiating event develops into a severe accident, the proposed algorithm showed accurate classification of initiating events. Also, it well predicted timings for important occurrences during severe accident progression scenarios, which is very helpful for operators to perform severe accident management

  6. Is Intelligence Artificial?

    OpenAIRE

    Greer, Kieran

    2014-01-01

    Our understanding of intelligence is directed primarily at the level of human beings. This paper attempts to give a more unifying definition that can be applied to the natural world in general. The definition would be used more to verify a degree of intelligence, not to quantify it and might help when making judgements on the matter. A version of an accepted test for AI is then put forward as the 'acid test' for Artificial Intelligence itself. It might be what a free-thinking program or robot...

  7. Code AI Personal Web Pages

    Science.gov (United States)

    Garcia, Joseph A.; Smith, Charles A. (Technical Monitor)

    1998-01-01

    The document consists of a publicly available web site (george.arc.nasa.gov) for Joseph A. Garcia's personal web pages in the AI division. Only general information will be posted and no technical material. All the information is unclassified.

  8. Making Computers Smarter: A Look At the Controversial Field of Artificial Intelligence.

    Science.gov (United States)

    Green, John O.

    1984-01-01

    Defines artificial intelligence (AI) and discusses its history; the current state of the art, research, experimentation, and practical applications; and probable future developments. Key dates in the history of AI and eight references are provided. (MBR)

  9. Proceedings of conference on AI applications in physical sciences

    International Nuclear Information System (INIS)

    1993-01-01

    A Conference cum workshop on AI applications in Physical Sciences was organised by the Indian Physics Association at Bhabha Atomic Research Centre, Bombay during January 15-17, 1992. It was held in memory of Late Shri S.N. Seshadri, who was the moving spirit behind self reliance in instrumentation development for research and industry. The two day conference which was followed by one day workshop covered the following broad spectrum of topics in Artificial Intelligence: AI Tools and Techniques, Neural Networks, Robotics and Machine Vision, Fuzzy Control and Applications, Natural Language and Speech Processing, Knowledge based Systems, and AI and Allied applications. The conference dealt with recent advances and achievements in AI. It provided a forum for the exchange of valuable information and expertise in this fast emerging field. Over 200 scientists, engineers and computer professionals from various universities, R and D institutes and industries actively participated. 45 contributed papers and 8 invited talks were presented in the symposium. The volume contains selected papers which were contributed by the participants. Some of them dealt with AI applications in nuclear science and technology. (original)

  10. Present status of application of AI in nuclear industry

    International Nuclear Information System (INIS)

    Kitamura, Masaharu

    1989-01-01

    Artificial intelligence (AL) techniques have been introduced actively in the nuclear industry in pursuit of increased safety and efficiency. The present report outlines some AI techniques currently used in nuclear facilities. This type of techniques have increasingly been introduced to such areas as design, construction, operation, maintenance, quality control and analysis. Most of them use knowledge engineering techniques including expert systems. Positive efforts at research and application of various more advance AI techniaues have started recently. For application of AI techniques, activities in nuclear power plants can be divided into two groups. One includes 'analytical' activities such as operation, maintenance and analysis, while the other includes 'synthetic' activities such as design, construction and fuel control. The most important AI technology for the analytical activities is diagnosis. Thus the report outlines major processes to which diagnostic techniques are applicable, and knowledge description and inference methods used for diagnosis. For AI techniques for synthetic activities, some problems and possible solutions are addressed. Development efforts in and outside Japan are also outlined. (Nogami, K.)

  11. Discovering Knowledge from AIS Database for Application in VTS

    Science.gov (United States)

    Tsou, Ming-Cheng

    The widespread use of the Automatic Identification System (AIS) has had a significant impact on maritime technology. AIS enables the Vessel Traffic Service (VTS) not only to offer commonly known functions such as identification, tracking and monitoring of vessels, but also to provide rich real-time information that is useful for marine traffic investigation, statistical analysis and theoretical research. However, due to the rapid accumulation of AIS observation data, the VTS platform is often unable quickly and effectively to absorb and analyze it. Traditional observation and analysis methods are becoming less suitable for the modern AIS generation of VTS. In view of this, we applied the same data mining technique used for business intelligence discovery (in Customer Relation Management (CRM) business marketing) to the analysis of AIS observation data. This recasts the marine traffic problem as a business-marketing problem and integrates technologies such as Geographic Information Systems (GIS), database management systems, data warehousing and data mining to facilitate the discovery of hidden and valuable information in a huge amount of observation data. Consequently, this provides the marine traffic managers with a useful strategic planning resource.

  12. Artificial Intelligence and Public Healthcare Service Innovation

    DEFF Research Database (Denmark)

    Sun, Tara Qian; Medaglia, Rony

    Public healthcare ecosystems are complex networks of diverse actors that are subject to pressures to innovate, also a result of technological advancements. Artificial Intelligence (AI), in particular, has the potential to transform the way hospitals, doctors, patients, government agencies...

  13. Event tree analysis using artificial intelligence techniques

    International Nuclear Information System (INIS)

    Dixon, B.W.; Hinton, M.F.

    1985-01-01

    Artificial Intelligence (AI) techniques used in Expert Systems and Object Oriented Programming are discussed as they apply to Event Tree Analysis. A SeQUence IMPortance calculator, SQUIMP, is presented to demonstrate the implementation of these techniques. Benefits of using AI methods include ease of programming, efficiency of execution, and flexibility of application. The importance of an appropriate user interface is stressed. 5 figs

  14. Artificial Intelligence, Computational Thinking, and Mathematics Education

    Science.gov (United States)

    Gadanidis, George

    2017-01-01

    Purpose: The purpose of this paper is to examine the intersection of artificial intelligence (AI), computational thinking (CT), and mathematics education (ME) for young students (K-8). Specifically, it focuses on three key elements that are common to AI, CT and ME: agency, modeling of phenomena and abstracting concepts beyond specific instances.…

  15. Artificial intelligence approaches to astronomical observation scheduling

    Science.gov (United States)

    Johnston, Mark D.; Miller, Glenn

    1988-01-01

    Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.

  16. Adding intelligence to scientific data management

    Science.gov (United States)

    Campbell, William J.; Short, Nicholas M., Jr.; Treinish, Lloyd A.

    1989-01-01

    NASA plans to solve some of the problems of handling large-scale scientific data bases by turning to artificial intelligence (AI) are discussed. The growth of the information glut and the ways that AI can help alleviate the resulting problems are reviewed. The employment of the Intelligent User Interface prototype, where the user will generate his own natural language query with the assistance of the system, is examined. Spatial data management, scientific data visualization, and data fusion are discussed.

  17. Human-in-the-loop Artificial Intelligence

    OpenAIRE

    Zanzotto, Fabio Massimo

    2017-01-01

    Little by little, newspapers are revealing the bright future that Artificial Intelligence (AI) is building. Intelligent machines will help everywhere. However, this bright future has a dark side: a dramatic job market contraction before its unpredictable transformation. Hence, in a near future, large numbers of job seekers will need financial support while catching up with these novel unpredictable jobs. This possible job market crisis has an antidote inside. In fact, the rise of AI is sustai...

  18. Artificial intelligence in medicine.

    Science.gov (United States)

    Hamet, Pavel; Tremblay, Johanne

    2017-04-01

    Artificial Intelligence (AI) is a general term that implies the use of a computer to model intelligent behavior with minimal human intervention. AI is generally accepted as having started with the invention of robots. The term derives from the Czech word robota, meaning biosynthetic machines used as forced labor. In this field, Leonardo Da Vinci's lasting heritage is today's burgeoning use of robotic-assisted surgery, named after him, for complex urologic and gynecologic procedures. Da Vinci's sketchbooks of robots helped set the stage for this innovation. AI, described as the science and engineering of making intelligent machines, was officially born in 1956. The term is applicable to a broad range of items in medicine such as robotics, medical diagnosis, medical statistics, and human biology-up to and including today's "omics". AI in medicine, which is the focus of this review, has two main branches: virtual and physical. The virtual branch includes informatics approaches from deep learning information management to control of health management systems, including electronic health records, and active guidance of physicians in their treatment decisions. The physical branch is best represented by robots used to assist the elderly patient or the attending surgeon. Also embodied in this branch are targeted nanorobots, a unique new drug delivery system. The societal and ethical complexities of these applications require further reflection, proof of their medical utility, economic value, and development of interdisciplinary strategies for their wider application. Copyright © 2017. Published by Elsevier Inc.

  19. Artificial intelligence in cardiology

    Directory of Open Access Journals (Sweden)

    Srishti Sharma

    2017-01-01

    Full Text Available Artificial intelligence (AI provides machines with the ability to learn and respond the way humans do and is also referred to as machine learning. The step to building an AI system is to provide the data to learn from so that it can map relations between inputs and outputs and set up parameters such as “weights”/decision boundaries to predict responses for inputs in the future. Then, the model is tested on a second data set. This article outlines the promise this analytic approach has in medicine and cardiology.

  20. Artificial Intelligence in Surgery: Promises and Perils.

    Science.gov (United States)

    Hashimoto, Daniel A; Rosman, Guy; Rus, Daniela; Meireles, Ozanan R

    2018-07-01

    The aim of this review was to summarize major topics in artificial intelligence (AI), including their applications and limitations in surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments. AI is composed of various subfields that each provide potential solutions to clinical problems. Each of the core subfields of AI reviewed in this piece has also been used in other industries such as the autonomous car, social networks, and deep learning computers. A review of AI papers across computer science, statistics, and medical sources was conducted to identify key concepts and techniques within AI that are driving innovation across industries, including surgery. Limitations and challenges of working with AI were also reviewed. Four main subfields of AI were defined: (1) machine learning, (2) artificial neural networks, (3) natural language processing, and (4) computer vision. Their current and future applications to surgical practice were introduced, including big data analytics and clinical decision support systems. The implications of AI for surgeons and the role of surgeons in advancing the technology to optimize clinical effectiveness were discussed. Surgeons are well positioned to help integrate AI into modern practice. Surgeons should partner with data scientists to capture data across phases of care and to provide clinical context, for AI has the potential to revolutionize the way surgery is taught and practiced with the promise of a future optimized for the highest quality patient care.

  1. The impact of artificial intelligence on the world economy

    OpenAIRE

    Kuprevich, T. S.

    2017-01-01

    In the article the potential benefits and opportunities offered by AI in the world economy are considered. In the course of the research benefits and tendencies of artificial intelligence in the world economy were revealed, the main directions of development and barriers of artificial intelligence adoption are analyzed and revealed. Nowadays artificial intelligence (AI) is going mainstream, driven by machine learning, big data and cloud computing.

  2. Artificial Intelligence in Autonomous Telescopes

    Science.gov (United States)

    Mahoney, William; Thanjavur, Karun

    2011-03-01

    Artificial Intelligence (AI) is key to the natural evolution of today's automated telescopes to fully autonomous systems. Based on its rapid development over the past five decades, AI offers numerous, well-tested techniques for knowledge based decision making essential for real-time telescope monitoring and control, with minimal - and eventually no - human intervention. We present three applications of AI developed at CFHT for monitoring instantaneous sky conditions, assessing quality of imaging data, and a prototype for scheduling observations in real-time. Closely complementing the current remote operations at CFHT, we foresee further development of these methods and full integration in the near future.

  3. Artificial Intelligence and Information Management

    Science.gov (United States)

    Fukumura, Teruo

    After reviewing the recent popularization of the information transmission and processing technologies, which are supported by the progress of electronics, the authors describe that by the introduction of the opto-electronics into the information technology, the possibility of applying the artificial intelligence (AI) technique to the mechanization of the information management has emerged. It is pointed out that althuogh AI deals with problems in the mental world, its basic methodology relies upon the verification by evidence, so the experiment on computers become indispensable for the study of AI. The authors also describe that as computers operate by the program, the basic intelligence which is concerned in AI is that expressed by languages. This results in the fact that the main tool of AI is the logical proof and it involves an intrinsic limitation. To answer a question “Why do you employ AI in your problem solving”, one must have ill-structured problems and intend to conduct deep studies on the thinking and the inference, and the memory and the knowledge-representation. Finally the authors discuss the application of AI technique to the information management. The possibility of the expert-system, processing of the query, and the necessity of document knowledge-base are stated.

  4. Towards Brain-inspired Web Intelligence

    Science.gov (United States)

    Zhong, Ning

    Artificial Intelligence (AI) has been mainly studied within the realm of computer based technologies. Various computational models and knowledge based systems have been developed for automated reasoning, learning, and problem-solving. However, there still exist several grand challenges. The AI research has not produced major breakthrough recently due to a lack of understanding of human brains and natural intelligence. In addition, most of the AI models and systems will not work well when dealing with large-scale, dynamically changing, open and distributed information sources at a Web scale.

  5. The role of automation and artificial intelligence

    Science.gov (United States)

    Schappell, R. T.

    1983-07-01

    Consideration is given to emerging technologies that are not currently in common use, yet will be mature enough for implementation in a space station. Artificial intelligence (AI) will permit more autonomous operation and improve the man-machine interfaces. Technology goals include the development of expert systems, a natural language query system, automated planning systems, and AI image understanding systems. Intelligent robots and teleoperators will be needed, together with improved sensory systems for the robotics, housekeeping, vehicle control, and spacecraft housekeeping systems. Finally, NASA is developing the ROBSIM computer program to evaluate level of automation, perform parametric studies and error analyses, optimize trajectories and control systems, and assess AI technology.

  6. Introducing artificial intelligence into structural optimization programs

    International Nuclear Information System (INIS)

    Jozwiak, S.F.

    1987-01-01

    Artificial Intelligence /AI/ is defined as the branch of the computer science concerned with the study of the ideas that enable computers to be intelligent. The main purpose of the application of AI in engineering is to develop computer programs which function better as tools for engineers and designers. Many computer programs today have properties which make them inconvenient to their final users and the research carried within the field of AI provides tools and techniques so that these restriction can be removed. The continuous progress in computer technology has lead to developing efficient computer systems which can be applied to more than simple solving sets of equations. (orig.)

  7. The potential of artificial intelligence toys

    DEFF Research Database (Denmark)

    Dai, Zheng

    2008-01-01

    Artificial intelligence is moving to a next step of development and application areas. From electronic games to human-like robots, AI toy is a good choice for next step during this process. Technology-based design is fit to the development of AI toy. It can exert the advantages and explore more...... value for existing resources. It combines AI programs and common sensors to realize the function of intelligence input and output. Designers can use technology-based criteria to design and need to consider the possible issues in this new field. All of these aspects can be referenced from electronic game...

  8. A quick overview of artificial intelligence and expert systems

    International Nuclear Information System (INIS)

    Engelmore, R.S.

    1989-01-01

    Artificial intelligence (AI) is almost a household word these days. There have been several conferences held in this country over the last two years on artificial intelligence and its applications. The international AI conference at Snowbird, Utah, in 1987 centered on AI applications in the nuclear industry. This paper serves as an introductory overview of the subject of AI for this state-of-the-art review of AI applications in the nuclear industry. We introduce the subject in a way that will be relevant to many people in the nuclear industry who have heard of AI but are not familiar with it and are looking for answers to several simple questions. We attempt to answer those simple questions here and prepare the reader so that he or she can appreciate the following sections on AI applications in the nuclear field. (orig./GL)

  9. Artificial-intelligence-based optimization of the management of snow removal assets and resources.

    Science.gov (United States)

    2002-10-01

    Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent : snow removal asset management system (SRAMS). The system has been evaluated through a case study examining : snow removal from the ...

  10. Des résumés en français

    Directory of Open Access Journals (Sweden)

    Bogdan Patrut

    2010-09-01

    Full Text Available Des résumés en français
    BRAIN. Broad Research in Artificial Intelligence and Neuroscience
    CERVEAU. Recherche large en intelligence artificielle et neurosciences
    Volume 1, Numéro 4
    Juillet 2010: « Automne 2010»
    www.brain.edusoft.ro
    Sous la direction de: Bogdan Pătruţ

  11. Artificial intelligence in radiology.

    Science.gov (United States)

    Hosny, Ahmed; Parmar, Chintan; Quackenbush, John; Schwartz, Lawrence H; Aerts, Hugo J W L

    2018-05-17

    Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.

  12. AI mass spectrometers for space shuttle health monitoring

    Science.gov (United States)

    Adams, F. W.

    1991-01-01

    The facility Hazardous Gas Detection System (HGDS) at Kennedy Space Center (KSC) is a mass spectrometer based gas analyzer. Two instruments make up the HGDS, which is installed in a prime/backup arrangement, with the option of using both analyzers on the same sample line, or on two different lines simultaneously. It is used for monitoring the Shuttle during fuel loading, countdown, and drainback, if necessary. The use of complex instruments, operated over many shifts, has caused problems in tracking the status of the ground support equipment (GSE) and the vehicle. A requirement for overall system reliability has been a major force in the development of Shuttle GSE, and is the ultimate driver in the choice to pursue artificial intelligence (AI) techniques for Shuttle and Advanced Launch System (ALS) mass spectrometer systems. Shuttle applications of AI are detailed.

  13. Artificial intelligence in astronomy - a forecast.

    Science.gov (United States)

    Adorf, H. M.

    Since several years artificial intelligence techniques are being actively used in astronomy, particularly within the Hubble Space Telescope project. This contribution reviews achievements, analyses some problems of using artificial intelligence in an astronomical environment, and projects current AI programming trends into the future.

  14. The Artificial Intelligence Applications to Learning Programme.

    Science.gov (United States)

    Williams, Noel

    1992-01-01

    Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…

  15. Does Wittgenstein Actually Undermine the Foundation of Artificial Intelligence?

    Institute of Scientific and Technical Information of China (English)

    XU Yingjin

    2016-01-01

    Wittgenstein is widely viewed as a potential critic of a key philosophical assumption of the Strong Artificial Intelligence (AI) thesis,namely,that it is in principle possible to build a programmed machine which can achieve real intelligence.Stuart Shanker has provided the most systematic reconstruction of the Wittgensteinian argument against AI,building on Wittgenstein's own statements,the "rule-following" feature of language-games,and the putative alliance between AI and psychologism.This article will attempt to refute this reconstruction and its constituent arguments,thereby paving the way for a new and amicable rather than agonistic conception of the Wittgensteinian position on AI.

  16. Artificial Intelligence Techniques and Methodology

    OpenAIRE

    Carbonell, Jaime G.; Sleeman, Derek

    1982-01-01

    Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. It is imperative to analyze the repertoire of AI methods with respect to past experience, utility in new domains,...

  17. AI Tools Bridge Technology Gap.

    Science.gov (United States)

    Rauch-Hindin, Wendy

    1985-01-01

    This second part of a report on artificial intelligence focuses on the development of expert systems in a variety of applications, from engineering to science, and details expectations for implementation of these systems. (JN)

  18. Artificial intelligence executive summary

    International Nuclear Information System (INIS)

    Wamsley, S.J.; Purvis, E.E. III

    1984-01-01

    Artificial intelligence (AI) is a high technology field that can be used to provide problem solving diagnosis, guidance and for support resolution of problems. It is not a stand alone discipline, but can also be applied to develop data bases for retention of the expertise that is required for its own knowledge base. This provides a way to retain knowledge that otherwise may be lost. Artificial Intelligence Methodology can provide an automated construction management decision support system, thereby restoring the manager's emphasis to project management

  19. Artificial intelligence in power system optimization

    CERN Document Server

    Ongsakul, Weerakorn

    2013-01-01

    With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.

  20. Optimizing Limousine Service with AI

    OpenAIRE

    Chun, Andy Hon Wai

    2011-01-01

    A common problem for companies with strong business growth is that it is hard to find enough experienced staff to support expansion needs. This problem is particular pronounced for operations planners and controllers who must be very highly knowledgeable and experienced with the business domain. This article is a case study of how one of the largest travel agencies in Hong Kong alleviated this problem by using AI to support decision-making and problem-solving so that their planners and contro...

  1. Little AI: Playing a constructivist robot

    Directory of Open Access Journals (Sweden)

    Olivier L. Georgeon

    2017-01-01

    Full Text Available Little AI is a pedagogical game aimed at presenting the founding concepts of constructivist learning and developmental Artificial Intelligence. It primarily targets students in computer science and cognitive science but it can also interest the general public curious about these topics. It requires no particular scientific background; even children can find it entertaining. Professors can use it as a pedagogical resource in class or in online courses. The player presses buttons to control a simulated “baby robot”. The player cannot see the robot and its environment, and initially ignores the effects of the commands. The only information received by the player is feedback from the player’s commands. The player must learn, at the same time, the functioning of the robot’s body and the structure of the environment from patterns in the stream of commands and feedback. We argue that this situation is analogous to how infants engage in early-stage developmental learning (e.g., Piaget (1937, [1].

  2. STAR - A computer language for hybrid AI applications

    Science.gov (United States)

    Borchardt, G. C.

    1986-01-01

    Constructing Artificial Intelligence application systems which rely on both symbolic and non-symbolic processing places heavy demands on the communication of data between dissimilar languages. This paper describes STAR (Simple Tool for Automated Reasoning), a computer language for the development of AI application systems which supports the transfer of data structures between a symbolic level and a non-symbolic level defined in languages such as FORTRAN, C and PASCAL. The organization of STAR is presented, followed by the description of an application involving STAR in the interpretation of airborne imaging spectrometer data.

  3. Alarm processing system using AI techniques for nuclear power plant

    International Nuclear Information System (INIS)

    Yang, Joon On; Chang, Soon Heung

    1990-01-01

    An alarm processing system (APS) has been developed using artificial intelligence (AI) techniques. The alarms of nuclear power plants (NPP's) are classified into the generalized and special alarms. The generalized alarms are also classified into the global and local alarms. For each type of alarms, the specific processing rules are applied to filter and suppress unnecessary and potentially misleading alarms. The local processing are based on 'model-based reasoning.' The global and special alarms are processed by using the general cause-consequence check rules. The priorities of alarms are determined according to the plant state and the consistencies between them

  4. ReACT!: An Interactive Educational Tool for AI Planning for Robotics

    Science.gov (United States)

    Dogmus, Zeynep; Erdem, Esra; Patogulu, Volkan

    2015-01-01

    This paper presents ReAct!, an interactive educational tool for artificial intelligence (AI) planning for robotics. ReAct! enables students to describe robots' actions and change in dynamic domains without first having to know about the syntactic and semantic details of the underlying formalism, and to solve planning problems using…

  5. Cognitive Maps, AI Agents and Personalized Virtual Environments in Internet Learning Experiences.

    Science.gov (United States)

    Maule, R. William

    1998-01-01

    Develops frameworks to help Internet media designers address end-user information presentation preferences by advancing structures for assessing metadata design variables which are then linked to user cognitive styles. An underlying theme is that artificial intelligence (AI) methodologies may be used to help automate the Internet media design…

  6. Autonomously generating operations sequences for a Mars Rover using AI-based planning

    Science.gov (United States)

    Sherwood, Rob; Mishkin, Andrew; Estlin, Tara; Chien, Steve; Backes, Paul; Cooper, Brian; Maxwell, Scott; Rabideau, Gregg

    2001-01-01

    This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from highlevel science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules.

  7. NASA space station automation: AI-based technology review. Executive summary

    Science.gov (United States)

    Firschein, O.; Georgeff, M. P.; Park, W.; Cheeseman, P. C.; Goldberg, J.; Neumann, P.; Kautz, W. H.; Levitt, K. N.; Rom, R. J.; Poggio, A. A.

    1985-01-01

    Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics.

  8. Ethical Considerations in Artificial Intelligence Courses

    OpenAIRE

    Burton, Emanuelle; Goldsmith, Judy; Koenig, Sven; Kuipers, Benjamin; Mattei, Nicholas; Walsh, Toby

    2017-01-01

    The recent surge in interest in ethics in artificial intelligence may leave many educators wondering how to address moral, ethical, and philosophical issues in their AI courses. As instructors we want to develop curriculum that not only prepares students to be artificial intelligence practitioners, but also to understand the moral, ethical, and philosophical impacts that artificial intelligence will have on society. In this article we provide practical case studies and links to resources for ...

  9. Artificial intelligence in healthcare: past, present and future.

    Science.gov (United States)

    Jiang, Fei; Jiang, Yong; Zhi, Hui; Dong, Yi; Li, Hao; Ma, Sufeng; Wang, Yilong; Dong, Qiang; Shen, Haipeng; Wang, Yongjun

    2017-12-01

    Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI.

  10. Artificial intelligence in healthcare: past, present and future

    Science.gov (United States)

    Jiang, Fei; Jiang, Yong; Zhi, Hui; Dong, Yi; Li, Hao; Ma, Sufeng; Wang, Yilong; Dong, Qiang; Shen, Haipeng; Wang, Yongjun

    2017-01-01

    Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI. PMID:29507784

  11. Synthesis and Analysis in Artificial Intelligence: The Role of Theory in Agent Implementation

    NARCIS (Netherlands)

    Raine, Roxanne B.; op den Akker, Hendrikus J.A.; Cai, Zhiqiang; Graesser, Arthur C.; McNamara, Danielle S.

    2009-01-01

    The domain of artificial intelligence (AI) progresses with extraordinary vicissitude. Whereas prior authors have divided AI into the two categories of analysis and synthesis, Raine and op den Akker distinguish between four types of AI: that of appearance, function, simulation and interpretation.

  12. 26th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE)

    CERN Document Server

    Bosse, Tibor; Hindriks, Koen; Hoogendoorn, Mark; Jonker, Catholijn; Treur, Jan; Contemporary Challenges and Solutions in Applied Artificial Intelligence

    2013-01-01

      Since its origination in the mid-twentieth century, the area of Artificial Intelligence (AI) has undergone a number of developments. While the early interest in AI was mainly triggered by the desire to develop artifacts that show the same intelligent behavior as humans, nowadays scientists have realized that research in AI involves a multitude of separate challenges, besides the traditional goal to replicate human intelligence. In particular, recent history has pointed out that a variety of ‘intelligent’ computational techniques, part of which are inspired by human intelligence, may be successfully applied to solve all kinds of practical problems. This sub-area of AI, which has its main emphasis on applications of intelligent systems to solve real-life problems, is currently known under the term Applied Intelligence.   The objective of the International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE) is to promote and disseminate recent research ...

  13. 77 FR 5681 - Establishment of Global Entry Program

    Science.gov (United States)

    2012-02-06

    ...) of the Intelligence Reform and Terrorism Prevention Act of 2004 (IRTPA), 118 Stat. 3638, as amended... major airport authority printed its own signs for Global Entry and strategically placed them throughout...

  14. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part A: The core ingredients

    Science.gov (United States)

    Gevarter, W. B.

    1983-01-01

    Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. The goal of Artificial Intelligence is focused on developing computational approaches to intelligent behavior. This goal is so broad - covering virtually all aspects of human cognitive activity - that substantial confusion has arisen as to the actual nature of AI, its current status and its future capability. This volume, the first in a series of NBS/NASA reports on the subject, attempts to address these concerns. Thus, this report endeavors to clarify what AI is, the foundations on which it rests, the techniques utilized, applications, the participants and, finally, AI's state-of-the-art and future trends. It is anticipated that this report will prove useful to government and private engineering and research managers, potential users, and others who will be affected by this field as it unfolds.

  15. Challenges in introduction of artificial intelligence in medical practice – a review of clinical trials concerning adaptation of artificial intelligence in medicine

    OpenAIRE

    Mielnik, Pawel Franciszek; Fojcik, Marcin; Kulbacki, Marek; Segen, Jakub

    2016-01-01

    An interest in Artificial Intelligence [AI] as science is growing in the last years. It has become gradually more used in the medicine. Methodology of development and testing of AI algorithms is generally well established. Use of AI in medicine requires elaboration of standards of its validation in clinical settings. This paper is a review of literature concerning clinical trials on AI adaptation in medicine

  16. [Artificial Intelligence in Drug Discovery].

    Science.gov (United States)

    Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

    2018-04-01

    According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

  17. "It's Going to Kill Us!" and Other Myths about the Future of Artificial Intelligence

    Science.gov (United States)

    Atkinson, Robert D.

    2016-01-01

    Given the promise that artificial intelligence (AI) holds for economic growth and societal advancement, it is critical that policymakers not only avoid retarding the progress of AI innovation, but also actively support its further development and use. This report provides a primer on artificial intelligence and debunks five prevailing myths that,…

  18. Economic reasoning and artificial intelligence.

    Science.gov (United States)

    Parkes, David C; Wellman, Michael P

    2015-07-17

    The field of artificial intelligence (AI) strives to build rational agents capable of perceiving the world around them and taking actions to advance specified goals. Put another way, AI researchers aim to construct a synthetic homo economicus, the mythical perfectly rational agent of neoclassical economics. We review progress toward creating this new species of machine, machina economicus, and discuss some challenges in designing AIs that can reason effectively in economic contexts. Supposing that AI succeeds in this quest, or at least comes close enough that it is useful to think about AIs in rationalistic terms, we ask how to design the rules of interaction in multi-agent systems that come to represent an economy of AIs. Theories of normative design from economics may prove more relevant for artificial agents than human agents, with AIs that better respect idealized assumptions of rationality than people, interacting through novel rules and incentive systems quite distinct from those tailored for people. Copyright © 2015, American Association for the Advancement of Science.

  19. Artificial intelligence and nuclear power. Report by the Technology Transfer Artificial Intelligence Task Team

    International Nuclear Information System (INIS)

    1985-06-01

    The Artificial Intelligence Task Team was organized to review the status of Artificial Intelligence (AI) technology, identify guidelines for AI work, and to identify work required to allow the nuclear industry to realize maximum benefit from this technology. The state of the nuclear industry was analyzed to determine where the application of AI technology could be of greatest benefit. Guidelines and criteria were established to focus on those particular problem areas where AI could provide the highest possible payoff to the industry. Information was collected from government, academic, and private organizations. Very little AI work is now being done to specifically support the nuclear industry. The AI Task Team determined that the establishment of a Strategic Automation Initiative (SAI) and the expansion of the DOE Technology Transfer program would ensure that AI technology could be used to develop software for the nuclear industry that would have substantial financial payoff to the industry. The SAI includes both long and short term phases. The short-term phase includes projects which would demonstrate that AI can be applied to the nuclear industry safely, and with substantial financial benefit. The long term phase includes projects which would develop AI technologies with specific applicability to the nuclear industry that would not be developed by people working in any other industry

  20. The role of artificial intelligence and expert systems in increasing STS operations productivity

    Science.gov (United States)

    Culbert, C.

    1985-01-01

    Artificial Intelligence (AI) is discussed. A number of the computer technologies pioneered in the AI world can make significant contributions to increasing STS operations productivity. Application of expert systems, natural language, speech recognition, and other key technologies can reduce manpower while raising productivity. Many aspects of STS support lend themselves to this type of automation. The artificial intelligence section of the mission planning and analysis division has developed a number of functioning prototype systems which demonstrate the potential gains of applying AI technology.

  1. Coupling artificial intelligence and numerical computation for engineering design (Invited paper)

    Science.gov (United States)

    Tong, S. S.

    1986-01-01

    The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.

  2. Demonstration of artificial intelligence technology for transit railcar diagnostics

    Science.gov (United States)

    1999-01-01

    This report will be of interest to railcar maintenance professionals concerned with improving railcar maintenance fault-diagnostic capabilities through the use of artificial intelligence (AI) technologies. It documents the results of a demonstration ...

  3. Utilising artificial intelligence in software defined wireless sensor network

    CSIR Research Space (South Africa)

    Matlou, OG

    2017-10-01

    Full Text Available Software Defined Wireless Sensor Network (SDWSN) is realised by infusing Software Defined Network (SDN) model in Wireless Sensor Network (WSN), Reason for that is to overcome the challenges of WSN. Artificial Intelligence (AI) and machine learning...

  4. Learning modalities in artificial intelligence systems: a framework and review

    Energy Technology Data Exchange (ETDEWEB)

    Araya, A A

    1982-01-01

    Intelligent systems should possess two fundamental capabilities: problem solving and learning. Problem solving capabilities allow an intelligent system to cope with problems in a given domain. Learning capabilities make possible for an intelligent system to improve the solution to the problems within its current reach or to cope with new problems. This paper examines research in artificial intelligence from the perspective of learning with the purpose of: 1) developing and understanding of the problem of learning from the AI point of view, and II) characterizing the current state of the art on learning in AI. 35 references.

  5. Hybrid-augmented intelligence:collaboration and cognition

    Institute of Scientific and Technical Information of China (English)

    Nan-ning ZHENG; Zi-yi LIU; Peng-ju REN; Yong-qiang MA; Shi-tao CHEN; Si-yu YU; Jian-ru XUE

    2017-01-01

    The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models:one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

  6. On the Edge: Intelligent CALL in the 1990s.

    Science.gov (United States)

    Underwood, John

    1989-01-01

    Examines the possibilities of developing computer-assisted language learning (CALL) based on the best of modern technology, arguing that artificial intelligence (AI) strategies will radically improve the kinds of exercises that can be performed. Recommends combining AI technology with other tools for delivering instruction, such as simulation and…

  7. The Seeds of Artificial Intelligence. SUMEX-AIM.

    Science.gov (United States)

    Research Resources Information Center, Rockville, MD.

    Written to provide an understanding of the broad base of information on which the artificial intelligence (AI) branch of computer science rests, this publication presents a general view of AI, the concepts from which it evolved, its current abilities, and its promise for research. The focus is on a community of projects that use the SUMEX-AIM…

  8. Second Conference on Artificial Intelligence for Space Applications

    Science.gov (United States)

    Dollman, Thomas (Compiler)

    1988-01-01

    The proceedings of the conference are presented. This second conference on Artificial Intelligence for Space Applications brings together a diversity of scientific and engineering work and is intended to provide an opportunity for those who employ AI methods in space applications to identify common goals and to discuss issues of general interest in the AI community.

  9. Introduction to the Articles on Innovative Applications of Artificial Intelligence

    OpenAIRE

    Rychtyckyj, Nestor; Shapiro, Daniel

    2011-01-01

    This issue of AI Magazine provides extended versions of several papers that were recently presented at the Innovative Applications of Artificial Intelligence Conference (IAAI-2010). We present three articles reflecting deployed applications of AI, one describing a unique, emerging application, plus an article based on the invited talk by Jay M. Tenenbaum, who was the 2010 Engelmore Award recipient.

  10. Artificial Intelligence in Business: Technocrat Jargon or Quantum Leap?

    Science.gov (United States)

    Burford, Anna M.; Wilson, Harold O.

    This paper addresses the characteristics and applications of artificial intelligence (AI) as a subsection of computer science, and briefly describes the most common types of AI programs: expert systems, natural language, and neural networks. Following a brief presentation of the historical background, the discussion turns to an explanation of how…

  11. Artificial Intelligence: Realizing the Ultimate Promises of Computing

    OpenAIRE

    Waltz, David L.

    1997-01-01

    Artificial intelligence (AI) is the key technology in many of today's novel applications, ranging from banking systems that detect attempted credit card fraud, to telephone systems that understand speech, to software systems that notice when you're having problems and offer appropriate advice. These technologies would not exist today without the sustained federal support of fundamental AI research over the past three decades.

  12. A brief overview of artificial intelligence in South Africa

    CSIR Research Space (South Africa)

    Ferrein, A

    2013-10-01

    Full Text Available One of the consequences of the growth in AI research in South Africa in recent years is the establishment of a number of research hubs involved in AI activities ranging from mobile robotics and computational intelligence to knowledge representation...

  13. An SDR based AIS receiver for satellites

    DEFF Research Database (Denmark)

    Larsen, Jesper Abildgaard; Mortensen, Hans Peter; Nielsen, Jens Frederik Dalsgaard

    2011-01-01

    For a few years now, there has been a high interest in monitoring the global ship traffic from space. A few satellite, capable of listening for ship borne AIS transponders have already been launched, and soon the AAUSAT3, carrying two different types of AIS receivers will also be launched. One...... of the AIS receivers onboard AAUSAT3 is an SDR based AIS receiver. This paper serves to describe the background of the AIS system, and how the SDR based receiver has been integrated into the AAUSAT3 satellite. Amongst some of the benefits of using an SDR based receiver is, that due to its versatility, new...... detection algorithms are easily deployed, and it is easily adapted the new proposed AIS transmission channels....

  14. True Visions The Emergence of Ambient Intelligence

    CERN Document Server

    Aarts, Emile

    2006-01-01

    Ambient intelligence (AI) refers to a developing technology that will increasingly make our everyday environment sensitive and responsive to our presence. The AI vision requires technology invisibly embedded in our everyday surroundings, present whenever we need it that will lead to the seamless integration of lighting, sounds, vision, domestic appliances, and personal healthcare products to enhance our living experience. Written for the non-specialist seeking an authoritative but accessible overview of this interdisciplinary field, True Visions explains how the devices making up the AI world will operate collectively using information and intelligence hidden in the wireless network connecting them. Expert contributions address key AI components such as smart materials and textiles, system architecture, mobile computing, broadband communication, and underlying issues of human-environment interactions. It seeks to unify the perspectives of scientists from diverse backgrounds ranging from the physics of materia...

  15. Artificial Intelligence as Structural Estimation: Economic Interpretations of Deep Blue, Bonanza, and AlphaGo

    OpenAIRE

    Igami, Mitsuru

    2017-01-01

    Artificial intelligence (AI) has achieved superhuman performance in a growing number of tasks, but understanding and explaining AI remain challenging. This paper clarifies the connections between machine-learning algorithms to develop AIs and the econometrics of dynamic structural models through the case studies of three famous game AIs. Chess-playing Deep Blue is a calibrated value function, whereas shogi-playing Bonanza is an estimated value function via Rust's (1987) nested fixed-point met...

  16. Fifth Conference on Artificial Intelligence for Space Applications

    Science.gov (United States)

    Odell, Steve L. (Compiler)

    1990-01-01

    The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration.

  17. IJCAI-91 Workshop on Objects and Artificial Intelligence

    OpenAIRE

    Hatzilygeroudis, Ioannis

    1994-01-01

    The Objects and Artificial Intelligence Workshop was held on 25 August 1991 in conjunction with the 1991 International Joint Conference on Artificial Intelligence. The workshop brought together researchers in AI and object-oriented programming to exchange ideas and investigate possible avenues of cooperation between AI and object-oriented programming. The workshop dealt with both the theoretical and the practical aspects of this cooperation.

  18. Human Brain inspired Artificial Intelligence & Developmental Robotics: A Review

    Directory of Open Access Journals (Sweden)

    Suresh Kumar

    2017-06-01

    Full Text Available Along with the developments in the field of the robotics, fascinating contributions and developments can be seen in the field of Artificial intelligence (AI. In this paper we will discuss about the developments is the field of artificial intelligence focusing learning algorithms inspired from the field of Biology, particularly large scale brain simulations, and developmental Psychology. We will focus on the emergence of the Developmental robotics and its significance in the field of AI.

  19. A Python Engine for Teaching Artificial Intelligence in Games

    OpenAIRE

    Riedl, Mark O.

    2015-01-01

    Computer games play an important role in our society and motivate people to learn computer science. Since artificial intelligence is integral to most games, they can also be used to teach artificial intelligence. We introduce the Game AI Game Engine (GAIGE), a Python game engine specifically designed to teach about how AI is used in computer games. A progression of seven assignments builds toward a complete, working Multi-User Battle Arena (MOBA) game. We describe the engine, the assignments,...

  20. A study on the applications of AI in finishing of additive manufacturing parts

    Science.gov (United States)

    Fathima Patham, K.

    2017-06-01

    Artificial intelligent and computer simulation are the technological powerful tools for solving complex problems in the manufacturing industries. Additive Manufacturing is one of the powerful manufacturing techniques that provide design flexibilities to the products. The products with complex shapes are directly manufactured without the need of any machining and tooling using Additive Manufacturing. However, the main drawback of the components produced using the Additive Manufacturing processes is the quality of the surfaces. This study aims to minimize the defects caused during Additive Manufacturing with the aid of Artificial Intelligence. The developed AI system has three layers, each layer is trying to eliminate or minimize the production errors. The first layer of the AI system optimizes the digitization of the 3D CAD model of the product and hence reduces the stair case errors. The second layer of the AI system optimizes the 3D printing machine parameters in order to eliminate the warping effect. The third layer of AI system helps to choose the surface finishing technique suitable for the printed component based on the Degree of Complexity of the product and the material. The efficiency of the developed AI system was examined on the functional parts such as gears.

  1. USACE AIS Transmit Technical Support Summary Report

    Science.gov (United States)

    2014-09-01

    the TAG block for the correct transmitters, and then send to the USACE AIS network. B. Outbound openings in the USCG firewall for the USCG Message...USACE AIS Transmit Technical Support Summary Report Distribution Statement A: Approved for public release; distribution is unlimited...September 2014 Report No. CD-D-09-15 USACE AIS Transmit Technical Support Summary Report ii UNCLAS//Public | CG-926 RDC | I. Gonin et al. Public

  2. US Ports of Entry

    Data.gov (United States)

    Department of Homeland Security — HSIP Non-Crossing Ports-of-Entry A Port of Entry is any designated place at which a CBP officer is authorized to accept entries of merchandise to collect duties, and...

  3. Worldwide Intelligent Systems: Approaches to Telecommunications and Network Management. Frontiers in Artificial Intelligence and Applications, Volume 24.

    Science.gov (United States)

    Liebowitz, Jay, Ed.; Prerau, David S., Ed.

    This is an international collection of 12 papers addressing artificial intelligence (AI) and knowledge technology applications in telecommunications and network management. It covers the latest and emerging AI technologies as applied to the telecommunications field. The papers are: "The Potential for Knowledge Technology in…

  4. Shimadzu AI-PACS 'SAIPACS'

    International Nuclear Information System (INIS)

    Andoh, Minoru; Asai, Shigeya; Matsui, Norihisa; Nishida, Shinichiro; Horino, Masato

    1990-01-01

    The PACS-WS named SAIPACS-WS(workstation) has been developed as the first step of complete PACS. This SAIPACS-WS is different from other PACS-WS's, because this is including computer aided diagnostic reporting and computer aided diagnosis by using artificial intelligence technique. In this paper we will report detail of the SAIPACS-WS and discuss the future development of the total PACS setting the SAIPACS-WS in its center. (author)

  5. Adaptive Motion Gaming AI for Health Promotion

    OpenAIRE

    Paliyawan, Pujana; Kusano, Takahiro; Nakagawa, Yuto; Harada, Tomohiro; Thawonmas, Ruck

    2017-01-01

    This paper presents a design of a non-player character (AI) for promoting balancedness in use of body segments when engaging in full-body motion gaming. In our experiment, we settle a battle between the proposed AI and a player by using FightingICE, a fighting game platform for AI development. A middleware called UKI is used to allow the player to control the game by using body motion instead of the keyboard and mouse. During gameplay, the proposed AI analyze health states of the player; it d...

  6. Artificial Intelligence techniques for big data analysis

    OpenAIRE

    Aditya Khatri

    2017-01-01

    During my stay in Salamanca (Spain), I was fortunate enough to participate in the BISITE Research Group of the University of Salamanca. The University of Salamanca is the oldest university in Spain and in 2018 it celebrates its 8th centenary. As a computer science researcher, I participated in one of the many international projects that the research group has active, especially in big data analysis using Artificial Intelligence (AI) techniques. AI is one of BISITE's main lines of rese...

  7. Parallel processing for artificial intelligence 1

    CERN Document Server

    Kanal, LN; Kumar, V; Suttner, CB

    1994-01-01

    Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discus

  8. Applications of artificial intelligence to scientific research

    Science.gov (United States)

    Prince, Mary Ellen

    1986-01-01

    Artificial intelligence (AI) is a growing field which is just beginning to make an impact on disciplines other than computer science. While a number of military and commercial applications were undertaken in recent years, few attempts were made to apply AI techniques to basic scientific research. There is no inherent reason for the discrepancy. The characteristics of the problem, rather than its domain, determines whether or not it is suitable for an AI approach. Expert system, intelligent tutoring systems, and learning programs are examples of theoretical topics which can be applied to certain areas of scientific research. Further research and experimentation should eventurally make it possible for computers to act as intelligent assistants to scientists.

  9. Artificial Intelligence and the Future of Defense

    DEFF Research Database (Denmark)

    De Spiegeleire, Stephan; Maas, Matthijs Michiel; Sweijs, Tim

    Artificial intelligence (AI) is on everybody’s minds these days. Most of the world’s leading companies are making massive investments in it. Governments are scrambling to catch up. Every single one of us who uses Google Search or any of the new digital assistants on our smartphones has witnessed...... suggests that the advent of artificial super-intelligence (i.e. AI that is superior across the board to human intelligence), which many experts now put firmly within the longer-term planning horizons of our DSOs, presents us with unprecedented risks but also opportunities that we have to start to explore....... The report contains an overview of the role that ‘intelligence’ - the computational part of the ability to achieve goals in the world - has played in defense and security throughout human history; a primer on AI (what it is, where it comes from and where it stands today - in both civilian and military...

  10. Artificial intelligence applications in space and SDI: A survey

    Science.gov (United States)

    Fiala, Harvey E.

    1988-01-01

    The purpose of this paper is to survey existing and planned Artificial Intelligence (AI) applications to show that they are sufficiently advanced for 32 percent of all space applications and SDI (Space Defense Initiative) software to be AI-based software. To best define the needs that AI can fill in space and SDI programs, this paper enumerates primary areas of research and lists generic application areas. Current and planned NASA and military space projects in AI will be reviewed. This review will be largely in the selected area of expert systems. Finally, direct applications of AI to SDI will be treated. The conclusion covers the importance of AI to space and SDI applications, and conversely, their importance to AI.

  11. Artificial intelligence and knowledge management

    OpenAIRE

    Hoesch, Hugo Cesar; Barcellos, Vânia

    2006-01-01

    This article intends to make an analysis about the Artificial Intelligence (AI) and the Knowledge Management (KM). Faced with the dualism mind and body how we be able to see it AI? It doesn’t intent to create identical copy of human being, but try to find the better form to represent all the knowledge contained in our minds. The society of the information lives a great paradox, at the same time that we have access to an innumerable amount of information, the capacity and the forms of its proc...

  12. Improving designer productivity. [artificial intelligence

    Science.gov (United States)

    Hill, Gary C.

    1992-01-01

    Designer and design team productivity improves with skill, experience, and the tools available. The design process involves numerous trials and errors, analyses, refinements, and addition of details. Computerized tools have greatly speeded the analysis, and now new theories and methods, emerging under the label Artificial Intelligence (AI), are being used to automate skill and experience. These tools improve designer productivity by capturing experience, emulating recognized skillful designers, and making the essence of complex programs easier to grasp. This paper outlines the aircraft design process in today's technology and business climate, presenting some of the challenges ahead and some of the promising AI methods for meeting these challenges.

  13. Epistasis analysis using artificial intelligence.

    Science.gov (United States)

    Moore, Jason H; Hill, Doug P

    2015-01-01

    Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

  14. Groundhog Day for Medical Artificial Intelligence.

    Science.gov (United States)

    London, Alex John

    2018-05-01

    Following a boom in investment and overinflated expectations in the 1980s, artificial intelligence entered a period of retrenchment known as the "AI winter." With advances in the field of machine learning and the availability of large datasets for training various types of artificial neural networks, AI is in another cycle of halcyon days. Although medicine is particularly recalcitrant to change, applications of AI in health care have professionals in fields like radiology worried about the future of their careers and have the public tittering about the prospect of soulless machines making life-and-death decisions. Medicine thus appears to be at an inflection point-a kind of Groundhog Day on which either AI will bring a springtime of improved diagnostic and predictive practices or the shadow of public and professional fear will lead to six more metaphorical weeks of winter in medical AI. © 2018 The Hastings Center.

  15. Artificial intelligence in process design and operation

    International Nuclear Information System (INIS)

    Sudduth, A.L.

    1988-01-01

    Artificial Intelligence (AI) has recently become prominent in the discussion of computer applications in the utility business. In order to assess this technology, a research project was performed to determine whether software development techniques based on AI could be used to facilitate management of information associated with the design of a generating station. The approach taken was the development of an expert system, using a relatively simple set of rules acting on a more complex knowledge base. A successful prototype for the application was developed and its potential extension to a production environment demonstrated. During the course of prototype development, other possible applications of AI in design engineering were discovered, and areas of particular interest selected for further investigation. A plan for AI R and D was formulated. That plan and other possible future work in AI are discussed

  16. Intelligent structural optimization: Concept, Model and Methods

    International Nuclear Information System (INIS)

    Lu, Dagang; Wang, Guangyuan; Peng, Zhang

    2002-01-01

    Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented

  17. A study on the Web intelligence

    Institute of Scientific and Technical Information of China (English)

    Sang-Geun Kim

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI). WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web - related products, systens, and activities. As a direction for scientific research and devlopment, WI can be extremely beneficial for the field of Artificial Intelligence in Education (AIED). This paper covers these issues only very briefly. It focuses more on other issues in WI, such as intelligent Web services, and semantic web, and proposes how to use them as basis for tackling new and challenging research problems in AIED.

  18. Philosophy and Theory of Artificial Intelligence

    CERN Document Server

    2013-01-01

    Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we s...

  19. Improving Tools in Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-01-01

    Full Text Available The historical origin of the Artificial Intelligence (AI is usually established in the Dartmouth Conference, of 1956. But we can find many more arcane origins [1]. Also, we can consider, in more recent times, very great thinkers, as Janos Neumann (then, John von Neumann, arrived in USA, Norbert Wiener, Alan Mathison Turing, or Lofti Zadeh, for instance [12, 14]. Frequently AI requires Logic. But its Classical version shows too many insufficiencies. So, it was necessary to introduce more sophisticated tools, as Fuzzy Logic, Modal Logic, Non-Monotonic Logic and so on [1, 2]. Among the things that AI needs to represent are categories, objects, properties, relations between objects, situations, states, time, events, causes and effects, knowledge about knowledge, and so on. The problems in AI can be classified in two general types [3, 5], search problems and representation problems. On this last "peak", there exist different ways to reach their summit. So, we have [4] Logics, Rules, Frames, Associative Nets, Scripts, and so on, many times connected among them. We attempt, in this paper, a panoramic vision of the scope of application of such representation methods in AI. The two more disputable questions of both modern philosophy of mind and AI will be perhaps the Turing Test and the Chinese Room Argument. To elucidate these very difficult questions, see our final note.

  20. JGOMAS: New Approach to AI Teaching

    Science.gov (United States)

    Barella, A.; Valero, S.; Carrascosa, C.

    2009-01-01

    This paper presents a new environment for teaching practical work in AI subjects. The main purpose of this environment is to make AI techniques more appealing to students and to facilitate the use of the toolkits which are currently widely used in research and development. This new environment has a toolkit for developing and executing agents,…

  1. 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

  2. Artificial Intelligence and brain.

    Science.gov (United States)

    Shapshak, Paul

    2018-01-01

    From the start, Kurt Godel observed that computer and brain paradigms were considered on a par by researchers and that researchers had misunderstood his theorems. He hailed with displeasure that the brain transcends computers. In this brief article, we point out that Artificial Intelligence (AI) comprises multitudes of human-made methodologies, systems, and languages, and implemented with computer technology. These advances enhance development in the electron and quantum realms. In the biological realm, animal neurons function, also utilizing electron flow, and are products of evolution. Mirror neurons are an important paradigm in neuroscience research. Moreover, the paradigm shift proposed here - 'hall of mirror neurons' - is a potentially further productive research tactic. These concepts further expand AI and brain research.

  3. Application of artificial intelligence in process control

    CERN Document Server

    Krijgsman, A

    1993-01-01

    This book is the result of a united effort of six European universities to create an overall course on the appplication of artificial intelligence (AI) in process control. The book includes an introduction to key areas including; knowledge representation, expert, logic, fuzzy logic, neural network, and object oriented-based approaches in AI. Part two covers the application to control engineering, part three: Real-Time Issues, part four: CAD Systems and Expert Systems, part five: Intelligent Control and part six: Supervisory Control, Monitoring and Optimization.

  4. Integrated Artificial Intelligence Approaches for Disease Diagnostics.

    Science.gov (United States)

    Vashistha, Rajat; Chhabra, Deepak; Shukla, Pratyoosh

    2018-06-01

    Mechanocomputational techniques in conjunction with artificial intelligence (AI) are revolutionizing the interpretations of the crucial information from the medical data and converting it into optimized and organized information for diagnostics. It is possible due to valuable perfection in artificial intelligence, computer aided diagnostics, virtual assistant, robotic surgery, augmented reality and genome editing (based on AI) technologies. Such techniques are serving as the products for diagnosing emerging microbial or non microbial diseases. This article represents a combinatory approach of using such approaches and providing therapeutic solutions towards utilizing these techniques in disease diagnostics.

  5. Nonlinear study of AI Velorum

    International Nuclear Information System (INIS)

    Cox, A.N.; Hodson, S.W.

    1979-01-01

    Using results from earlier studies of double-mode dwarf Cepheids by Cox, King, and Hodson, hydrodynamic calculations were undertaken for AI Vel. The earlier derived evolution theory mass of 1.8 M sub solar, a luminosity of of 23 L sub solar and a T/sub e/ of 7500 0 K give the observed period of 0.11 day and the observed period ratio PI 1 /PI 0 = 0.773. A cooler T/sub e/ than the observed one (7620 0 K) was used because 7620 0 K is beyond the fundamental pulsation mode blue edge. The composition used is X = 0.70 Z = 0.01. This lower than normal Z is necessary to make the period ratio as large as observed. The goal is to see if double-mode behavior, due to either mode switching or a permanent state, can be predicted for the model. Progress in converging the model to a periodic pulsation solution by the von Sengbusch--Stellingwerf relaxation method will be reported. 17 references

  6. Toward New-Generation Intelligent Manufacturing

    Directory of Open Access Journals (Sweden)

    Ji Zhou

    2018-02-01

    Full Text Available Intelligent manufacturing is a general concept that is under continuous development. It can be categorized into three basic paradigms: digital manufacturing, digital-networked manufacturing, and new-generation intelligent manufacturing. New-generation intelligent manufacturing represents an in-depth integration of new-generation artificial intelligence (AI technology and advanced manufacturing technology. It runs through every link in the full life-cycle of design, production, product, and service. The concept also relates to the optimization and integration of corresponding systems; the continuous improvement of enterprises’ product quality, performance, and service levels; and reduction in resources consumption. New-generation intelligent manufacturing acts as the core driving force of the new industrial revolution and will continue to be the main pathway for the transformation and upgrading of the manufacturing industry in the decades to come. Human-cyber-physical systems (HCPSs reveal the technological mechanisms of new-generation intelligent manufacturing and can effectively guide related theoretical research and engineering practice. Given the sequential development, cross interaction, and iterative upgrading characteristics of the three basic paradigms of intelligent manufacturing, a technology roadmap for “parallel promotion and integrated development” should be developed in order to drive forward the intelligent transformation of the manufacturing industry in China. Keywords: Advanced manufacturing, New-generation intelligent manufacturing, Human-cyber-physical system, New-generation AI, Basic paradigms, Parallel promotion, Integrated development

  7. AI based HealthCare Platform for Real Time, Predictive and Prescriptive Analytics using Reactive Programming

    Science.gov (United States)

    Kaur, Jagreet; Singh Mann, Kulwinder, Dr.

    2018-01-01

    AI in Healthcare needed to bring real, actionable insights and Individualized insights in real time for patients and Doctors to support treatment decisions., We need a Patient Centred Platform for integrating EHR Data, Patient Data, Prescriptions, Monitoring, Clinical research and Data. This paper proposes a generic architecture for enabling AI based healthcare analytics Platform by using open sources Technologies Apache beam, Apache Flink Apache Spark, Apache NiFi, Kafka, Tachyon, Gluster FS, NoSQL- Elasticsearch, Cassandra. This paper will show the importance of applying AI based predictive and prescriptive analytics techniques in Health sector. The system will be able to extract useful knowledge that helps in decision making and medical monitoring in real-time through an intelligent process analysis and big data processing.

  8. Deep into the Brain: Artificial Intelligence in Stroke Imaging.

    Science.gov (United States)

    Lee, Eun-Jae; Kim, Yong-Hwan; Kim, Namkug; Kang, Dong-Wha

    2017-09-01

    Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives.

  9. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part B: Applications

    Science.gov (United States)

    Gevarter, W. B.

    1983-01-01

    Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. This report, Part B of a three part report on AI, presents overviews of the key application areas: Expert Systems, Computer Vision, Natural Language Processing, Speech Interfaces, and Problem Solving and Planning. The basic approaches to such systems, the state-of-the-art, existing systems and future trends and expectations are covered.

  10. System for intelligent teleoperation research

    International Nuclear Information System (INIS)

    Orlando, N.E.

    1983-01-01

    The Automation Technology Branch of NASA Langley Research Center is developing a research capability in the field of artificial intelligence, particularly as applicable in teleoperator/robotics development for remote space operations. As a testbed for experimentation in these areas, a system concept has been developed and is being implemented. This system, termed DAISIE (Distributed Artificially Intelligent System for Interacting with the Environment), interfaces the key processes of perception, reasoning, and manipulation by linking hardware sensors and manipulators to a modular artificial intelligence (AI) software system in a hierarchical control structure. Verification experiments have been performed: one experiment used a blocksworld database and planner embedded in the DAISIE system to intelligently manipulate a simple physical environment; the other experiment implemented a joint-space collision avoidance algorithm. Continued system development is planned

  11. The coming of age of artificial intelligence in medicine

    NARCIS (Netherlands)

    Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-01-01

    This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in

  12. Artificial Intelligence and Educational Technology: A Natural Synergy. Extended Abstract.

    Science.gov (United States)

    McCalla, Gordon I.

    Educational technology and artificial intelligence (AI) are natural partners in the development of environments to support human learning. Designing systems with the characteristics of a rich learning environment is the long term goal of research in intelligent tutoring systems (ITS). Building these characteristics into a system is extremely…

  13. Active and intelligent food packaging: legal aspects and safety concerns

    NARCIS (Netherlands)

    Dainelli, D.; Gontard, N.; Spyropoulos, D.; Zondervan-van den Beuken, E.; Tobback, P.

    2008-01-01

    'Active and intelligent' (A&I) food packaging is based on a deliberate interaction of the packaging with the food and/or its direct environment. This article presents: (i) the main types of materials developed for food contact; (ii) the global market and the future trends of active and intelligent

  14. Ethico-epistemological implications of artificial intelligence for ...

    African Journals Online (AJOL)

    We argued for a re-direction of AI. research and suggested a humanization of Artificial Intelligence that cloaks technoscientific innovations with humanistic life jackets for man‟s preservation. The textual analysis method is adopted for this research. Key words: Ethics, Epistemology, Artificial Intelligence, Humanity.

  15. "All-In-One Test" (AI1)

    DEFF Research Database (Denmark)

    Giacalone, Davide; Bredie, Wender Laurentius Petrus; Frøst, Michael Bom

    2013-01-01

    by the Check-All-That-Apply (CATA) technique is reported. In this exploratory "All-In-One Test"(AI1), subjects (N = 160) filled out a questionnaire with demographic and psychographic variables, and appropriateness ratings for specific sensory descriptors of beer. Subsequently, subjects gave hedonic ratings...... between appropriateness and actual hedonic response. Overall, the AI1 test provided interpretable results concerning consumer perception (sensory/hedonic) of the beers, and revealed relations with consumers' background information. Initial results with AI1 test show that it is an efficient and versatile...

  16. Health Information in French (français)

    Science.gov (United States)

    ... Biopsy - français (French) Bilingual PDF Health Information Translations Breast Biopsy - français (French) Bilingual PDF Health Information Translations Colposcopy - français (French) Bilingual PDF ...

  17. Art in the Age of Machine Intelligence

    Directory of Open Access Journals (Sweden)

    Blaise Agüera y Arcas

    2017-09-01

    Full Text Available In this wide‐ranging essay, the leader of Google’s Seattle AI group and founder of the Artists and Machine Intelligence program discusses the long‐standing and complex relationship between art and technology. The transformation of artistic practice and theory that attended the 19th century photographic revolution is explored as a parallel for the current revolution in machine intelligence, which promises not only to mechanize (or democratize the means of reproduction, but also of production.

  18. ARTIFICIAL INTELLIGENCE- BENEFITS, CHALLENGES AND ETHICAL ISSUES

    OpenAIRE

    Elena Juganaru Andreou

    2017-01-01

    Nowadays, all big companies and most of small businesses are focused on increasing profitability and improving competitiveness. With this goal in mind, many of them turned to replace many tasks performed by humans with Artificial Intelligence. Artificial Intelligence (AI) is receiving an increasing attention lately and the debate is fiercely growing with a question not being answered yet: will it change the world for the better or for worse?

  19. The 2002 Starting Artificial Intelligence Researchers Symposium

    OpenAIRE

    Vidal, Thierry

    2003-01-01

    During the 2002 European Conference on Artificial Intelligence (ECAI-02) was introduced the Starting Artificial Intelligence Researchers Symposium STAIRS), the first-ever international symposium specifically aimed at Ph.D. students in AI. The outcome was a thorough, high-quality, and successful event, with all the features one usually finds in the best international conferences: large international committees, comprehensive coverage, published proceedings, renowned speakers and panelists, sub...

  20. Fully automatic AI-based leak detection system

    Energy Technology Data Exchange (ETDEWEB)

    Tylman, Wojciech; Kolczynski, Jakub [Dept. of Microelectronics and Computer Science, Technical University of Lodz in Poland, ul. Wolczanska 221/223, Lodz (Poland); Anders, George J. [Kinectrics Inc., 800 Kipling Ave., Toronto, Ontario M8Z 6C4 (Canada)

    2010-09-15

    This paper presents a fully automatic system intended to detect leaks of dielectric fluid in underground high-pressure, fluid-filled (HPFF) cables. The system combines a number of artificial intelligence (AI) and data processing techniques to achieve high detection capabilities for various rates of leaks, including leaks as small as 15 l per hour. The system achieves this level of precision mainly thanks to a novel auto-tuning procedure, enabling learning of the Bayesian network - the decision-making component of the system - using simulated leaks of various rates. Significant new developments extending the capabilities of the original leak detection system described in and form the basis of this paper. Tests conducted on the real-life HPFF cable system in New York City are also discussed. (author)

  1. Planning chemical syntheses with deep neural networks and symbolic AI

    Science.gov (United States)

    Segler, Marwin H. S.; Preuss, Mike; Waller, Mark P.

    2018-03-01

    To plan the syntheses of small organic molecules, chemists use retrosynthesis, a problem-solving technique in which target molecules are recursively transformed into increasingly simpler precursors. Computer-aided retrosynthesis would be a valuable tool but at present it is slow and provides results of unsatisfactory quality. Here we use Monte Carlo tree search and symbolic artificial intelligence (AI) to discover retrosynthetic routes. We combined Monte Carlo tree search with an expansion policy network that guides the search, and a filter network to pre-select the most promising retrosynthetic steps. These deep neural networks were trained on essentially all reactions ever published in organic chemistry. Our system solves for almost twice as many molecules, thirty times faster than the traditional computer-aided search method, which is based on extracted rules and hand-designed heuristics. In a double-blind AB test, chemists on average considered our computer-generated routes to be equivalent to reported literature routes.

  2. Applying AI techniques to improve alarm display effectiveness

    International Nuclear Information System (INIS)

    Gross, J.M.; Birrer, S.A.; Crosberg, D.R.

    1987-01-01

    The Alarm Filtering System (AFS) addresses the problem of information overload in a control room during abnormal operations. Since operators can miss vital information during these periods, systems which emphasize important messages are beneficial. AFS uses the artificial intelligence (AI) technique of object-oriented programming to filter and dynamically prioritize alarm messages. When an alarm's status changes, AFS determines the relative importance of that change according to the current process state. AFS bases that relative importance on relationships the newly changed alarm has with other activated alarms. Evaluations of a alarm importance take place without regard to the activation sequence of alarm signals. The United States Department of Energy has applied for a patent on the approach used in this software. The approach was originally developed by EG and G Idaho for a nuclear reactor control room

  3. Orthogonally Evolved AI to Improve Difficulty Adjustment in Video Games

    DEFF Research Database (Denmark)

    Hintze, Arend; Olson, Randal; Lehman, Joel Anthony

    2016-01-01

    Computer games are most engaging when their difficulty is well matched to the player's ability, thereby providing an experience in which the player is neither overwhelmed nor bored. In games where the player interacts with computer-controlled opponents, the difficulty of the game can be adjusted...... not only by changing the distribution of opponents or game resources, but also through modifying the skill of the opponents. Applying evolutionary algorithms to evolve the artificial intelligence that controls opponent agents is one established method for adjusting opponent difficulty. Less-evolved agents...... (i.e. agents subject to fewer generations of evolution) make for easier opponents, while highly-evolved agents are more challenging to overcome. In this publication we test a new approach for difficulty adjustment in games: orthogonally evolved AI, where the player receives support from collaborating...

  4. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

    Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

  5. The Singularity, or How I Learned to Stop Worrying and Love AI

    OpenAIRE

    Bishop, Mark (J. M.)

    2015-01-01

    Professor Stephen Hawking recently warned about the growing power of Artificial Intelligence (AI) to imbue robots with the ability to both replicate them- selves and to increase the rate at which they get smarter - leading to a tipping point or ‘technological singularity’ when they can outsmart humans. In this chapter I will argue that Hawking is essentially correct to flag up an existential danger surrounding widespread deployment of ‘autonomous machines’, but wrong to be so concerned about ...

  6. Sensor assignment to mission in AI-TECD

    Science.gov (United States)

    Ganger, Robert; de Mel, Geeth; Pham, Tien; Rudnicki, Ronald; Schreiber, Yonatan

    2016-05-01

    Sensor-mission assignment involves the allocation of sensors and other information-providing resources to missions in order to cover the information needs of the individual tasks within each mission. The importance of efficient and effective means to find appropriate resources for tasks is exacerbated in the coalition context where the operational environment is dynamic and a multitude of critically important tasks need to achieve their collective goals to meet the objectives of the coalition. The Sensor Assignment to Mission (SAM) framework—a research product of the International Technology Alliance in Network and Information Sciences (NIS-ITA) program—provided the first knowledge intensive resource selection approach for the sensor network domain so that contextual information could be used to effectively select resources for tasks in coalition environments. Recently, CUBRC, Inc. was tasked with operationalizing the SAM framework through the use of the I2WD Common Core Ontologies for the Communications-Electronics Research, Development and Engineering Center (CERDEC) sponsored Actionable Intelligence Technology Enabled Capabilities Demonstration (AI-TECD). The demonstration event took place at Fort Dix, New Jersey during July 2015, and this paper discusses the integration and the successful demonstration of the SAM framework within the AI-TECD, lessons learned, and its potential impact in future operations.

  7. Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  8. Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  9. The coming of age of artificial intelligence in medicine

    OpenAIRE

    Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-01-01

    This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its “adolescence” (Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ‘90s? Artificial Intelligence in Medicine 1993; 5:93–106). In this article, the ...

  10. AIS Ship Traffic: Hawaii: 2011-2012

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Ship position data from a satellite-based Automatic Identification System (AIS) were obtained jointly by PacIOOS (J. Potemra), SOEST/ORE of the University of Hawaii...

  11. Cracks appear in the AI gravy train

    Energy Technology Data Exchange (ETDEWEB)

    Mill, J.

    1983-10-01

    This article highlights some of the problems facing the Alvey committee and outlines some reasons for believing that the optimistically founded Alvey and Esprit funding programmes are no guarantee Britain will win the AI race.

  12. National AIS at 1 Minute Intervals

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — OCM plans to contract for AIS data per the following description. The United States Automatic Identification System Database contains vessel traffic data for...

  13. Biomimetics in Intelligent Sensor and Actuator Automation Systems

    Science.gov (United States)

    Bruckner, Dietmar; Dietrich, Dietmar; Zucker, Gerhard; Müller, Brit

    Intelligent machines are really an old mankind's dream. With increasing technological development, the requirements for intelligent devices also increased. However, up to know, artificial intelligence (AI) lacks solutions to the demands of truly intelligent machines that have no problems to integrate themselves into daily human environments. Current hardware with a processing power of billions of operations per second (but without any model of human-like intelligence) could not substantially contribute to the intelligence of machines when compared with that of the early AI times. There are great results, of course. Machines are able to find the shortest path between far apart cities on the map; algorithms let you find information described only by few key words. But no machine is able to get us a cup of coffee from the kitchen yet.

  14. Learning game AI programming with Lua

    CERN Document Server

    Young, David

    2014-01-01

    If you are a game developer or a general programmer who wishes to focus on programming systems and techniques to build your game AI without creating low-level interfaces in a game engine, then this book is for you. Knowledge of C++ will come in handy to debug the entirety of the AI sandbox and expand on the features present within the book, but it is not required.

  15. 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...

  16. Research Directions for AI in Computer Games

    OpenAIRE

    Fairclough, Chris; Fagan, Michael; Cunningham, Padraig; Mac Namee, Brian

    2001-01-01

    The computer games industry is now bigger than the film industry. Until recently, technology in games was driven by a desire to achieve real-time, photo-realistic graphics. To a large extent, this has now been achieved. As game developers look for new and innovative technologies to drive games development, AI is coming to the fore. This paper will examine how sophisticated AI techniques, such as those being used in mainstream academic research, can be applied to computer games ...

  17. A regulator's viewpoint on the use of AI in the nuclear industry

    International Nuclear Information System (INIS)

    Wainwright, N.

    1995-01-01

    The regulatory position within the UK places the responsibility for safety on a nuclear site with the licensee. The licensee must produce a safety case that demonstrates that the plant is safe. Assessment of this safety case is performed by the regulator in the Health and Safety Executive (HSE) using HSE's published Safety Assessment Principles. This paper presents the personal views of a regulator on the use of artificial intelligence (AI) in the nuclear industry. The AI-based system considered are restricted to expert systems, neural networks and fuzzy logic. Some of the safety issues are discussed. The particular concerns associated with software-based systems are compounded by some of the inherent problems of AI-based systems. Such is the nature of these concerns that an acceptable safety case will be difficult to mount for safety systems and post-accident monitoring systems. However, given the present maturity of the technology, acceptable safety cases might be formulated in the areas of operator advisory systems designed to reduce accident frequencies, and robotics where dose reduction is important. There are also arguments that suggests that suitable safety cases could be formulated for AI-based plant control systems. Nevertheless, AI-based systems should be treated with caution - further research is required into suitable designs and safety demonstration techniques. (author)

  18. Advanced Applications of Neural Networks and Artificial Intelligence: A Review

    OpenAIRE

    Koushal Kumar; Gour Sundar Mitra Thakur

    2012-01-01

    Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields. This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN’s) and Artificial Intelligence (AI). It also considers the integration of neural networks with other computing methods Such as fuzzy logic to enhance the interpretation ability of data. Artificial Neural Networks is c...

  19. Applying AI tools to operational space environmental analysis

    Science.gov (United States)

    Krajnak, Mike; Jesse, Lisa; Mucks, John

    1995-01-01

    The U.S. Air Force and National Oceanic Atmospheric Agency (NOAA) space environmental operations centers are facing increasingly complex challenges meeting the needs of their growing user community. These centers provide current space environmental information and short term forecasts of geomagnetic activity. Recent advances in modeling and data access have provided sophisticated tools for making accurate and timely forecasts, but have introduced new problems associated with handling and analyzing large quantities of complex data. AI (Artificial Intelligence) techniques have been considered as potential solutions to some of these problems. Fielding AI systems has proven more difficult than expected, in part because of operational constraints. Using systems which have been demonstrated successfully in the operational environment will provide a basis for a useful data fusion and analysis capability. Our approach uses a general purpose AI system already in operational use within the military intelligence community, called the Temporal Analysis System (TAS). TAS is an operational suite of tools supporting data processing, data visualization, historical analysis, situation assessment and predictive analysis. TAS includes expert system tools to analyze incoming events for indications of particular situations and predicts future activity. The expert system operates on a knowledge base of temporal patterns encoded using a knowledge representation called Temporal Transition Models (TTM's) and an event database maintained by the other TAS tools. The system also includes a robust knowledge acquisition and maintenance tool for creating TTM's using a graphical specification language. The ability to manipulate TTM's in a graphical format gives non-computer specialists an intuitive way of accessing and editing the knowledge base. To support space environmental analyses, we used TAS's ability to define domain specific event analysis abstractions. The prototype system defines

  20. Artificial intelligence - NASA. [robotics for Space Station

    Science.gov (United States)

    Erickson, J. D.

    1985-01-01

    Artificial Intelligence (AI) represents a vital common space support element needed to enable the civil space program and commercial space program to perform their missions successfully. It is pointed out that advances in AI stimulated by the Space Station Program could benefit the U.S. in many ways. A fundamental challenge for the civil space program is to meet the needs of the customers and users of space with facilities enabling maximum productivity and having low start-up costs, and low annual operating costs. An effective way to meet this challenge may involve a man-machine system in which artificial intelligence, robotics, and advanced automation are integrated into high reliability organizations. Attention is given to the benefits, NASA strategy for AI, candidate space station systems, the Space Station as a stepping stone, and the commercialization of space.

  1. Jesus' Entry into Jerusalem

    Directory of Open Access Journals (Sweden)

    Juho Sankamo

    2014-12-01

    Full Text Available This article intends to contribute to the understanding of Jesus’ entry into Jerusalem. The author studies the entry, which is found in all the Gospels, in its Jewish context. The author argues that Jesus’ entry into Jerusalem on an ass is to be understood as a prophetic sign which was primarily meant to convey a message to the Jews.

  2. 3rd Workshop on "Combinations of Intelligent Methods and Applications"

    CERN Document Server

    Palade, Vasile

    2013-01-01

    The combination of different intelligent methods is a very active research area in Artificial Intelligence (AI). The aim is to create integrated or hybrid methods that benefit from each of their components.  The 3rd Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2012) was intended to become a forum for exchanging experience and ideas among researchers and practitioners who are dealing with combining intelligent methods either based on first principles or in the context of specific applications. CIMA 2012 was held in conjunction with the 22nd European Conference on Artificial Intelligence (ECAI 2012).This volume includes revised versions of the papers presented at CIMA 2012.  .

  3. Case studies in intelligent computing achievements and trends

    CERN Document Server

    Issac, Biju

    2014-01-01

    Although the field of intelligent systems has grown rapidly in recent years, there has been a need for a book that supplies a timely and accessible understanding of this important technology. Filling this need, Case Studies in Intelligent Computing: Achievements and Trends provides an up-to-date introduction to intelligent systems.This edited book captures the state of the art in intelligent computing research through case studies that examine recent developments, developmental tools, programming, and approaches related to artificial intelligence (AI). The case studies illustrate successful ma

  4. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  5. Intelligent mechatronics; Intelligent mechatronics

    Energy Technology Data Exchange (ETDEWEB)

    Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

    1995-10-01

    Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

  6. Artificial intelligence in hematology.

    Science.gov (United States)

    Zini, Gina

    2005-10-01

    Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

  7. Two new Oxalis species (Oxalidaceae) from the Ai-Ais / Richtersveld Transfrontier Park, South Africa

    NARCIS (Netherlands)

    Roets, F.; Oberlander, K.C.; Dreyer, L.L.

    2012-01-01

    South Africa has a rich, but scantily surveyed, desert flora. Documenting annual and geophytic species in this biome is challenging, as they usually only flower after adequate precipitation, which is characteristically erratic and infrequent. Recent floristic surveys in the Ai-Ais / Richtersveld

  8. Use of AI-1024 and AI-4096 analyzers in multiple regimes

    International Nuclear Information System (INIS)

    Zaika, N.D.; Kovtunenko, I.S.; Savchuk, O.G.

    1975-01-01

    The operation of pulse multichannel analyzers in the following multidimensional modes: AI-1024-4 - amplitude mode from several transducers; amplitude mode from several transducers at different time intervals; AI-4096-3M - amplitude mode at different time intervals in each of four groups with unit BVI-1

  9. Artificial intelligence applications in the intensive care unit.

    Science.gov (United States)

    Hanson, C W; Marshall, B E

    2001-02-01

    To review the history and current applications of artificial intelligence in the intensive care unit. The MEDLINE database, bibliographies of selected articles, and current texts on the subject. The studies that were selected for review used artificial intelligence tools for a variety of intensive care applications, including direct patient care and retrospective database analysis. All literature relevant to the topic was reviewed. Although some of the earliest artificial intelligence (AI) applications were medically oriented, AI has not been widely accepted in medicine. Despite this, patient demographic, clinical, and billing data are increasingly available in an electronic format and therefore susceptible to analysis by intelligent software. Individual AI tools are specifically suited to different tasks, such as waveform analysis or device control. The intensive care environment is particularly suited to the implementation of AI tools because of the wealth of available data and the inherent opportunities for increased efficiency in inpatient care. A variety of new AI tools have become available in recent years that can function as intelligent assistants to clinicians, constantly monitoring electronic data streams for important trends, or adjusting the settings of bedside devices. The integration of these tools into the intensive care unit can be expected to reduce costs and improve patient outcomes.

  10. On the Nature of Intelligence

    Science.gov (United States)

    Churchland, Paul M.

    Alan Turing is the consensus patron saint of the classical research program in Artificial Intelligence (AI), and his behavioral test for the possession of conscious intelligence has become his principal legacy in the mind of the academic public. Both takes are mistakes. That test is a dialectical throwaway line even for Turing himself, a tertiary gesture aimed at softening the intellectual resistance to a research program which, in his hands, possessed real substance, both mathematical and theoretical. The wrangling over his celebrated test has deflected attention away from those more substantial achievements, and away from the enduring obligation to construct a substantive theory of what conscious intelligence really is, as opposed to an epistemological account of how to tell when you are confronting an instance of it. This essay explores Turing's substantive research program on the nature of intelligence, and argues that the classical AI program is not its best expression, nor even the expression intended by Turing. It then attempts to put the famous Test into its proper, and much reduced, perspective.

  11. Artificial Intelligence and Moral intelligence

    OpenAIRE

    Laura Pana

    2008-01-01

    We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

  12. Strategic Team AI Path Plans: Probabilistic Pathfinding

    Directory of Open Access Journals (Sweden)

    Tng C. H. John

    2008-01-01

    Full Text Available This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002, in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006. We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.

  13. Event detection for car park entries by video-surveillance

    Science.gov (United States)

    Coquin, Didier; Tailland, Johan; Cintract, Michel

    2007-10-01

    Intelligent surveillance has become an important research issue due to the high cost and low efficiency of human supervisors, and machine intelligence is required to provide a solution for automated event detection. In this paper we describe a real-time system that has been used for detecting car park entries, using an adaptive background learning algorithm and two indicators representing activity and identity to overcome the difficulty of tracking objects.

  14. Artificial intelligence for Space Station automation: Crew safety, productivity, autonomy, augmented capability

    Science.gov (United States)

    Firschein, O.; Georgeff, M. P.; Park, W.; Cheeseman, P. C.; Geldberg, J.

    1986-01-01

    Artificial intelligence (AI) R&D projects for the successful and efficient operation of the Space Station are described. The book explores the most advanced AI-based technologies, reviews the results of concept design studies to determine required AI capabilities, details demonstrations that would indicate the existence of these capabilities, and develops an R&D plan leading to such demonstrations. Particular attention is given to teleoperation and robotics, sensors, expert systems, computers, planning, and man-machine interface.

  15. Integration of AI-2 Based Cell-Cell Signaling with Metabolic Cues in Escherichia coli.

    Directory of Open Access Journals (Sweden)

    Arindam Mitra

    Full Text Available The quorum sensing molecule Autoinducer-2 (AI-2 is generated as a byproduct of activated methyl cycle by the action of LuxS in Escherichia coli. AI-2 is synthesized, released and later internalized in a cell-density dependent manner. Here, by mutational analysis of the genes, uvrY and csrA, we describe a regulatory circuit of accumulation and uptake of AI-2. We constructed a single-copy chromosomal luxS-lacZ fusion in a luxS + merodiploid strain and evaluated its relative expression in uvrY and csrA mutants. At the entry of stationary phase, the expression of the fusion and AI-2 accumulation was positively regulated by uvrY and negatively regulated by csrA respectively. A deletion of csrA altered message stability of the luxS transcript and CsrA protein exhibited weak binding to 5' luxS regulatory region. DNA protein interaction and chromatin immunoprecipitation analysis confirmed direct interaction of UvrY with the luxS promoter. Additionally, reduced expression of the fusion in hfq deletion mutant suggested involvement of small RNA interactions in luxS regulation. In contrast, the expression of lsrA operon involved in AI-2 uptake, is negatively regulated by uvrY and positively by csrA in a cell-density dependent manner. The dual role of csrA in AI-2 synthesis and uptake suggested a regulatory crosstalk of cell signaling with carbon regulation in Escherichia coli. We found that the cAMP-CRP mediated catabolite repression of luxS expression was uvrY dependent. This study suggests that luxS expression is complex and regulated at the level of transcription and translation. The multifactorial regulation supports the notion that cell-cell communication requires interaction and integration of multiple metabolic signals.

  16. Artificial Intelligence Is for Real: Undergraduate Students Should Know about It.

    Science.gov (United States)

    Liebowitz, Jay

    1988-01-01

    Discussion of the possibilities of introducing artificial intelligence (AI) into the undergraduate curriculum highlights the introduction of AI in an introduction to information processing course for business students at George Washington University. Topics discussed include robotics, expert systems prototyping in class, and the interdisciplinary…

  17. Exploiting Artificial Intelligence To Enhance Training: A Short- and Medium-Term Perspective.

    Science.gov (United States)

    Cumming, Geoff

    This paper is an introductory discussion of industrial training, artificial intelligence (AI), and AI applications in training, prepared in the context of the United Kingdom Training Commission (TC) program. Following an outline of the activities and aims of the program, individual sections describe perspectives on: (1) training needs, including…

  18. Applications of artificial intelligence systems in the analysis of epidemiological data.

    Science.gov (United States)

    Flouris, Andreas D; Duffy, Jack

    2006-01-01

    A brief review of the germane literature suggests that the use of artificial intelligence (AI) statistical algorithms in epidemiology has been limited. We discuss the advantages and disadvantages of using AI systems in large-scale sets of epidemiological data to extract inherent, formerly unidentified, and potentially valuable patterns that human-driven deductive models may miss.

  19. Survey of Artificial Intelligence and Expert Systems in Library and Information Science Literature.

    Science.gov (United States)

    Hsieh, Cynthia C.; Hall, Wendy

    1989-01-01

    Examines the definition and history of artificial intelligence (AI) and investigates the body of literature on AI found in "Library Literature" and "Library and Information Science Abstracts." The results reported include the number of articles by year and per journal, and the percentage of articles dealing with library…

  20. Artificial Intelligence, Expert Systems, Natural Language Interfaces, Knowledge Engineering and the Librarian.

    Science.gov (United States)

    Davies, Jim

    This paper begins by examining concepts of artificial intelligence (AI) and discusses various definitions of the concept that have been suggested in the literature. The nesting relationship of expert systems within the broader framework of AI is described, and expert systems are characterized as knowledge-based systems (KBS) which attempt to solve…

  1. Artificial Intelligence Needs More Emphasis on Basic Research: President's Quarterly Message

    OpenAIRE

    McCarthy, John

    1983-01-01

    Too few people are doing basic research in AI relative to the number working on applications. The ratio of basic/applied is less in AI than in the older sciences and than in computer science generally. This is unfortunate, because reaching human level artificial intelligence will require fundamental conceptual advances.

  2. Artificial Intelligence and Expert Systems Research and Their Possible Impact on Information Science.

    Science.gov (United States)

    Borko, Harold

    1985-01-01

    Defines artificial intelligence (AI) and expert systems; describes library applications utilizing AI to automate creation of document representations, request formulations, and design and modify search strategies for information retrieval systems; discusses expert system development for information services; and reviews impact of these…

  3. Life 3.0: being human in the age of artificial intelligence

    National Research Council Canada - National Science Library

    Tegmark, Max

    2017-01-01

    ...? How likely is the emergence of suprahuman intelligence? A.I. is the future of science, technology, and business--and there is no person better qualified or situated to explore that future than Max Tegmark. What has A.I. brought us...

  4. Artificial intelligence as a reflection of reality in the twenty-first century

    Directory of Open Access Journals (Sweden)

    Gusev S. S.

    2016-03-01

    Full Text Available the article discusses artificial intelligence (AI at the present stage of development, as a way of presenting and understanding AI as the mechanisms of computers. Features a large bunch of some algorithmic procedures for the solution by computer of a specific task, an example of which can serve as an attempt of modeling of biological neural networks.

  5. Artificial Intelligence Application in Power Generation Industry: Initial considerations

    Science.gov (United States)

    Ismail, Rahmat Izaizi B.; Ismail Alnaimi, Firas B.; AL-Qrimli, Haidar F.

    2016-03-01

    With increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. One of the most powerful tools in faults detection and diagnosis is artificial intelligence (AI). Faults should be detected early so correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary interruption and downtime. For the last few decades there has been major interest towards intelligent condition monitoring system (ICMS) application in power plant especially with AI development particularly in artificial neural network (ANN). ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. In this paper, the studies of ANN and genetic algorithm (GA) application will be presented.

  6. Imagining the thinking machine: technological myths and the rise of Artificial Intelligence

    OpenAIRE

    Natale, Simone; Ballatore, Andrea

    2017-01-01

    This article discusses the role of technological myths in the development of Artificial Intelligence (AI) technologies from 1950s to the early 1970s. It shows how the rise of AI was accompanied by the construction of a powerful cultural myth: the creation of a thinking machine, which would be able to perfectly simulate the cognitive faculties of the human mind. Based on a content analysis of articles on Artificial Intelligence published in two magazines, the Scientific American and the New Sc...

  7. AI in Computer-Based Training

    Science.gov (United States)

    Camstra, Bert

    2008-01-01

    In this paper, intelligent approaches to CBT are put into several perspectives in an attempt to elucidate the concepts and give them a more realistic (and not only glamorous) footing. The role of expert systems in training is explored and possible routes towards intelligent CBT are outlined. [This paper was first published in "Interactive Learning…

  8. New trends in computational collective intelligence

    CERN Document Server

    Kim, Sang-Wook; Trawiński, Bogdan

    2015-01-01

    This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods an...

  9. GPU: the biggest key processor for AI and parallel processing

    Science.gov (United States)

    Baji, Toru

    2017-07-01

    Two types of processors exist in the market. One is the conventional CPU and the other is Graphic Processor Unit (GPU). Typical CPU is composed of 1 to 8 cores while GPU has thousands of cores. CPU is good for sequential processing, while GPU is good to accelerate software with heavy parallel executions. GPU was initially dedicated for 3D graphics. However from 2006, when GPU started to apply general-purpose cores, it was noticed that this architecture can be used as a general purpose massive-parallel processor. NVIDIA developed a software framework Compute Unified Device Architecture (CUDA) that make it possible to easily program the GPU for these application. With CUDA, GPU started to be used in workstations and supercomputers widely. Recently two key technologies are highlighted in the industry. The Artificial Intelligence (AI) and Autonomous Driving Cars. AI requires a massive parallel operation to train many-layers of neural networks. With CPU alone, it was impossible to finish the training in a practical time. The latest multi-GPU system with P100 makes it possible to finish the training in a few hours. For the autonomous driving cars, TOPS class of performance is required to implement perception, localization, path planning processing and again SoC with integrated GPU will play a key role there. In this paper, the evolution of the GPU which is one of the biggest commercial devices requiring state-of-the-art fabrication technology will be introduced. Also overview of the GPU demanding key application like the ones described above will be introduced.

  10. SNAP and AI Fuel Summary Report

    International Nuclear Information System (INIS)

    Lords, R.E.

    1994-08-01

    The SNAP and AI Fuel Summary Report provides a detailed overview of treatment and storage of these fuels from fabrication through current storage including design parameters and reactor history. Chemical and physical characteristics are described, and potential indicators of as-stored fuel conditions are emphasized

  11. Automating Commercial Video Game Development using Computational Intelligence

    OpenAIRE

    Tse G. Tan; Jason Teo; Patricia Anthony

    2011-01-01

    Problem statement: The retail sales of computer and video games have grown enormously during the last few years, not just in United States (US), but also all over the world. This is the reason a lot of game developers and academic researchers have focused on game related technologies, such as graphics, audio, physics and Artificial Intelligence (AI) with the goal of creating newer and more fun games. In recent years, there has been an increasing interest in game AI for pro...

  12. Energy Demand Forecasting: Combining Cointegration Analysis and Artificial Intelligence Algorithm

    OpenAIRE

    Huang, Junbing; Tang, Yuee; Chen, Shuxing

    2018-01-01

    Energy is vital for the sustainable development of China. Accurate forecasts of annual energy demand are essential to schedule energy supply and provide valuable suggestions for developing related industries. In the existing literature on energy use prediction, the artificial intelligence-based (AI-based) model has received considerable attention. However, few econometric and statistical evidences exist that can prove the reliability of the current AI-based model, an area that still needs to ...

  13. Artificial Intelligence at Advanced Information and Decision Systems

    OpenAIRE

    McCune, Brian P.

    1981-01-01

    Advanced Information and Decision Systems (AI-DS) is a relatively new, employee-owned company that does basic and applied research, product development, and consulting in the fields of artificial intelligence, computer science, decision analysis, operations research, control theory, estimation theory, and signal processing. AI&DS performs studies, analyses, systems design and evaluation, and software development for a variety of industrial clients and government agencies, including the Depart...

  14. Artificial intelligence and foreign policy decision-making

    OpenAIRE

    Berkoff, Russ H.

    1997-01-01

    Approved for public release; distribution is unlimited With the advent of a global information society, the US will seek to tap the potential of advanced computing capability to enhance its ability to conduct foreign policy decision making. This thesis explores the potential for improving individual and organizational decision making capabilities by means of artificial intelligence (AI). The use of AI will allow us to take advantage of the plethora of information available to obtain an edg...

  15. Artificial Intelligence Techniques Applications for Power Disturbances Classification

    OpenAIRE

    K.Manimala; Dr.K.Selvi; R.Ahila

    2008-01-01

    Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge...

  16. The coming of age of artificial intelligence in medicine.

    Science.gov (United States)

    Patel, Vimla L; Shortliffe, Edward H; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-05-01

    This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its "adolescence" (Shortliffe EH. The adolescence of AI in medicine: will the field come of age in the '90s? Artificial Intelligence in Medicine 1993;5:93-106). In this article, the discussants reflect on medical AI research during the subsequent years and characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision-making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems.

  17. Artificial intelligence - New tools for aerospace project managers

    Science.gov (United States)

    Moja, D. C.

    1985-01-01

    Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

  18. A PHILOSOPHICAL APPROACH TO ARTIFICIAL INTELLIGENCE AND ISLAMIC VALUES

    Directory of Open Access Journals (Sweden)

    Ali Akbar Ziaee

    2012-02-01

    Full Text Available Artificial Intelligence has the potential to empower humans through enhanced learning and performance. But if this potential is to be realized and accepted, the ethical aspects as well as the technical must be addressed. Many engineers claim that AI will be smarter than human brains, including scientific creativity, general wisdom and social skills, so we must consider it an important factor for making decisions in our social life and especially in our Islamic societies. The most important challenges will be the quality of representing the Islamic values like piety, obedience, Halal and Haram, and etc in the form of semantics. In this paper, I want to emphasize on the role of Divine Islamic values in the application of AI and discuss it according to philosophy of AI and Islamic perspective.Keywords- Value, expert, Community Development, Artificial Intelligence, Superintelligence, Friendly Artificial Intelligence

  19. The Coming of Age of Artificial Intelligence in Medicine*

    Science.gov (United States)

    Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-01-01

    Summary This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its “adolescence” (Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ‘90s? Artificial Intelligence in Medicine 1993; 5:93–106). In this article, the discussants reflect on medical AI research during the subsequent years and attempt to characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems. PMID:18790621

  20. Artificial Intelligence.

    Science.gov (United States)

    Information Technology Quarterly, 1985

    1985-01-01

    This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

  1. Competitive Intelligence.

    Science.gov (United States)

    Bergeron, Pierrette; Hiller, Christine A.

    2002-01-01

    Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

  2. Implementing embedded artificial intelligence rules within algorithmic programming languages

    Science.gov (United States)

    Feyock, Stefan

    1988-01-01

    Most integrations of artificial intelligence (AI) capabilities with non-AI (usually FORTRAN-based) application programs require the latter to execute separately to run as a subprogram or, at best, as a coroutine, of the AI system. In many cases, this organization is unacceptable; instead, the requirement is for an AI facility that runs in embedded mode; i.e., is called as subprogram by the application program. The design and implementation of a Prolog-based AI capability that can be invoked in embedded mode are described. The significance of this system is twofold: Provision of Prolog-based symbol-manipulation and deduction facilities makes a powerful symbolic reasoning mechanism available to applications programs written in non-AI languages. The power of the deductive and non-procedural descriptive capabilities of Prolog, which allow the user to describe the problem to be solved, rather than the solution, is to a large extent vitiated by the absence of the standard control structures provided by other languages. Embedding invocations of Prolog rule bases in programs written in non-AI languages makes it possible to put Prolog calls inside DO loops and similar control constructs. The resulting merger of non-AI and AI languages thus results in a symbiotic system in which the advantages of both programming systems are retained, and their deficiencies largely remedied.

  3. Double entry bookkeeping vs single entry bookkeeping

    Directory of Open Access Journals (Sweden)

    Ileana Andreica

    2016-11-01

    Full Text Available Abstract: A financial management eficiently begin, primarily, with an accounting record kept in the best possible conditions, this being conditioned on the adoption of a uniform forms, rational, clear and simple accounting. Throughout history, there have been known two forms of accounting: the simple and double entry. Romanian society after 1990 underwent a substantial change in social structure, the sector on which put a great emphasis being private, that of small manufacturers, peddler, freelance, who work independently and authorized or as associative form (family enterprises, various associations (owners, tenants, etc., liberal professions, etc.. They are obliged to keep a simple bookkeeping, because they have no juridical personality. Companies with legal personality are required to keep double entry bookkeeping; therefore, knowledge and border demarcation between the two forms of organisation of accounting is an essential. The material used for this work is mainly represented by the financial and accounting documents, by the analysis of the economic, by legislative updated sources, and as the method was used the comparison method, using hypothetical data, in case of an authorized individual and a legal entity. Based on the chosen material, an authorized individual (who perform single entry accounting system and a juridical entity (who perform double entry accounting system were selected comparative case studies, using hypothetical data, were analysed advantages and disadvantages in term of fiscal, if using two accounting systems, then were highlighted some conclusion that result.

  4. Approaches to the study of intelligence

    Science.gov (United States)

    Norman, Donald A.

    1991-01-01

    A survey and an evaluation are conducted for the Rosenbloom et al. (1991) 'SOAR' model of intelligence, both as found in humans and in prospective AI systems, which views it as a representational system for goal-oriented symbolic activity based on a physical symbol system. Attention is given to SOAR's implications for semantic and episodic memory, symbol processing, and search within a uniform problem space; also noted are the relationships of SOAR to competing AI schemes, and its potential usefulness as a theoretical tool for cognitive psychology.

  5. The Third Age of Artificial Intelligence

    OpenAIRE

    Miailhe, Nicolas; Hodes, Cyrus

    2018-01-01

    If the definitional boundaries of Artificial Intelligence (AI) remains contested, experts agree that we are witnessing a revolution. “Is this time different?” is the question that they worryingly argue over when they analyze the socio-economic impact of the AI revolution as compared with the other industrial revolutions of the 19th and 20th centuries. This Schumpeterian wave may prove to be a creative destruction raising incomes, enhancing quality of life for all and generating previously uni...

  6. Artificial intelligence techniques in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Laughton, M.A.

    1997-12-31

    Since the early to mid 1980s much of the effort in power systems analysis has turned away from the methodology of formal mathematical modelling which came from the fields of operations research, control theory and numerical analysis to the less rigorous techniques of artificial intelligence (AI). Today the main AI techniques found in power systems applications are those utilising the logic and knowledge representations of expert systems, fuzzy systems, artificial neural networks (ANN) and, more recently, evolutionary computing. These techniques will be outlined in this chapter and the power system applications indicated. (Author)

  7. Applications of artificial intelligence to reactor and plant control

    International Nuclear Information System (INIS)

    Bernard, J.A.

    1989-01-01

    Potential improvements in plant efficiency and reliability are often cited as reasons for developing and applying artificial intelligence (AI) techniques, principally expert systems, to the control and operation of nuclear reactors. Nevertheless, there have been few such applications and then mostly at the prototype level. Therefore, if AI techniques are to contribute to process control, methods must be identified by which rule-based and analytic approaches can be merged. This hypothesis is the basic premise of this article. Presented below are 1. a brief review of the human approach towards process control, 2. a discussion of the suitability of AI methodologies for the performance of control tasks, 3. examples of AI applications to both open- and closed-loop control, 4. an enumeration of unresolved issues associated with the use of AI for control, and 5. a discussion of the possible role of expert system techniques in process control. (orig./GL)

  8. Artificial intelligence in medicine: humans need not apply?

    Science.gov (United States)

    Diprose, William; Buist, Nicholas

    2016-05-06

    Artificial intelligence (AI) is a rapidly growing field with a wide range of applications. Driven by economic constraints and the potential to reduce human error, we believe that over the coming years AI will perform a significant amount of the diagnostic and treatment decision-making traditionally performed by the doctor. Humans would continue to be an important part of healthcare delivery, but in many situations, less expensive fit-for-purpose healthcare workers could be trained to 'fill the gaps' where AI are less capable. As a result, the role of the doctor as an expensive problem-solver would become redundant.

  9. Multisensor system and artificial intelligence in housing for the elderly.

    Science.gov (United States)

    Chan, M; Bocquet, H; Campo, E; Val, T; Estève, D; Pous, J

    1998-01-01

    To improve the safety of a growing proportion of elderly and disabled people in the developed countries, a multisensor system based on Artificial Intelligence (AI), Advanced Telecommunications (AT) and Information Technology (IT) has been devised and fabricated. Thus, the habits and behaviours of these populations will be recorded without disturbing their daily activities. AI will diagnose any abnormal behavior or change and the system will warn the professionals. Gerontology issues are presented together with the multisensor system, the AI-based learning and diagnosis methodology and the main functionalities.

  10. Natural language processing in psychiatry. Artificial intelligence technology and psychopathology.

    Science.gov (United States)

    Garfield, D A; Rapp, C; Evens, M

    1992-04-01

    The potential benefit of artificial intelligence (AI) technology as a tool of psychiatry has not been well defined. In this essay, the technology of natural language processing and its position with regard to the two main schools of AI is clearly outlined. Past experiments utilizing AI techniques in understanding psychopathology are reviewed. Natural language processing can automate the analysis of transcripts and can be used in modeling theories of language comprehension. In these ways, it can serve as a tool in testing psychological theories of psychopathology and can be used as an effective tool in empirical research on verbal behavior in psychopathology.

  11. Towards a nuclear industry boosted by artificial intelligence?

    International Nuclear Information System (INIS)

    Le Ngoc, B.

    2017-01-01

    Artificial intelligence (AI) is deemed as the fourth industrial revolution after the steam engine, electric power and the computer. Auto manufacturers invest a lot in AI to develop autonomous vehicles. Nuclear industry that has to deal with a huge amount of data due to the complexity of its installations may benefit from AI in terms of quick handling of complex situations, of reducing the rate of errors, of drawing adequate conclusions through the right crossing of data and of improving decision making. (A.C.)

  12. S&T converging trends in dealing with disaster: A review on AI tools

    International Nuclear Information System (INIS)

    Hasan, Abu Bakar; Isa, Mohd Hafez Mohd.

    2016-01-01

    Science and Technology (S&T) has been able to help mankind to solve or minimize problems when arise. Different methodologies, techniques and tools were developed or used for specific cases by researchers, engineers, scientists throughout the world, and numerous papers and articles have been written by them. Nine selected cases such as flash flood, earthquakes, workplace accident, fault in aircraft industry, seismic vulnerability, disaster mitigation and management, and early fault detection in nuclear industry have been studied. This paper looked at those cases, and their results showed nearly 60% uses artificial intelligence (AI) as a tool. This paper also did some review that will help young researchers in deciding the types of AI tools to be selected; thus proving the future trends in S&T

  13. S&T converging trends in dealing with disaster: A review on AI tools

    Science.gov (United States)

    Hasan, Abu Bakar; Isa, Mohd. Hafez Mohd.

    2016-01-01

    Science and Technology (S&T) has been able to help mankind to solve or minimize problems when arise. Different methodologies, techniques and tools were developed or used for specific cases by researchers, engineers, scientists throughout the world, and numerous papers and articles have been written by them. Nine selected cases such as flash flood, earthquakes, workplace accident, fault in aircraft industry, seismic vulnerability, disaster mitigation and management, and early fault detection in nuclear industry have been studied. This paper looked at those cases, and their results showed nearly 60% uses artificial intelligence (AI) as a tool. This paper also did some review that will help young researchers in deciding the types of AI tools to be selected; thus proving the future trends in S&T.

  14. S&T converging trends in dealing with disaster: A review on AI tools

    Energy Technology Data Exchange (ETDEWEB)

    Hasan, Abu Bakar, E-mail: abakarh@usim.edu.my; Isa, Mohd Hafez Mohd. [Faculty of Science and Technology, Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan (Malaysia)

    2016-01-22

    Science and Technology (S&T) has been able to help mankind to solve or minimize problems when arise. Different methodologies, techniques and tools were developed or used for specific cases by researchers, engineers, scientists throughout the world, and numerous papers and articles have been written by them. Nine selected cases such as flash flood, earthquakes, workplace accident, fault in aircraft industry, seismic vulnerability, disaster mitigation and management, and early fault detection in nuclear industry have been studied. This paper looked at those cases, and their results showed nearly 60% uses artificial intelligence (AI) as a tool. This paper also did some review that will help young researchers in deciding the types of AI tools to be selected; thus proving the future trends in S&T.

  15. New progress of FEM simulation and AI application in rolling at RAL

    International Nuclear Information System (INIS)

    Liu Xianghua; Wang Guodong; Zhao Kun

    2000-01-01

    New progresses on FEM simulation and AI application in rolling have been achieved at RAL recently. The existence and uniqueness of the extreme point of total functional for rolling problem has been proved. Different rolling processes, such as H-beam rolling, ribbing strip rolling, slab sizing, have been solved by our in-house FEM software package. The simulation results have been put into production use to improve the precision of math models. The Artificial Neural Network has been used to predict rolling force, coiling temperature, microstructure and properties of the rolled products. An expert system for deviation diagnoses of strip thickness has been developed for industry use. Synergetic Artificial Intelligence has also been applied to rolling scheduling. We are making continuous efforts to develop AI applications for rolling line co-operating in China steel industry. (author)

  16. CHALLENGES OF THE NOT-SO-FAR FUTURE: EU ROBOTICS AND AI LAW IN BUSINESS

    Directory of Open Access Journals (Sweden)

    Roxana Mihaela CATEA

    2018-05-01

    Full Text Available The paper focuses on the emerging European legislation in the area of artificial intelligence and robotics, based on the currently fast developing technical procedures for the manufacture of products characterized by autonomy. The importance of having a clear and stable legislation for the production and spread of technical devices has been under discussion for some time now and member states have reached preliminary conclusions regarding the definition and criteria by which one can identify artificial intelligence. Also, continuous innovation lead to the necessity of integrating these AI products in common household economy and therefore, the need for a proper legal framework addressing both liability and limits for creating and operating machines for civil use arose. This article shall review the measures already taken by the European Parliament and the European Commission for the establishment of a standardized legal framework related to robotic and artificial intelligence products. The objectives of this study are to analyze the general guidelines available as created by the EU legislator which shall ultimately be transposed in national legislation, in order to supersede the current lack of regulations for companies developing and selling AI products nation-wide.

  17. Three IQs of AI Systems and their Testing Methods

    OpenAIRE

    Liu, Feng; Shi, Yong; Liu, Ying

    2017-01-01

    The rapid development of artificial intelligence has brought the artificial intelligence threat theory as well as the problem about how to evaluate the intelligence level of intelligent products. Both need to find a quantitative method to evaluate the intelligence level of intelligence systems, including human intelligence. Based on the standard intelligence system and the extended Von Neumann architecture, this paper proposes General IQ, Service IQ and Value IQ evaluation methods for intelli...

  18. The BSM-AI project: SUSY-AI-generalizing LHC limits on supersymmetry with machine learning

    Energy Technology Data Exchange (ETDEWEB)

    Caron, Sascha [Radboud Universiteit, Institute for Mathematics, Astro- and Particle Physics IMAPP, Nijmegen (Netherlands); Nikhef, Amsterdam (Netherlands); Kim, Jong Soo [UAM/CSIC, Instituto de Fisica Teorica, Madrid (Spain); Rolbiecki, Krzysztof [UAM/CSIC, Instituto de Fisica Teorica, Madrid (Spain); University of Warsaw, Faculty of Physics, Warsaw (Poland); Ruiz de Austri, Roberto [IFIC-UV/CSIC, Instituto de Fisica Corpuscular, Valencia (Spain); Stienen, Bob [Radboud Universiteit, Institute for Mathematics, Astro- and Particle Physics IMAPP, Nijmegen (Netherlands)

    2017-04-15

    A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300, 000 pMSSM model sets - each tested against 200 signal regions by ATLAS - have been used to train and validate SUSY-AI. The code is currently able to reproduce the ATLAS exclusion regions in 19 dimensions with an accuracy of at least 93%. It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/. An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/. (orig.)

  19. The BSM-AI project: SUSY-AI-generalizing LHC limits on supersymmetry with machine learning

    International Nuclear Information System (INIS)

    Caron, Sascha; Kim, Jong Soo; Rolbiecki, Krzysztof; Ruiz de Austri, Roberto; Stienen, Bob

    2017-01-01

    A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300, 000 pMSSM model sets - each tested against 200 signal regions by ATLAS - have been used to train and validate SUSY-AI. The code is currently able to reproduce the ATLAS exclusion regions in 19 dimensions with an accuracy of at least 93%. It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/. An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/. (orig.)

  20. Intelligence Ethics:

    DEFF Research Database (Denmark)

    Rønn, Kira Vrist

    2016-01-01

    Questions concerning what constitutes a morally justified conduct of intelligence activities have received increased attention in recent decades. However, intelligence ethics is not yet homogeneous or embedded as a solid research field. The aim of this article is to sketch the state of the art...... of intelligence ethics and point out subjects for further scrutiny in future research. The review clusters the literature on intelligence ethics into two groups: respectively, contributions on external topics (i.e., the accountability of and the public trust in intelligence agencies) and internal topics (i.......e., the search for an ideal ethical framework for intelligence actions). The article concludes that there are many holes to fill for future studies on intelligence ethics both in external and internal discussions. Thus, the article is an invitation – especially, to moral philosophers and political theorists...

  1. Launch vehicle operations cost reduction through artificial intelligence techniques

    Science.gov (United States)

    Davis, Tom C., Jr.

    1988-01-01

    NASA's Kennedy Space Center has attempted to develop AI methods in order to reduce the cost of launch vehicle ground operations as well as to improve the reliability and safety of such operations. Attention is presently given to cost savings estimates for systems involving launch vehicle firing-room software and hardware real-time diagnostics, as well as the nature of configuration control and the real-time autonomous diagnostics of launch-processing systems by these means. Intelligent launch decisions and intelligent weather forecasting are additional applications of AI being considered.

  2. APPLYING ARTIFICIAL INTELLIGENCE TECHNIQUES TO HUMAN-COMPUTER INTERFACES

    DEFF Research Database (Denmark)

    Sonnenwald, Diane H.

    1988-01-01

    A description is given of UIMS (User Interface Management System), a system using a variety of artificial intelligence techniques to build knowledge-based user interfaces combining functionality and information from a variety of computer systems that maintain, test, and configure customer telephone...... and data networks. Three artificial intelligence (AI) techniques used in UIMS are discussed, namely, frame representation, object-oriented programming languages, and rule-based systems. The UIMS architecture is presented, and the structure of the UIMS is explained in terms of the AI techniques....

  3. Man-machine communication in reactor control using AI methods

    International Nuclear Information System (INIS)

    Klebau, J.; Lindner, A.; Fiedler, U.

    1987-01-01

    In the last years the interest in process control has expecially focused on problems of man-machine communication. It depends on its great importance to process performance and user acceptance. Advanced computerized operator aids, e.g. in nuclear power plants, are as well as their man-machine interface. In the Central Institute for Nuclear Research in Rossendorf a computerized operator support system for nuclear power plants is designed, which is involved in a decentralized process automation system. A similar but simpler system, the Hierarchical Informational System (HIS) at the Rossendorf Research Reactor, works with a computer controlled man-machine interface, based on menu. In the special case of the disturbance analysis program SAAP-2, which is included in the HIS, the limits of menu techniques are obviously. Therefore it seems to be necessary and with extended hard- and software possible to realize an user controlled natural language interface using Artificial Intelligence (AI) methods. The draft of such a system is described. It should be able to learn during a teaching phase all phrases and their meanings. The system will work on the basis of a self-organizing, associative data structure. It is used to recognize a great amount of words which are used in language analysis. Error recognition and, if possible, correction is done by means of a distance function in the word set. Language analysis should be carried out with a simplified word class controlled functional analysis. With this interface it is supposed to get experience in intelligent man-machine communication to enhance operational safety in future. (author)

  4. Two Fundamental Problems Connected with AI

    OpenAIRE

    Dobrev, Dimiter

    2008-01-01

    This paper is about two fundamental problems in the field of computer science. Solving these two problems is important because it has to do with the creation of Artificial Intelligence. In fact, these two problems are not very famous because they have not many applications outside the field of Artificial Intelligence. In this paper we will give a solution neither of the first nor of the second problem. Our goal will be to formulate these two problems and to give some ideas for...

  5. Artificial intelligence in nuclear engineering: developments, lesson learned and future directions

    Energy Technology Data Exchange (ETDEWEB)

    Ruan, Da [The Belgian Nuclear Research Centre (SCK.CEN), Mol (Belgium)]. E-mail: druan@sckcen.be

    2005-07-01

    Full text of publication follows: In this lecture, an overview on artificial intelligence (AI) from control to decision making in nuclear engineering will be given mainly based on the 10 years progress of the FLINS forum (Fuzzy Logic and Intelligent Technology in Nuclear Science). Some FLINS concrete examples on nuclear reactor operation, nuclear safeguards information management, and cost estimation under uncertainty for a large nuclear project will be illustrated for the potential use of AI in nuclear engineering. Recommendations and future research directions on AI in nuclear engineering will be suggested from a practical point of view. (author)

  6. Artificial intelligence in nuclear engineering: developments, lesson learned and future directions

    International Nuclear Information System (INIS)

    Ruan, Da

    2005-01-01

    Full text of publication follows: In this lecture, an overview on artificial intelligence (AI) from control to decision making in nuclear engineering will be given mainly based on the 10 years progress of the FLINS forum (Fuzzy Logic and Intelligent Technology in Nuclear Science). Some FLINS concrete examples on nuclear reactor operation, nuclear safeguards information management, and cost estimation under uncertainty for a large nuclear project will be illustrated for the potential use of AI in nuclear engineering. Recommendations and future research directions on AI in nuclear engineering will be suggested from a practical point of view. (author)

  7. Intelligence Naturelle et Intelligence Artificielle

    OpenAIRE

    Dubois, Daniel

    2011-01-01

    Cet article présente une approche systémique du concept d’intelligence naturelle en ayant pour objectif de créer une intelligence artificielle. Ainsi, l’intelligence naturelle, humaine et animale non-humaine, est une fonction composée de facultés permettant de connaître et de comprendre. De plus, l'intelligence naturelle reste indissociable de la structure, à savoir les organes du cerveau et du corps. La tentation est grande de doter les systèmes informatiques d’une intelligence artificielle ...

  8. Deploying Embodied AI into Virtual Worlds

    Science.gov (United States)

    Burden, David J. H.

    The last two years have seen the start of commercial activity within virtual worlds. Unlike computer games where Non-Player-Character avatars are common, in most virtual worlds they are the exception — and until recently in Second Life they were non-existent. However there is real commercial scope for Als in these worlds — in roles from virtual sales staff and tutors to personal assistants. Deploying an embodied AI into a virtual world offers a unique opportunity to evaluate embodied Als, and to develop them within an environment where human and computer are on almost equal terms. This paper presents an architecture being used for the deployment of chatbot driven avatars within the Second Life virtual world, looks at the challenges of deploying an AI within such a virtual world, the possible implications for the Turing Test, and identifies research directions for the future.

  9. AI in medical education--another grand challenge for medical informatics.

    Science.gov (United States)

    Lillehaug, S I; Lajoie, S P

    1998-03-01

    The potential benefits of artificial intelligence in medicine (AIM) were never realized as anticipated. This paper addresses ways in which such potential can be achieved. Recent discussions of this topic have proposed a stronger integration between AIM applications and health information systems, and emphasize computer guidelines to support the new health care paradigms of evidence-based medicine and cost-effectiveness. These proposals, however, promote the initial definition of AIM applications as being AI systems that can perform or aid in diagnoses. We challenge this traditional philosophy of AIM and propose a new approach aiming at empowering health care workers to become independent self-sufficient problem solvers and decision makers. Our philosophy is based on findings from a review of empirical research that examines the relationship between the health care personnel's level of knowledge and skills, their job satisfaction, and the quality of the health care they provide. This review supports addressing the quality of health care by empowering health care workers to reach their full potential. As an aid in this empowerment process we argue for reviving a long forgotten AIM research area, namely, AI based applications for medical education and training. There is a growing body of research in artificial intelligence in education that demonstrates that the use of artificial intelligence can enhance learning in numerous domains. By examining the strengths of these educational applications and the results from previous AIM research we derive a framework for empowering medical personnel and consequently raising the quality of health care through the use of advanced AI based technology.

  10. Double entry bookkeeping vs single entry bookkeeping

    OpenAIRE

    Ileana Andreica

    2016-01-01

    Abstract: A financial management eficiently begin, primarily, with an accounting record kept in the best possible conditions, this being conditioned on the adoption of a uniform forms, rational, clear and simple accounting. Throughout history, there have been known two forms of accounting: the simple and double entry. Romanian society after 1990 underwent a substantial change in social structure, the sector on which put a great emphasis being private, that of small manufacturers, ped...

  11. Why Don't Accounting Students like AIS?

    Science.gov (United States)

    Vatanasakdakul, Savanid; Aoun, Chadi

    2011-01-01

    Purpose: The demand for Accounting Information Systems (AIS) knowledge has increased exponentially over the past two decades, but studying AIS has not proved easy for many accounting students. The aim of the study is to understand the challenges accounting students face in studying AIS through investigation of the factors which may be contributing…

  12. Dicty_cDB: FC-AI04 [Dicty_cDB

    Lifescience Database Archive (English)

    Full Text Available FC (Link to library) FC-AI04 (Link to dictyBase) - - - Contig-U15121-1 FC-AI04E (Li...nk to Original site) - - - - - - FC-AI04E 772 Show FC-AI04 Library FC (Link to library) Clone ID FC-AI04 (Li.../dictycdb.biol.tsukuba.ac.jp/CSM/FC/FC-AI/FC-AI04Q.Seq.d/ Representative seq. ID FC-AI...04E (Link to Original site) Representative DNA sequence >FC-AI04 (FC-AI04Q) /CSM/FC/FC-AI/FC-AI04Q.Seq....qvnkhqqvvtktvsd vlvphqvhnqvfphipqqmtlvnkhqpvvtktvsdvlvphqvhnqvfphtpqlkiqvylq vfqvvvvtiisai

  13. Dicty_cDB: FC-AI10 [Dicty_cDB

    Lifescience Database Archive (English)

    Full Text Available FC (Link to library) FC-AI10 (Link to dictyBase) - - - Contig-U16270-1 FC-AI10F (Li...nk to Original site) FC-AI10F 405 - - - - - - Show FC-AI10 Library FC (Link to library) Clone ID FC-AI10 (Li.../dictycdb.biol.tsukuba.ac.jp/CSM/FC/FC-AI/FC-AI10Q.Seq.d/ Representative seq. ID FC-AI...10F (Link to Original site) Representative DNA sequence >FC-AI10 (FC-AI10Q) /CSM/FC/FC-AI/FC-AI10Q.Seq.... sequence RKKRKSDYTSFSTYIHKLLKQITPPTNAKSNEKGDRKFTISSKAMSVMNSFVHDIFDRIA TEASGLAKKKKRQTLHSRDIQVAVRIILTGELAXHAI

  14. Dicty_cDB: FC-AI23 [Dicty_cDB

    Lifescience Database Archive (English)

    Full Text Available FC (Link to library) FC-AI23 (Link to dictyBase) - - - Contig-U15308-1 FC-AI23Z (Li...nk to Original site) - - FC-AI23Z 603 - - - - Show FC-AI23 Library FC (Link to library) Clone ID FC-AI23 (Li.../dictycdb.biol.tsukuba.ac.jp/CSM/FC/FC-AI/FC-AI23Q.Seq.d/ Representative seq. ID FC-AI...23Z (Link to Original site) Representative DNA sequence >FC-AI23 (FC-AI23Q) /CSM/FC/FC-AI/FC-AI23Q.Seq....LNTLAKKNEQVVEGEILAKQLTGVTAEELSEFKACFSHFDKDN DNKLNRLEFSSCLKSIGDELTEEQLNQVISKIDTDGNGTISFEEFIDYMVSSRKGTDSVE STKAAFKVMAEDKDFITEAQIRAAI

  15. Dicty_cDB: FC-AI05 [Dicty_cDB

    Lifescience Database Archive (English)

    Full Text Available FC (Link to library) FC-AI05 (Link to dictyBase) - - - Contig-U15516-1 FC-AI05E (Li...nk to Original site) - - - - - - FC-AI05E 1189 Show FC-AI05 Library FC (Link to library) Clone ID FC-AI05 (L...//dictycdb.biol.tsukuba.ac.jp/CSM/FC/FC-AI/FC-AI05Q.Seq.d/ Representative seq. ID FC-AI...05E (Link to Original site) Representative DNA sequence >FC-AI05 (FC-AI05Q) /CSM/FC/FC-AI/FC-AI05Q.Seq...KIVGEASLKNKGKMSRVLAAKAALSARFD ALCEVSDTSYGIAYKGAVDRRAAAIEGREVRKSLNAVKPEKSGNVAKYDHTKSATTNTTR DVATKSSKESSIKQEKQ

  16. Dicty_cDB: FC-AI21 [Dicty_cDB

    Lifescience Database Archive (English)

    Full Text Available FC (Link to library) FC-AI21 (Link to dictyBase) - - - Contig-U16254-1 FC-AI21Z (Li...nk to Original site) - - FC-AI21Z 696 - - - - Show FC-AI21 Library FC (Link to library) Clone ID FC-AI21 (Li.../dictycdb.biol.tsukuba.ac.jp/CSM/FC/FC-AI/FC-AI21Q.Seq.d/ Representative seq. ID FC-AI...21Z (Link to Original site) Representative DNA sequence >FC-AI21 (FC-AI21Q) /CSM/FC/FC-AI/FC-AI21Q.Seq....YPGYMYTDLSTIYERAGRIQGRNGSITQI PILTMPNDDITHPIPDLTGYITEGQIFIDRQINNRQIYPPINVLPSLSRLMKSAI

  17. AI and simulation: What can they learn from each other

    Science.gov (United States)

    Colombano, Silvano P.

    1988-01-01

    Simulation and Artificial Intelligence share a fertile common ground both from a practical and from a conceptual point of view. Strengths and weaknesses of both Knowledge Based System and Modeling and Simulation are examined and three types of systems that combine the strengths of both technologies are discussed. These types of systems are a practical starting point, however, the real strengths of both technologies will be exploited only when they are combined in a common knowledge representation paradigm. From an even deeper conceptual point of view, one might even argue that the ability to reason from a set of facts (i.e., Expert System) is less representative of human reasoning than the ability to make a model of the world, change it as required, and derive conclusions about the expected behavior of world entities. This is a fundamental problem in AI, and Modeling Theory can contribute to its solution. The application of Knowledge Engineering technology to a Distributed Processing Network Simulator (DPNS) is discussed.

  18. Artificial intelligence in short term electric load forecasting: a state-of-the-art survey for the researcher

    Energy Technology Data Exchange (ETDEWEB)

    Metaxiotis, K.; Kagiannas, A.; Askounis, D.; Psarras, J. [National Technical University of Athens, Zografou (Turkey). Dept. of Electrical and Computer Engineering

    2003-06-01

    Intelligent solutions, based on artificial intelligence (AI) technologies, to solve complicated practical problems in various sectors are becoming more and more widespread nowadays. AI-based systems are being developed and deployed worldwide in myriad applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. This paper provides an overview for the researcher of AI technologies, as well as their current use in the field of short term electric load forecasting (STELF). The history of AI in STELF is outlined, leading to a discussion of the various approaches as well as the current research directions. The paper concludes by sharing thoughts and estimations on AI future prospects in this area. This review reveals that although still regarded as a novel methodology, AI technologies are shown to have matured to the point of offering real practical benefits in many of their applications. (Author)

  19. The Human Touch: Practical and Ethical Implications of Putting AI and Robotics to Work for Patients.

    Science.gov (United States)

    Banks, Jim

    2018-01-01

    We live in a time when science fiction can quickly become science fact. Within a generation, the Internet has matured from a technological marvel to a utility, and mobile telephones have redefined how we communicate. Health care, as an industry, is quick to embrace technology, so it is no surprise that the application of programmable robotic systems that can carry out actions automatically and artificial intelligence (AI), e.g., machines that learn, solve problems, and respond to their environment, is being keenly explored.

  20. Narrative theories as computational models: reader-oriented theory and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Galloway, P.

    1983-12-01

    In view of the rapid development of reader-oriented theory and its interest in dynamic models of narrative, the author speculates in a serious way about what such models might look like in computational terms. Researchers in artificial intelligence (AI) have already begun to develop models of story understanding as the emphasis in ai research has shifted toward natural language understanding and as ai has allied itself with cognitive psychology and linguistics to become cognitive science. Research in ai and in narrative theory share many common interests and problems and both studies might benefit from an exchange of ideas. 11 references.

  1. Border Crossing Entry Data

    Data.gov (United States)

    Department of Transportation — The Bureau of Transportation Statistics (BTS) Border Crossing/Entry Data provides summary statistics for inbound crossings at the U.S.-Canadian and the U.S.-Mexican...

  2. Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

  3. Artificial intelligence a beginner's guide

    CERN Document Server

    Whitby, Blay

    2012-01-01

    Tomorrow begins right here as we embark on an enthralling and jargon-free journey into the world of computers and the inner recesses of the human mind. Readers encounter everything from the nanotechnology used to make insect-like robots, to computers that perform surgery, in addition to discovering the biggest controversies to dog the field of AI. Blay Whitby is a Lecturer on Cognitive Science and Artificial Intelligence at the University of Sussex UK. He is the author of two books and numerous papers.

  4. Entry and Exit.

    Science.gov (United States)

    1987-03-01

    1. Introduction R Analyses of industrial competition have attained a new vigor with the application of game -theoretic methods. The process of... competition is represented in models that reflect genuine struggles for entry, market power, and continuing survival. Dynamics and informational effects are...presents a few of the models developed recently to study competitive processes that affect a firm’s entry into a market , and the decision to exit. The

  5. Vision Guided Intelligent Robot Design And Experiments

    Science.gov (United States)

    Slutzky, G. D.; Hall, E. L.

    1988-02-01

    The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

  6. Management Intelligent Systems : First International Symposium

    CERN Document Server

    Martínez-López, Francisco; Rodríguez, Juan

    2012-01-01

    The 2012 International Symposium on Management Intelligent Systems is believed to be the first international forum to present and discuss original, rigorous and significant contributions on Artificial Intelligence-based (AI) solutions—with a strong, practical logic and, preferably, with empirical applications—developed to aid the management of organizations in multiple areas, activities, processes and problem-solving; i.e., what we propose to be named as Management Intelligent Systems (MiS). The three-day event aimed to bring together researchers interested in this promising interdisciplinary field who came from areas as varied as management, marketing, and business in general, computer science, artificial intelligence, statistics, etc. This volume presents the proceedings of these activities in a collection of contributions with many original approaches. They address diverse Management and Business areas of application such as decision support, segmentation of markets, CRM, product design, service person...

  7. An introduction to artificial intelligence and its potential use in space systems.

    OpenAIRE

    McDonald, Gary Wayne

    1986-01-01

    Approved for public release; distribution is unlimited This thesis provides an introduction to Artificial Intelligence and Space Systems, with comments regarding their integration. The survey of Artificial Intelligence (AI) is based upon a review of its history, its philosophical development, and subcategories of its current technologies. These subcategories are Expert Systems (ES), Natural Language Processing (NLP), Computer Vision and Pattern Recognition, and Robotic...

  8. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  9. Developing an intelligent assistant for table tennis umpires

    OpenAIRE

    Wong, Patrick K. C.

    2007-01-01

    This paper outlines the idea and plan of developing an intelligent assistant for table tennis umpire in evaluating services. Table tennis is a fast sport. A service usually takes a few second to complete but there are many observations an umpire needs to take and makes a judgment before or soon after the service is complete. This is a complex task and the author believes the employment of videography, image processing and artificial intelligence (AI) technologies could help evaluating the ser...

  10. Knowledge in Artificial Intelligence Systems: Searching the Strategies for Application

    OpenAIRE

    Kornienko, Alla A.; Kornienko, Anatoly V.; Fofanov, Oleg B.; Chubik, Maxim P.

    2015-01-01

    The studies based on auto-epistemic logic are pointed out as an advanced direction for development of artificial intelligence (AI). Artificial intelligence is taken as a system that imitates the solution of complicated problems by human during the course of life. The structure of symbols and operations, by which intellectual solution is performed, as well as searching the strategic reference points for those solutions, which are caused by certain structures of symbols and operations, – are co...

  11. Machine learning \\& artificial intelligence in the quantum domain

    OpenAIRE

    Dunjko, Vedran; Briegel, Hans J.

    2017-01-01

    Quantum information technologies, and intelligent learning systems, are both emergent technologies that will likely have a transforming impact on our society. The respective underlying fields of research -- quantum information (QI) versus machine learning (ML) and artificial intelligence (AI) -- have their own specific challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question to what extent th...

  12. Artificial intelligence applications in information and communication technologies

    CERN Document Server

    Bouguila, Nizar

    2015-01-01

    This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.  .

  13. Artificial and Computational Intelligence for Games on Mobile Platforms

    OpenAIRE

    Congdon, Clare Bates; Hingston, Philip; Kendall, Graham

    2013-01-01

    In this chapter, we consider the possibilities of creating new and innovative games that are targeted for mobile devices, such as smart phones and tablets, and that showcase AI (Artificial Intelligence) and CI (Computational Intelligence) approaches. Such games might take advantage of the sensors and facilities that are not available on other platforms, or might simply rely on the "app culture" to facilitate getting the games into users' hands. While these games might be profitable in themsel...

  14. Intelligent system for lighting control in smart cities

    OpenAIRE

    de Paz Santana, Juan F.; Bajo Pérez, Javier; Rodríguez González, Sara; Villarrubia González, Gabriel; Corchado Rodríguez, Juan M.

    2017-01-01

    This paper presents an adaptive architecture that centralizes the control of public lighting and intelligent management to economize lighting and maintain maximum visual comfort in illuminated areas. To carry out this management, the architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA, and a Service Oriented Approach (SOA). It achieves optimization in ter...

  15. Management Intelligent Systems : 2nd International Symposium

    CERN Document Server

    Martínez-López, Francisco; Vicari, Rosa; Prieta, Fernando

    2013-01-01

    This symposium was born as a research forum to present and discuss original, rigorous and significant contributions on Artificial Intelligence-based (AI) solutions—with a strong, practical logic and, preferably, with empirical applications—developed to aid the management of organizations in multiple areas, activities, processes and problem-solving; what we call Management Intelligent Systems (MiS).   This volume presents the proceedings of these activities in a collection of contributions with many original approaches. They address diverse Management and Business areas of application such as decision support, segmentation of markets, CRM, product design, service personalization, organizational design, e-commerce, credit scoring, workplace integration, innovation management, business database analysis, workflow management, location of stores, etc. A wide variety of AI techniques have been applied to these areas such as multi-objective optimization and evolutionary algorithms, classification algorithms, an...

  16. Trends in telemedicine utilizing artificial intelligence

    Science.gov (United States)

    Pacis, Danica Mitch M.; Subido, Edwin D. C.; Bugtai, Nilo T.

    2018-02-01

    With the growth and popularity of the utilization of artificial intelligence (AI) in several fields and industries, studies in the field of medicine have begun to implement its capabilities in handling and analyzing data to telemedicine. With the challenges in the implementation of telemedicine, there has been a need to expand its capabilities and improve procedures to be specialized to solve specific problems. The versatility and flexibility of both AI and telemedicine gave the endless possibilities for development and these can be seen in the literature reviewed in this paper. The trends in the development of the utilization of this technology can be classified in to four: patient monitoring, healthcare information technology, intelligent assistance diagnosis, and information analysis collaboration. Each trend will be discussed and presented with examples of recent literature and the problems they aim to address. Related references will also be tabulated and categorized to see the future and potential of this current trend in telemedicine.

  17. Application of artificial intelligence in coal preparation

    Energy Technology Data Exchange (ETDEWEB)

    Kuang, Y.; Deng, J.; Liu, H. [China University of Mining and Technology, Xuzhou (China). School of Chemical Engineering and Technology

    2001-11-01

    The general situation of using AI (Artificial intelligence) technology in coal preparation was introduced. The expert systems of coal preparation plant design, the expert management system of coal preparation plant, and the intelligent data-drawing bank were discussed. Some opinions about their foundation and method of knowledge expressing, inference, knowledge discovery of databases were presented. It is pointed out that an industrial system such as coal preparation is big and complex, so it is necessary and also difficult to use AI technology in these systems. Because the types of knowledge are different, there are various knowledge expressions and model of knowledge inference, hence only comprehensive methods suitable for the characters of the system may be used. 14 refs., 5 figs.

  18. Artificial Intelligence: An Analysis of the Technology for Training. Training and Development Research Center Project Number Fourteen.

    Science.gov (United States)

    Sayre, Scott Alan

    The ultimate goal of the science of artificial intelligence (AI) is to establish programs that will use algorithmic computer techniques to imitate the heuristic thought processes of humans. Most AI programs, especially expert systems, organize their knowledge into three specific areas: data storage, a rule set, and a control structure. Limitations…

  19. Knowledge representation an approach to artificial intelligence

    CERN Document Server

    Bench-Capon, TJM

    1990-01-01

    Although many texts exist offering an introduction to artificial intelligence (AI), this book is unique in that it places an emphasis on knowledge representation (KR) concepts. It includes small-scale implementations in PROLOG to illustrate the major KR paradigms and their developments.****back cover copy:**Knowledge representation is at the heart of the artificial intelligence enterprise: anyone writing a program which seeks to work by encoding and manipulating knowledge needs to pay attention to the scheme whereby he will represent the knowledge, and to be aware of the consequences of the ch

  20. Seventh Scandinavian Conference on Artificial Intelligence

    DEFF Research Database (Denmark)

    Lund, Henrik Hautop; Mayoh, Brian Henry; Perram, John

    2001-01-01

    The book covers the seventh Scandinavian Conference on Artificial Intelligence, held at the Maersk Mc-Kinney Moller Institute for Production Technology at the University of Southern Denmark during the period 20-21 February, 2001. It continues the tradition established by SCAI of being one...... of the most important regional AI conferences in Europe, attracting high quality submissions from Scandinavia and the rest of the world, including the Baltic countries. The contents include robotics, sensor/motor intelligence, evolutionary robotics, behaviour-based systems, multi-agent systems, applications...

  1. Artificial Intelligence Research at General Electric

    OpenAIRE

    Sweet, Larry

    1985-01-01

    General Electric is engaged in a broad range of research and development activities in artificial intelligence, with the dual objectives of improving the productivity of its internal operations and of enhancing future products and services in its aerospace, industrial, aircraft engine, commercial, and service sectors. Many of the applications projected for AI within GE will require significant advances in the state of the art in advanced inference, formal logic, and architectures for real-tim...

  2. Artificial Intelligence and Virology - quo vadis.

    Science.gov (United States)

    Shapshak, Paul; Somboonwit, Charurut; Sinnott, John T

    2017-01-01

    Artificial Intelligence (AI), robotics, co-robotics (cobots), quantum computers (QC), include surges of scientific endeavor to produce machines (mechanical and software) among numerous types and constructions that are accelerating progress to defeat infectious diseases. There is a plethora of additional applications and uses of these methodologies and technologies for the understanding of biomedicine through bioinformation discovery. Therefore, we briefly outline the use of such techniques in virology.

  3. Dicty_cDB: FC-AI01 [Dicty_cDB

    Lifescience Database Archive (English)

    Full Text Available FC (Link to library) FC-AI01 (Link to dictyBase) - - - Contig-U15592-1 FC-AI01E (Li...nk to Original site) - - - - - - FC-AI01E 307 Show FC-AI01 Library FC (Link to library) Clone ID FC-AI01 (Li.../dictycdb.biol.tsukuba.ac.jp/CSM/FC/FC-AI/FC-AI01Q.Seq.d/ Representative seq. ID FC-AI...01E (Link to Original site) Representative DNA sequence >FC-AI01 (FC-AI01Q) /CSM/FC/FC-AI/FC-AI01Q.Seq....uences producing significant alignments: (bits) Value FC-AI01 (FC-AI01Q) /CSM/FC/FC-AI/FC-AI01Q.Seq.d/ 68 8e

  4. Dicty_cDB: FC-AI13 [Dicty_cDB

    Lifescience Database Archive (English)

    Full Text Available FC (Link to library) FC-AI13 (Link to dictyBase) - - - Contig-U16263-1 FC-AI13F (Li...nk to Original site) FC-AI13F 507 - - - - - - Show FC-AI13 Library FC (Link to library) Clone ID FC-AI13 (Li.../dictycdb.biol.tsukuba.ac.jp/CSM/FC/FC-AI/FC-AI13Q.Seq.d/ Representative seq. ID FC-AI...13F (Link to Original site) Representative DNA sequence >FC-AI13 (FC-AI13Q) /CSM/FC/FC-AI/FC-AI13Q.Seq....nificant alignments: (bits) Value FC-AI13 (FC-AI13Q) /CSM/FC/FC-AI/FC-AI13Q.Seq.d/ 963 0.0 VSA730 (VSA730Q)

  5. Artificial Intelligence.

    Science.gov (United States)

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  6. Intelligent Design

    DEFF Research Database (Denmark)

    Hjorth, Poul G.

    2005-01-01

    Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig.......Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig....

  7. Developing Pokemon AI For Finding Comfortable Settings

    OpenAIRE

    Panumate, Chetprayoon; Iida, Hiroyuki

    2016-01-01

    This paper explores an innovative way to find a comfortable setting of video games. Pokemon is chosen as benchmark and game refinement measure is employed for the assessment. The number of Pokemon that one trainer can carry (i.e., setting with n=6) has never been changed after the first episode of Pokemon was released in 1996. Pokemon battle is simulated and various AIs are developed for the experiments. The results show that the original setting is the best for many players of various levels.

  8. Entry: direct control or regulation?

    NARCIS (Netherlands)

    Perotti, E.; Vorage, M.

    2009-01-01

    We model a setting in which citizens form coalitions to seek preferential entry to a given market. The lower entry the higher firm profits and political contributions, but the lower social welfare. Politicians choose to either control entry directly and be illegally bribed, or regulate entry using a

  9. Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

    Science.gov (United States)

    Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

  10. Deep Blue Cannot Play Checkers: The Need for Generalized Intelligence for Mobile Robots

    Directory of Open Access Journals (Sweden)

    Troy D. Kelley

    2010-01-01

    Full Text Available Generalized intelligence is much more difficult than originally anticipated when Artificial Intelligence (AI was first introduced in the early 1960s. Deep Blue, the chess playing supercomputer, was developed to defeat the top rated human chess player and successfully did so by defeating Gary Kasporov in 1997. However, Deep Blue only played chess; it did not play checkers, or any other games. Other examples of AI programs which learned and played games were successful at specific tasks, but generalizing the learned behavior to other domains was not attempted. So the question remains: Why is generalized intelligence so difficult? If complex tasks require a significant amount of development, time and task generalization is not easily accomplished, then a significant amount of effort is going to be required to develop an intelligent system. This approach will require a system of systems approach that uses many AI techniques: neural networks, fuzzy logic, and cognitive architectures.

  11. Development of a Car Racing Simulator Game Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Marvin T. Chan

    2015-01-01

    Full Text Available This paper presents a car racing simulator game called Racer, in which the human player races a car against three game-controlled cars in a three-dimensional environment. The objective of the game is not to defeat the human player, but to provide the player with a challenging and enjoyable experience. To ensure that this objective can be accomplished, the game incorporates artificial intelligence (AI techniques, which enable the cars to be controlled in a manner that mimics natural driving. The paper provides a brief history of AI techniques in games, presents the use of AI techniques in contemporary video games, and discusses the AI techniques that were implemented in the development of Racer. A comparison of the AI techniques implemented in the Unity platform with traditional AI search techniques is also included in the discussion.

  12. Artificial Psychology: The Psychology of AI

    Directory of Open Access Journals (Sweden)

    James A. Crowder

    2013-12-01

    Full Text Available Having artificially intelligent machines that think, learn, reason, experience, and can function autonomously, without supervision, is one of the most intriguing goals in all of Computer Science. As the types of problems we would like machines to solve get more complex, it is becoming a necessary goal as well. One of the many problems associated with this goal is that what learning and reasoning are have so many possible meanings that the solution can easily get lost in the sea of opinions and options. The goal of this paper is to establish some foundational principles, theory, and concepts that we feel are the backbone of real, autonomous Artificial Intelligence. With this fully autonomous, learning, reasoning, artificially intelligent system (an artificial brain, comes the need to possess constructs in its hardware and software that mimic processes and subsystems that exist within the human brain, including intuitive and emotional memory concepts. Presented here is a discussion of the psychological constructs of artificial intelligence and how they might play out in an artificial mind.

  13. Artificial intelligence applications concepts for the remote sensing and earth science community

    Science.gov (United States)

    Campbell, W. J.; Roelofs, L. H.

    1984-01-01

    The following potential applications of AI to the study of earth science are described: (1) intelligent data management systems; (2) intelligent processing and understanding of spatial data; and (3) automated systems which perform tasks that currently require large amounts of time by scientists and engineers to complete. An example is provided of how an intelligent information system might operate to support an earth science project.

  14. Report on the First Conference on Artificial General Intelligence (AGI-08)

    OpenAIRE

    de Garis, Hugo Roland; Xiamen University; Goertzel, Ben; Novamente LLC

    2009-01-01

    The First Conference on Artificial General Intelligence (AGI-08) was held on March 1-3, 2008, at the University of Memphis. The overall goal of the conference was to work toward a common understanding of the most promising paths toward creating AI systems with general intelligence at the human level and beyond, and to share interim results and ideas achieved by researchers actively working toward powerful artificial general intelligence.

  15. How People Interact with Technology based on Natural and Artificial Intelligence

    OpenAIRE

    Vasile MAZILESCU

    2017-01-01

    This paper aims to analyse the different forms of intelligence within organizations in a systemic and inclusive vision, in order to design an integrated environment based on Artificial Intelligence (AI) and Collective Intelligence (CI). This way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow), of connecting people with...

  16. Challenges and Characteristics of Intelligent Autonomy for Internet of Battle Things in Highly Adversarial Environments

    OpenAIRE

    Kott, Alexander

    2018-01-01

    Numerous, artificially intelligent, networked things will populate the battlefield of the future, operating in close collaboration with human warfighters, and fighting as teams in highly adversarial environments. This paper explores the characteristics, capabilities and intelligence required of such a network of intelligent things and humans - Internet of Battle Things (IOBT). It will experience unique challenges that are not yet well addressed by the current generation of AI and machine lear...

  17. [Artificial intelligence in medicine: limits and obstacles.

    Science.gov (United States)

    Santoro, Eugenio

    2017-12-01

    Data scientists and physicians are starting to use artificial intelligence (AI) even in the medical field in order to better understand the relationships among the huge amount of data coming from the great number of sources today available. Through the data interpretation methods made available by the recent AI tools, researchers and AI companies have focused on the development of models allowing to predict the risk of suffering from a specific disease, to make a diagnosis, and to recommend a treatment that is based on the best and most updated scientific evidence. Even if AI is used to perform unimaginable tasks until a few years ago, the awareness about the ongoing revolution has not yet spread through the medical community for several reasons including the lack of evidence about safety, reliability and effectiveness of these tools, the lack of regulation accompanying hospitals in the use of AI by health care providers, the difficult attribution of liability in case of errors and malfunctions of these systems, and the ethical and privacy questions that they raise and that, as of today, are still unanswered.

  18. Dissecting phenotypic variation among AIS patients

    International Nuclear Information System (INIS)

    Wang Minghua; Wang Jiucun; Zhang Zhen; Zhao Zhimin; Zhang Rongmei; Hu Xiaohua; Tan Tao; Luo Shijing; Luo Zewei

    2005-01-01

    We have created genital skin fibroblast cell lines directly from three patients in a Chinese family affected by androgen insensitivity syndrome (AIS). All patients in the family share an identical AR Arg 840 Cys mutant but show different disease phenotypes. By using the cell lines, we find that the mutation has not influenced a normal androgen-binding capacity at 37 deg C but has reduced the affinity for androgens and may cause thermolability of the androgen-receptor complex. The impaired nuclear trafficking of the androgen receptor in the cell lines is highly correlated with the severity of donors' disease phenotype. The transactivity of the mutant is substantially weakened and the extent of the reduced transactivity reflects severity of the donors' disease symptom. Our data reveal that although etiology of AIS is monogenic and the mutant may alter the major biological functions of its wild allele, the function of the mutant AR can also be influenced by the different genetic backgrounds and thus explains the divergent disease phenotypes

  19. Application of artificial intelligence to risk analysis for forested ecosystems

    Science.gov (United States)

    Daniel L. Schmoldt

    2001-01-01

    Forest ecosystems are subject to a variety of natural and anthropogenic disturbances that extract a penalty from human population values. Such value losses (undesirable effects) combined with their likelihoods of occurrence constitute risk. Assessment or prediction of risk for various events is an important aid to forest management. Artificial intelligence (AI)...

  20. Automatic food detection in egocentric images using artificial intelligence technology

    Science.gov (United States)

    Our objective was to develop an artificial intelligence (AI)-based algorithm which can automatically detect food items from images acquired by an egocentric wearable camera for dietary assessment. To study human diet and lifestyle, large sets of egocentric images were acquired using a wearable devic...

  1. Research Priorities for Robust and Beneficial Artificial Intelligence

    OpenAIRE

    Russell, Stuart; Dewey, Daniel; Tegmark, Max

    2015-01-01

    Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to investigate how to maximize these benefits while avoiding potential pitfalls. This article gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial.

  2. An application of artificial intelligence for rainfall–runoff modeling

    Indian Academy of Sciences (India)

    This study proposes an application of two techniques of artificial intelligence (AI) for rainfall–runoff modeling: the artificial neural networks (ANN) and the evolutionary computation (EC). Two diff- erent ANN techniques, the feed forward back propagation (FFBP) and generalized regression neural network (GRNN) methods ...

  3. AI model for computer games based on case based reasoning and AI planning

    NARCIS (Netherlands)

    Menkovski, V.; Metafas, D.

    2008-01-01

    Making efficient AI models for games with imperfect information can be a particular challenge. Considering the large number of possible moves and the incorporated uncertainties building game trees for these games becomes very difficult due to the exponential growth of the number of nodes at each

  4. 3rd Euro-China Conference on Intelligent Data Analysis and Applications

    CERN Document Server

    Snášel, Václav; Sung, Tien-Wen; Wang, Xiao

    2017-01-01

    This book gathers papers presented at the ECC 2016, the Third Euro-China Conference on Intelligent Data Analysis and Applications, which was held in Fuzhou City, China from November 7 to 9, 2016. The aim of the ECC is to provide an internationally respected forum for scientific research in the broad areas of intelligent data analysis, computational intelligence, signal processing, and all associated applications of artificial intelligence (AI). The third installment of the ECC was jointly organized by Fujian University of Technology, China, and VSB-Technical University of Ostrava, Czech Republic. The conference was co-sponsored by Taiwan Association for Web Intelligence Consortium, and Immersion Co., Ltd.

  5. Exclusive Dealing and Entry

    OpenAIRE

    João Leão

    2008-01-01

    This paper examines the use of exclusive dealing agreements to prevent the entry of rival firms. An exclusive dealing agreement is a contract between a buyer and a seller where the buyer commits to buy a good exclusively from the seller. One main concern of the literature is to explain how an incumbent seller is able to persuade the buyers to sign an exclusive dealing agreement that deters the entry of a more efficient rival seller. We propose a new explanation when the buyers are downstream ...

  6. Decision-Making and the Interface between Human Intelligence and Artificial Intelligence. AIR 1987 Annual Forum Paper.

    Science.gov (United States)

    Henard, Ralph E.

    Possible future developments in artificial intelligence (AI) as well as its limitations are considered that have implications for institutional research in higher education, and especially decision making and decision support systems. It is noted that computer software programs have been developed that store knowledge and mimic the decision-making…

  7. Intelligent playgrounds

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    2009-01-01

    This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...

  8. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  9. Risk Reducing Effect of AIS Implementation on Collision Risk

    DEFF Research Database (Denmark)

    Lützen, Marie; Friis-Hansen, Peter

    2003-01-01

    AIS (Automatic Identification System) is a transponder system developed for sea traffic purposes. The system sends and receives important ship information and other safety-related information between other ships and shore-based AIS stations. The implementation of AIS has now been initiated and......, as a result, the community will undoubtedly observe an increase in navigational safety. However, to the authors? knowledge, no study has so far rigorously quantified the risk reducing effect of using AIS as an integrated part of the navigational system. The objective of this study is to fill this gap....... The risk reducing effect of AIS is quantified by building a Bayesian network facilitating an evaluation of the effect of AIS on the navigational officer?s reaction ability in a potential, critical collision situation. The time-dependent change in the risk reducing effect on ship collisions is analysed...

  10. Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

  11. Artificial intelligence and the space station software support environment

    Science.gov (United States)

    Marlowe, Gilbert

    1986-01-01

    In a software system the size of the Space Station Software Support Environment (SSE), no one software development or implementation methodology is presently powerful enough to provide safe, reliable, maintainable, cost effective real time or near real time software. In an environment that must survive one of the most harsh and long life times, software must be produced that will perform as predicted, from the first time it is executed to the last. Many of the software challenges that will be faced will require strategies borrowed from Artificial Intelligence (AI). AI is the only development area mentioned as an example of a legitimate reason for a waiver from the overall requirement to use the Ada programming language for software development. The limits are defined of the applicability of the Ada language Ada Programming Support Environment (of which the SSE is a special case), and software engineering to AI solutions by describing a scenario that involves many facets of AI methodologies.

  12. Automatic detection of mycobacterium tuberculosis using artificial intelligence

    Science.gov (United States)

    Xiong, Yan; Ba, Xiaojun; Hou, Ao; Zhang, Kaiwen; Chen, Longsen

    2018-01-01

    Background Tuberculosis (TB) is a global issue that seriously endangers public health. Pathology is one of the most important means for diagnosing TB in clinical practice. To confirm TB as the diagnosis, finding specially stained TB bacilli under a microscope is critical. Because of the very small size and number of bacilli, it is a time-consuming and strenuous work even for experienced pathologists, and this strenuosity often leads to low detection rate and false diagnoses. We investigated the clinical efficacy of an artificial intelligence (AI)-assisted detection method for acid-fast stained TB bacillus. Methods We built a convolutional neural networks (CNN) model, named tuberculosis AI (TB-AI), specifically to recognize TB bacillus. The training set contains 45 samples, including 30 positive cases and 15 negative cases, where bacilli are labeled by human pathologists. Upon training the neural network model, 201 samples (108 positive cases and 93 negative cases) were collected as test set and used to examine TB-AI. We compared the diagnosis of TB-AI to the ground truth result provided by human pathologists, analyzed inconsistencies between AI and human, and adjusted the protocol accordingly. Trained TB-AI were run on the test data twice. Results Examined against the double confirmed diagnosis by pathologists both via microscopes and digital slides, TB-AI achieved 97.94% sensitivity and 83.65% specificity. Conclusions TB-AI can be a promising support system to detect stained TB bacilli and help make clinical decisions. It holds the potential to relieve the heavy workload of pathologists and decrease chances of missed diagnosis. Samples labeled as positive by TB-AI must be confirmed by pathologists, and those labeled as negative should be reviewed to make sure that the digital slides are qualified. PMID:29707349

  13. Automatic detection of mycobacterium tuberculosis using artificial intelligence.

    Science.gov (United States)

    Xiong, Yan; Ba, Xiaojun; Hou, Ao; Zhang, Kaiwen; Chen, Longsen; Li, Ting

    2018-03-01

    Tuberculosis (TB) is a global issue that seriously endangers public health. Pathology is one of the most important means for diagnosing TB in clinical practice. To confirm TB as the diagnosis, finding specially stained TB bacilli under a microscope is critical. Because of the very small size and number of bacilli, it is a time-consuming and strenuous work even for experienced pathologists, and this strenuosity often leads to low detection rate and false diagnoses. We investigated the clinical efficacy of an artificial intelligence (AI)-assisted detection method for acid-fast stained TB bacillus. We built a convolutional neural networks (CNN) model, named tuberculosis AI (TB-AI), specifically to recognize TB bacillus. The training set contains 45 samples, including 30 positive cases and 15 negative cases, where bacilli are labeled by human pathologists. Upon training the neural network model, 201 samples (108 positive cases and 93 negative cases) were collected as test set and used to examine TB-AI. We compared the diagnosis of TB-AI to the ground truth result provided by human pathologists, analyzed inconsistencies between AI and human, and adjusted the protocol accordingly. Trained TB-AI were run on the test data twice. Examined against the double confirmed diagnosis by pathologists both via microscopes and digital slides, TB-AI achieved 97.94% sensitivity and 83.65% specificity. TB-AI can be a promising support system to detect stained TB bacilli and help make clinical decisions. It holds the potential to relieve the heavy workload of pathologists and decrease chances of missed diagnosis. Samples labeled as positive by TB-AI must be confirmed by pathologists, and those labeled as negative should be reviewed to make sure that the digital slides are qualified.

  14. Lobbying on entry

    NARCIS (Netherlands)

    Perotti, E.C.; Volpin, P.

    2004-01-01

    We develop a model of endogenous lobby formation in which wealth inequality and political accountability undermine entry and financial development. Incumbents seek a low level of effective investor protection to prevent potential entrants from raising capital. They succeed because they can promise

  15. Using design science and artificial intelligence to improve health communication: ChronologyMD case example.

    Science.gov (United States)

    Neuhauser, Linda; Kreps, Gary L; Morrison, Kathleen; Athanasoulis, Marcos; Kirienko, Nikolai; Van Brunt, Deryk

    2013-08-01

    This paper describes how design science theory and methods and use of artificial intelligence (AI) components can improve the effectiveness of health communication. We identified key weaknesses of traditional health communication and features of more successful eHealth/AI communication. We examined characteristics of the design science paradigm and the value of its user-centered methods to develop eHealth/AI communication. We analyzed a case example of the participatory design of AI components in the ChronologyMD project intended to improve management of Crohn's disease. eHealth/AI communication created with user-centered design shows improved relevance to users' needs for personalized, timely and interactive communication and is associated with better health outcomes than traditional approaches. Participatory design was essential to develop ChronologyMD system architecture and software applications that benefitted patients. AI components can greatly improve eHealth/AI communication, if designed with the intended audiences. Design science theory and its iterative, participatory methods linked with traditional health communication theory and methods can create effective AI health communication. eHealth/AI communication researchers, developers and practitioners can benefit from a holistic approach that draws from theory and methods in both design sciences and also human and social sciences to create successful AI health communication. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  16. Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success.

    Science.gov (United States)

    Thrall, James H; Li, Xiang; Li, Quanzheng; Cruz, Cinthia; Do, Synho; Dreyer, Keith; Brink, James

    2018-03-01

    Worldwide interest in artificial intelligence (AI) applications, including imaging, is high and growing rapidly, fueled by availability of large datasets ("big data"), substantial advances in computing power, and new deep-learning algorithms. Apart from developing new AI methods per se, there are many opportunities and challenges for the imaging community, including the development of a common nomenclature, better ways to share image data, and standards for validating AI program use across different imaging platforms and patient populations. AI surveillance programs may help radiologists prioritize work lists by identifying suspicious or positive cases for early review. AI programs can be used to extract "radiomic" information from images not discernible by visual inspection, potentially increasing the diagnostic and prognostic value derived from image datasets. Predictions have been made that suggest AI will put radiologists out of business. This issue has been overstated, and it is much more likely that radiologists will beneficially incorporate AI methods into their practices. Current limitations in availability of technical expertise and even computing power will be resolved over time and can also be addressed by remote access solutions. Success for AI in imaging will be measured by value created: increased diagnostic certainty, faster turnaround, better outcomes for patients, and better quality of work life for radiologists. AI offers a new and promising set of methods for analyzing image data. Radiologists will explore these new pathways and are likely to play a leading role in medical applications of AI. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  17. Automatic Identification System (AIS) Transmit Testing in Louisville Phase 2

    Science.gov (United States)

    2014-08-01

    Firewall Louisville QM 65.206.28.x NAIS Site Controller PC RS232 Serial cable TV32 Computer Cmd Center Serial splitter SAAB R40 AIS Base Station...172.17.14.6 Rack mount computer AIS Radio Interface Ethernet Switch 192.168.0.x Firewall Cable Modem 192.168.0.1 VTS Accred. Boundary serial connection...Automatic Identification System ( AIS ) Transmit Testing in Louisville Phase 2 Distribution Statement A: Approved for public release

  18. AI User Support System for SAP ERP

    Science.gov (United States)

    Vlasov, Vladimir; Chebotareva, Victoria; Rakhimov, Marat; Kruglikov, Sergey

    2017-10-01

    An intelligent system for SAP ERP user support is proposed in this paper. It enables automatic replies on users’ requests for support, saving time for problem analysis and resolution and improving responsiveness for end users. The system is based on an ensemble of machine learning algorithms of multiclass text classification, providing efficient question understanding, and a special framework for evidence retrieval, providing the best answer derivation.

  19. Intelligent Advertising

    OpenAIRE

    Díaz Pinedo, Edilfredo Eliot

    2012-01-01

    Intelligent Advertisement diseña e implementa un sistema de publicidad para dispositivos móviles en un centro comercial, donde los clientes reciben publicidad de forma pasiva en sus dispositivos mientras están dentro.

  20. Distributed artificial intelligence, diversity and information literacy

    Directory of Open Access Journals (Sweden)

    Peter Kåhre

    2010-09-01

    Full Text Available My proposal is based on my doctoral dissertation On the Shoulders of AI-technology : Sociology of Knowledge and Strong Artificial Intelligence which I succesfully defended on May 29th 2009. E-published http://www.lu.se/o.o.i.s?id=12588&postid=1389611 The dissertation is concerned with Sociology’s stance in the debate on Strong Artificial Intelligence,.i.e. AI-systems that is able to shape knowledge on their own. There is a need for sociologists to realize the difference between two approaches to constructing AI systems: Symbolic AI (or Classic AI and Connectionistic AI in a distributed model – DAI. Sociological literature shows a largely critical attitude towards Symbolic AI, an attitude that is justified. The main theme of the dissertation is that DAI is not only compatible with Sociology’s approach to what is social, but also constitutes an apt model of how a social system functions. This is consolidated with help from german sociologist Niklas Luhmann’s social systems theory. A lot of sociologists criticize AI because they think that diversity is important and can only be comprehended in informal circumstances that only humans interacting together can handle. They mean that social intelligence is needed to make something out of diversity and informalism. Luhmann´s systems theory gives the opposite perspective. It tells us that it is social systems that communicate and produce new knowledge structures out of contincency. Psychological systems, i.e. humans, can only think within the circumstances the social system offer. In that way human thoughts are bound by formalism. Diversity is constructed when the social systems interact with complexity in their environments. They reduce the complexity and try to present it as meaningful diversity. Today when most of academic literature is electronically stored and is accessible through the Internet from al over the world, DAI can help social systems to observe and reduce complexity in this

  1. The implementation of AI technologies in computer wargames

    Science.gov (United States)

    Tiller, John A.

    2004-08-01

    Computer wargames involve the most in-depth analysis of general game theory. The enumerated turns of a game like chess are dwarfed by the exponentially larger possibilities of even a simple computer wargame. Implementing challenging AI is computer wargames is an important goal in both the commercial and military environments. In the commercial marketplace, customers demand a challenging AI opponent when they play a computer wargame and are frustrated by a lack of competence on the part of the AI. In the military environment, challenging AI opponents are important for several reasons. A challenging AI opponent will force the military professional to avoid routine or set-piece approaches to situations and cause them to think much deeper about military situations before taking action. A good AI opponent would also include national characteristics of the opponent being simulated, thus providing the military professional with even more of a challenge in planning and approach. Implementing current AI technologies in computer wargames is a technological challenge. The goal is to join the needs of AI in computer wargames with the solutions of current AI technologies. This talk will address several of those issues, possible solutions, and currently unsolved problems.

  2. AI tools in computer based problem solving

    Science.gov (United States)

    Beane, Arthur J.

    1988-01-01

    The use of computers to solve value oriented, deterministic, algorithmic problems, has evolved a structured life cycle model of the software process. The symbolic processing techniques used, primarily in research, for solving nondeterministic problems, and those for which an algorithmic solution is unknown, have evolved a different model, much less structured. Traditionally, the two approaches have been used completely independently. With the advent of low cost, high performance 32 bit workstations executing identical software with large minicomputers and mainframes, it became possible to begin to merge both models into a single extended model of computer problem solving. The implementation of such an extended model on a VAX family of micro/mini/mainframe systems is described. Examples in both development and deployment of applications involving a blending of AI and traditional techniques are given.

  3. Artificial intelligence techniques for sizing photovoltaic systems. A review

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, A. [Department of Electronics, Faculty of Science Engineering, LAMEL Laboratory, Jijel University, P.O. Box 98, Oulad Aissa, Jijel 18000 (Algeria); Kalogirou, S.A. [Department of Mechanical Engineering and Materials Science and Engineering, Cyprus University of Technology, P.O. Box 50329, Limassol 3603 (Cyprus); Hontoria, L. [Grupo Investigacion y Desarrollo en Energia Solar y Automatica, Dpto. de Electronica, E.P.S. Jaen, Universidad de Jaen, Avda., Madrid, 35, 23071 Jaen (Spain); Shaari, S. [Faculty of Applied Sciences, Universiti Teknologi MARA 40450 Shah Alam, Selangor (Malaysia)

    2009-02-15

    Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. AI-techniques have the following features: can learn from examples; are fault tolerant in the sense that they are able to handle noisy and incomplete data; are able to deal with non-linear problems; and once trained can perform prediction and generalization at high speed. AI-based systems are being developed and deployed worldwide in a myriad of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. AI have been used and applied in different sectors, such as engineering, economics, medicine, military, marine, etc. They have also been applied for modeling, identification, optimization, prediction, forecasting, and control of complex systems. The main objective of this paper is to present an overview of the AI-techniques for sizing photovoltaic (PV) systems: stand-alone PVs, grid-connected PV systems, PV-wind hybrid systems, etc. Published literature presented in this paper show the potential of AI as a design tool for the optimal sizing of PV systems. Additionally, the advantage of using an AI-based sizing of PV systems is that it provides good optimization, especially in isolated areas, where the weather data are not always available. (author)

  4. BUSINESS INTELLIGENCE

    OpenAIRE

    Bogdan Mohor Dumitrita

    2011-01-01

    The purpose of this work is to present business intelligence systems. These systems can be extremely complex and important in modern market competition. Its effectiveness also reflects in price, so we have to exlore their financial potential before investment. The systems have 20 years long history and during that time many of such tools have been developed, but they are rarely still in use. Business intelligence system consists of three main areas: Data Warehouse, ETL tools and tools f...

  5. Intelligent indexing

    International Nuclear Information System (INIS)

    Farkas, J.

    1992-01-01

    In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space ι 2 to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs

  6. Intelligent indexing

    Energy Technology Data Exchange (ETDEWEB)

    Farkas, J

    1993-12-31

    In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space {iota}{sup 2} to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs.

  7. Dicty_cDB: FC-AI17 [Dicty_cDB

    Lifescience Database Archive (English)

    Full Text Available FC (Link to library) FC-AI17 (Link to dictyBase) - - - Contig-U15690-1 FC-AI17P (Li...nk to Original site) FC-AI17F 587 FC-AI17Z 626 FC-AI17P 1212 - - Show FC-AI17 Library FC (Link to library) Clone ID FC-AI...nal site URL http://dictycdb.biol.tsukuba.ac.jp/CSM/FC/FC-AI/FC-AI17Q.Seq.d/ Representative seq. ID FC-AI...17P (Link to Original site) Representative DNA sequence >FC-AI17 (FC-AI17Q) /CSM/FC/FC-AI/FC-AI...slated Amino Acid sequence ANIATVGDFLKADTVVPKMIITYNKRKQGTDYLKAVIGPILSNVIKQELNLELKPNLVYA AIISEQEIRTGEKSTLDRNV

  8. Dicty_cDB: FC-AI18 [Dicty_cDB

    Lifescience Database Archive (English)

    Full Text Available FC (Link to library) FC-AI18 (Link to dictyBase) - - - Contig-U15590-1 FC-AI18P (Li...nk to Original site) FC-AI18F 621 FC-AI18Z 703 FC-AI18P 1324 - - Show FC-AI18 Library FC (Link to library) Clone ID FC-AI...nal site URL http://dictycdb.biol.tsukuba.ac.jp/CSM/FC/FC-AI/FC-AI18Q.Seq.d/ Representative seq. ID FC-AI...18P (Link to Original site) Representative DNA sequence >FC-AI18 (FC-AI18Q) /CSM/FC/FC-AI/FC-AI...AVWPLIPGYERA DGEKQYPVAAMLCNFTKPTPTTPSLLTHDEVVTFFHEFGHVMHNMSTKVHYSMFSGTSVE RDFVECPSQLFEFWCWNKDVLVNKLSGHXKDHSKKLPTDLVERMIAAKNLNVAI

  9. Dicty_cDB: FC-AI03 [Dicty_cDB

    Lifescience Database Archive (English)

    Full Text Available FC (Link to library) FC-AI03 (Link to dictyBase) - - - Contig-U15833-1 FC-AI03P (Li...nk to Original site) FC-AI03F 690 FC-AI03Z 651 FC-AI03P 1341 - - Show FC-AI03 Library FC (Link to library) Clone ID FC-AI...nal site URL http://dictycdb.biol.tsukuba.ac.jp/CSM/FC/FC-AI/FC-AI03Q.Seq.d/ Representative seq. ID FC-AI...03P (Link to Original site) Representative DNA sequence >FC-AI03 (FC-AI03Q) /CSM/FC/FC-AI/FC-AI...li*l*ivtlskv*qswyqvfcslmrftcwi*nv fht*ivhwsqhwhql*flqpivaiv*skapitifnlhmaslwif*ivl*sfvpfhiitmk sfkfspfvpqlki

  10. A review of European applications of artificial intelligence to space

    Science.gov (United States)

    Drummond, Mark (Editor); Stewart, Helen (Editor)

    1993-01-01

    The purpose is to describe the applications of Artificial Intelligence (AI) to the European Space program that are being developed or have been developed. The results of a study sponsored by the Artificial Intelligence Research and Development program of NASA's Office of Advanced Concepts and Technology (OACT) are described. The report is divided into two sections. The first consists of site reports, which are descriptions of the AI applications seen at each place visited. The second section consists of two summaries which synthesize the information in the site reports by organizing this information in two different ways. The first organizes the material in terms of the type of application, e.g., data analysis, planning and scheduling, and procedure management. The second organizes the material in terms of the component technologies of Artificial Intelligence which the applications used, e.g., knowledge based systems, model based reasoning, procedural reasoning, etc.

  11. First steps in translating human cognitive processes of cane pruning grapevines into AI rules for automated robotic pruning

    Directory of Open Access Journals (Sweden)

    Saxton Valerie

    2014-01-01

    Full Text Available Cane pruning of grapevines is a skilled task for which, internationally, there is a dire shortage of human pruners. As part of a larger project developing an automated robotic pruner, we have used artificial intelligence (AI algorithms to create an expert system for selecting new canes and cutting off unwanted canes. A domain and ontology has been created for AI, which reflects the expertise of expert human pruners. The first step in the creation of an expert system was to generate virtual vines, which were then ‘pruned’ by human pruners and also by the expert system in its infancy. Here we examined the decisions of 12 human pruners, for consistency of decision, on 60 virtual vines. 96.7% of the 12 pruners agreed on at least one cane choice after which there was diminishing agreement on which further canes to select for laying. Our results indicate that techniques developed in computational intelligence can be used to co-ordinate and synthesise the expertise of human pruners into a best practice format. This paper describes first steps in this knowledge elicitation process, and discusses the fit between cane pruning expertise and the expertise that can be elicited using AI based expert system techniques.

  12. Atmospheric Entry Studies for Uranus

    Science.gov (United States)

    Agrawal, P.; Allen, G. A.; Hwang, H. H.; Marley, M. S.; McGuire, M. K.; Garcia, J. A.; Sklyanskiy, E.; Huynh, L. C.; Moses, R. W.

    2014-07-01

    To better understand the technology requirements for Uranus atmospheric entry probe, Entry Vehicle Technology project funded an internal study with a multidisciplinary team from NASA Ames, Langley and JPL. The results of this study are communicated.

  13. Border Crossing/Entry Data

    Data.gov (United States)

    Department of Transportation — The dataset is known as “Border Crossing/Entry Data.” The Bureau of Transportation Statistics (BTS) Border Crossing/Entry Data provides summary statistics to the...

  14. Q&A: The AI composer

    Science.gov (United States)

    Spinney, Laura

    2017-09-01

    Computer scientist Luc Steels uses artificial intelligence to explore the origins and evolution of language. He is best known for his 1999-2001 Talking Heads Experiment, in which robots had to construct a language from scratch to communicate with each other. Now Steels, who works at the Free University of Brussels (VUB), has composed an opera based on the legend of Faust, with a twenty-first-century twist. He talks about Mozart as a nascent computer programmer, how music maps onto language, and the blurred boundaries of a digitized world.

  15. Satellite and Missile Data Generation for AIS.

    Science.gov (United States)

    1979-12-01

    for the Study of Artificiel Intelli- gence and the Simulation of Behaviour , July 1976, 104-117. Engel, E.S. & Granda, R.E. Guidelines for Man/Display...A. Implicit Causality In Verbs. Linquistic Inquire, 5(3), Sum- mer 1974, 464-469. 6-6 Garvey, C., Caramazza, A. and Yates, J. Factors Influencing ...Intelligence Laboratory, Stanford University, 1974. Goldman, N.M. Conceptual Generation. in: Schank 1975, 289-371. Goldstein, I.P. and Roberts, R. B. NUDGE

  16. Artificial Intelligence: An Analysis of Potential Applications to Training, Performance Measurement, and Job Performance Aiding. Interim Report for Period September 1982-July 1983.

    Science.gov (United States)

    Richardson, J. Jeffrey

    This paper is part of an Air Force planning effort to develop a research, development, and applications program for the use of artificial intelligence (AI) technology in three target areas: training, performance measurement, and job performance aiding. The paper is organized in five sections that (1) introduce the reader to AI and those subfields…

  17. Ai Weiwei - 21. sajandi märter? / Tanel Veenre

    Index Scriptorium Estoniae

    Veenre, Tanel, 1977-

    2011-01-01

    Hiina kunstniku, inimõiguslase ja teisitimõtleja Ai Weiwei elust, õpingutest, loomingust ja tegevusest. Hiinas kunstniku tagakiusamisest, arreteerimisest, maksupettuses süüdistamisest jm. Kunstniku toetajatest. Inglise kunstileht Art Review valis Ai Weiwei 2011. a. kõige mõjuvõimsamaks kunstitegelaseks

  18. Integrating the Wall Street Journal into AIS Courses

    Science.gov (United States)

    Kohlmeyer, James M., III

    2008-01-01

    While it is important for accounting information systems (AIS) students to understand computer technology, internal controls and business processes, such knowledge is of little use without reference to appropriate contexts. Integrating Wall Street Journal (WSJ) readings and discussions into AIS classes can enrich learning by stimulating…

  19. Brosimacutins A-I, nine new flavonoids from Brosimum acutifolium.

    Science.gov (United States)

    Takashima, Junko; Ohsaki, Ayumi

    2002-12-01

    Nine new flavonoids, brosimacutins A-I (1-9), and four known flavonoids were isolated from the bark of Brosimum acutifolium, a Brazilian folk medicine ("Mururé"). Their structures were elucidated by spectroscopic methods, including 2D NMR. Brosimacutins A-I possess differentially functionalized isoprene units at C-8.

  20. the Lexique kikongo–français by

    African Journals Online (AJOL)

    Gilles-Maurice de Schryver

    français by the Jesuit missionary Charles Polis, is analysed in great detail. Section 1 expounds on the goal and ... dictionary manuscript for Kikongo: the Lexique kikongo–français by Charles Polis. s.j. (1885–†1943). .... Inkisi River, and all but one (Leverville, the present Lusanga) are close to that river, which thus strongly ...

  1. Recent advances in knowledge-based paradigms and applications enhanced applications using hybrid artificial intelligence techniques

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

    This book presents carefully selected contributions devoted to the modern perspective of AI research and innovation. This collection covers several areas of applications and motivates new research directions. The theme across all chapters combines several domains of AI research , Computational Intelligence and Machine Intelligence including an introduction to  the recent research and models. Each of the subsequent chapters reveals leading edge research and innovative solution that employ AI techniques with an applied perspective. The problems include classification of spatial images, early smoke detection in outdoor space from video images, emergent segmentation from image analysis, intensity modification in images, multi-agent modeling and analysis of stress. They all are novel pieces of work and demonstrate how AI research contributes to solutions for difficult real world problems that benefit the research community, industry and society.

  2. Non-Newtonian Aspects of Artificial Intelligence

    Science.gov (United States)

    Zak, Michail

    2016-05-01

    The challenge of this work is to connect physics with the concept of intelligence. By intelligence we understand a capability to move from disorder to order without external resources, i.e., in violation of the second law of thermodynamics. The objective is to find such a mathematical object described by ODE that possesses such a capability. The proposed approach is based upon modification of the Madelung version of the Schrodinger equation by replacing the force following from quantum potential with non-conservative forces that link to the concept of information. A mathematical formalism suggests that a hypothetical intelligent particle, besides the capability to move against the second law of thermodynamics, acquires such properties like self-image, self-awareness, self-supervision, etc. that are typical for Livings. However since this particle being a quantum-classical hybrid acquires non-Newtonian and non-quantum properties, it does not belong to the physics matter as we know it: the modern physics should be complemented with the concept of the information force that represents a bridge to intelligent particle. As a follow-up of the proposed concept, the following question is addressed: can artificial intelligence (AI) system composed only of physical components compete with a human? The answer is proven to be negative if the AI system is based only on simulations, and positive if digital devices are included. It has been demonstrated that there exists such a quantum neural net that performs simulations combined with digital punctuations. The universality of this quantum-classical hybrid is in capability to violate the second law of thermodynamics by moving from disorder to order without external resources. This advanced capability is illustrated by examples. In conclusion, a mathematical machinery of the perception that is the fundamental part of a cognition process as well as intelligence is introduced and discussed.

  3. Artificial Intelligence Methodologies and Their Application to Diabetes.

    Science.gov (United States)

    Rigla, Mercedes; García-Sáez, Gema; Pons, Belén; Hernando, Maria Elena

    2018-03-01

    In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors' decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers-doctors and nurses-in this field.

  4. Radioimmunoassay of apolipoprotein A-I of rat serum

    International Nuclear Information System (INIS)

    Fainaru, M.; Havel, R.J.; Felker, T.E.

    1976-01-01

    A double antibody radioimmunoassay technique was developed for quantification of apolipoprotein A-I, the major apoprotein of rat high density lipoprotein. Apo A-I was labelled with 125 I by the chloramine-T method. 125 I-labeled apo A-I had the same electrophoretic mobility as unlabeled apo A-I and more than 80% of the 125 I was precipitated by rabbit anti apo A-I antibodies. The assay is sensitive at the level of 0.5-5 ng, and has intraassay and interassay coefficients of variation of 4.5 and 6.5% respectively. The specificity of the assay was established by competitive displacement of 125 I-labeled apo A-I from its antibody by apo A-I and lipoproteins containing apo A-I, but not by rat albumin and other apoproteins. Immunoreactivity of high density lipoprotein and serum was only about 35% of that of their delipidated forms when Veronal buffer was used as a diluent. Inclusion of 5 mM sodium decyl sulfate in the incubation mixture brought out reactivity equivalent to that found after delipidation. Completeness of the reaction was verified by comparison with the amount of apo A-I in chromatographic fractions of the total apoprotein of high density lipoprotein. Content (weight %, mean values +- S.D.) of immunoassayable apo A-I was: 62.3 +- 5.9 in high density lipoprotein; 1.7 +- 0.3 in low density lipoprotein; 0.09 +- 0.03 in very low density lipoprotein and 25.0 +- 5.0 in lymph chylomicrons. Concentration in whole serum was 51.4 +- 8.9 mg/dl and 33.6 +- 4.1 mg/dl for female and male rats, respectively (p 1.21 g/ml and <1% in lipoproteins of d<1.063 g/ml

  5. Approaching Artificial Intelligence for Games – the Turing Test revisited

    Directory of Open Access Journals (Sweden)

    Jenny Eriksson Lundström

    2008-07-01

    Full Text Available Today's powerful computers have increasingly more resources available, which can be used for incorporating more sophisticated AI into home applications like computer games. The perhaps obvious way of using AI to enhance the experience of a game is to make the player perceive the computer-controlled entities as intelligent. The traditional idea of how to determine whether a machine can pass as intelligent is the Turing Test. In this paper we show that it is possible and useful to conduct a test adhering to the intention of the original Turing test. We present an empirical study exploring human discrimination of artificial intelligence from the behaviour of a computer-controlled entity used in its specific context and how the behaviour responds to the user's expectations. In our empirical study the context is a real-time strategy computer game and the purpose of the AI is merely to pass as an acceptable opponent. We discuss the results of the empirical study and its implications for AI in computer applications.

  6. Amplify scientific discovery with artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Gil, Yolanda; Greaves, Mark T.; Hendler, James; Hirsch, Hyam

    2014-10-10

    Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automated language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.

  7. Who Are Afraid of Losing Their Jobs to Artificial Intelligence and Robots? Evidence from a Survey

    OpenAIRE

    Morikawa, Masayuki

    2017-01-01

    This study, using original survey data of 10,000 individuals, analyzes the possible impacts of artificial intelligence (AI) and robotics on employment. The first interest of this study is to ascertain, from the viewpoint of workers, what types of worker characteristics are associated with the perception of risk of jobs being replaced by the development of AI and robotics. The second interest is to identify, from the viewpoint of consumers, what types of services are likely to be replaced by A...

  8. Data of evolutionary structure change: 1AIFB-2AI0K [Confc[Archive

    Lifescience Database Archive (English)

    Full Text Available ignment> 0 n> 1AIF n>B 1AI... CA 272 n> 2AI0 n>K ...n>2AI0Kn> VAHPASSTKVD EEE EEEE...1AIFB-2AI0K 1AIF 2AI0 B K EVKLQESGGGLVQPGGSMKLSCVASGFTFNNYWMSWVRQ...SCAASGFTFRNYGMSWVRQTPEKRLEWVAAIS--GNSLYTSYPDSVKGRFTISRDNAKNNLYLQMSSLRSEDTALYFCARH

  9. Intelligent systems

    CERN Document Server

    Irwin, J David

    2011-01-01

    Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system

  10. Intelligent Universe

    Energy Technology Data Exchange (ETDEWEB)

    Hoyle, F

    1983-01-01

    The subject is covered in chapters, entitled: chance and the universe (synthesis of proteins; the primordial soup); the gospel according to Darwin (discussion of Darwin theory of evolution); life did not originate on earth (fossils from space; life in space); the interstellar connection (living dust between the stars; bacteria in space falling to the earth; interplanetary dust); evolution by cosmic control (microorganisms; genetics); why aren't the others here (a cosmic origin of life); after the big bang (big bang and steady state); the information rich universe; what is intelligence up to; the intelligent universe.

  11. Artificial intelligence

    International Nuclear Information System (INIS)

    Perret-Galix, D.

    1992-01-01

    A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of artificial intelligence and related themes. This was reflected in the second international workshop on 'Software Engineering, Artificial Intelligence and Expert Systems in High Energy and Nuclear Physics' which took place from 13-18 January at France Telecom's Agelonde site at La Londe des Maures, Provence. It was the second in a series, the first having been held at Lyon in 1990

  12. Artificial Intelligence and Moral intelligence

    Directory of Open Access Journals (Sweden)

    Laura Pana

    2008-07-01

    Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

  13. Paradox in AI - AI 2.0: The Way to Machine Consciousness

    Science.gov (United States)

    Palensky, Peter; Bruckner, Dietmar; Tmej, Anna; Deutsch, Tobias

    Artificial Intelligence, the big promise of the last millennium, has apparently made its way into our daily lives. Cell phones with speech control, evolutionary computing in data mining or power grids, optimized via neural network, show its applicability in industrial environments. The original expectation of true intelligence and thinking machines lies still ahead of us. Researchers are, however, optimistic as never before. This paper tries to compare the views, challenges and approaches of several disciplines: engineering, psychology, neuroscience, philosophy. It gives a short introduction to Psychoanalysis, discusses the term consciousness, social implications of intelligent machines, related theories, and expectations and shall serve as a starting point for first attempts of combining these diverse thoughts.

  14. Artificial Intelligence and Robotics

    OpenAIRE

    Perez, Javier Andreu; Deligianni, Fani; Ravi, Daniele; Yang, Guang-Zhong

    2018-01-01

    The recent successes of AI have captured the wildest imagination of both the scientific communities and the general public. Robotics and AI amplify human potentials, increase productivity and are moving from simple reasoning towards human-like cognitive abilities. Current AI technologies are used in a set area of applications, ranging from healthcare, manufacturing, transport, energy, to financial services, banking, advertising, management consulting and government agencies. The global AI mar...

  15. Sustainable Technology Analysis of Artificial Intelligence Using Bayesian and Social Network Models

    Directory of Open Access Journals (Sweden)

    Juhwan Kim

    2018-01-01

    Full Text Available Recent developments in artificial intelligence (AI have led to a significant increase in the use of AI technologies. Many experts are researching and developing AI technologies in their respective fields, often submitting papers and patent applications as a result. In particular, owing to the characteristics of the patent system that is used to protect the exclusive rights to registered technology, patent documents contain detailed information on the developed technology. Therefore, in this study, we propose a statistical method for analyzing patent data on AI technology to improve our understanding of sustainable technology in the field of AI. We collect patent documents that are related to AI technology, and then analyze the patent data to identify sustainable AI technology. In our analysis, we develop a statistical method that combines social network analysis and Bayesian modeling. Based on the results of the proposed method, we provide a technological structure that can be applied to understand the sustainability of AI technology. To show how the proposed method can be applied to a practical problem, we apply the technological structure to a case study in order to analyze sustainable AI technology.

  16. Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology.

    Science.gov (United States)

    Tang, An; Tam, Roger; Cadrin-Chênevert, Alexandre; Guest, Will; Chong, Jaron; Barfett, Joseph; Chepelev, Leonid; Cairns, Robyn; Mitchell, J Ross; Cicero, Mark D; Poudrette, Manuel Gaudreau; Jaremko, Jacob L; Reinhold, Caroline; Gallix, Benoit; Gray, Bruce; Geis, Raym

    2018-05-01

    Artificial intelligence (AI) is rapidly moving from an experimental phase to an implementation phase in many fields, including medicine. The combination of improved availability of large datasets, increasing computing power, and advances in learning algorithms has created major performance breakthroughs in the development of AI applications. In the last 5 years, AI techniques known as deep learning have delivered rapidly improving performance in image recognition, caption generation, and speech recognition. Radiology, in particular, is a prime candidate for early adoption of these techniques. It is anticipated that the implementation of AI in radiology over the next decade will significantly improve the quality, value, and depth of radiology's contribution to patient care and population health, and will revolutionize radiologists' workflows. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI working group with the mandate to discuss and deliberate on practice, policy, and patient care issues related to the introduction and implementation of AI in imaging. This white paper provides recommendations for the CAR derived from deliberations between members of the AI working group. This white paper on AI in radiology will inform CAR members and policymakers on key terminology, educational needs of members, research and development, partnerships, potential clinical applications, implementation, structure and governance, role of radiologists, and potential impact of AI on radiology in Canada. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Artificial intelligence: A joint narrative on potential use in pediatric stem and immune cell therapies and regenerative medicine.

    Science.gov (United States)

    Sniecinski, Irena; Seghatchian, Jerard

    2018-05-09

    Artificial Intelligence (AI) reflects the intelligence exhibited by machines and software. It is a highly desirable academic field of many current fields of studies. Leading AI researchers describe the field as "the study and design of intelligent agents". McCarthy invented this term in 1955 and defined it as "the science and engineering of making intelligent machines". The central goals of AI research are reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. In fact the multidisplinary AI field is considered to be rather interdisciplinary covering numerous number of sciences and professions, including computer science, psychology, linguistics, philosophy and neurosciences. The field was founded on the claim that a central intellectual property of humans, intelligence-the sapience of Homo Sapiens "can be so precisely described that a machine can be made to simulate it". This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence. Artificial Intelligence has been the subject of tremendous optimism but has also suffered stunning setbacks. The goal of this narrative is to review the potential use of AI approaches and their integration into pediatric cellular therapies and regenerative medicine. Emphasis is placed on recognition and application of AI techniques in the development of predictive models for personalized treatments with engineered stem cells, immune cells and regenerated tissues in adults and children. These intelligent machines could dissect the whole genome and isolate the immune particularities of individual patient's disease in a matter of minutes and create the treatment that is customized to patient's genetic specificity and immune system capability. AI techniques could be used for optimization of clinical trials of innovative stem cell and gene therapies in pediatric patients

  18. Experiments with microcomputer-based artificial intelligence environments

    Science.gov (United States)

    Summers, E.G.; MacDonald, R.A.

    1988-01-01

    The U.S. Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the "artificial intelligence computer," and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently, inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Gold Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming. ?? 1988 International Association for Mathematical Geology.

  19. Applications of artificial intelligence to mission planning

    Science.gov (United States)

    Ford, Donnie R.; Rogers, John S.; Floyd, Stephen A.

    1990-01-01

    The scheduling problem facing NASA-Marshall mission planning is extremely difficult for several reasons. The most critical factor is the computational complexity involved in developing a schedule. The size of the search space is large along some dimensions and infinite along others. It is because of this and other difficulties that many of the conventional operation research techniques are not feasible or inadequate to solve the problems by themselves. Therefore, the purpose is to examine various artificial intelligence (AI) techniques to assist conventional techniques or to replace them. The specific tasks performed were as follows: (1) to identify mission planning applications for object oriented and rule based programming; (2) to investigate interfacing AI dedicated hardware (Lisp machines) to VAX hardware; (3) to demonstrate how Lisp may be called from within FORTRAN programs; (4) to investigate and report on programming techniques used in some commercial AI shells, such as Knowledge Engineering Environment (KEE); and (5) to study and report on algorithmic methods to reduce complexity as related to AI techniques.

  20. Artificial intelligence, physiological genomics, and precision medicine.

    Science.gov (United States)

    Williams, Anna Marie; Liu, Yong; Regner, Kevin R; Jotterand, Fabrice; Liu, Pengyuan; Liang, Mingyu

    2018-04-01

    Big data are a major driver in the development of precision medicine. Efficient analysis methods are needed to transform big data into clinically-actionable knowledge. To accomplish this, many researchers are turning toward machine learning (ML), an approach of artificial intelligence (AI) that utilizes modern algorithms to give computers the ability to learn. Much of the effort to advance ML for precision medicine has been focused on the development and implementation of algorithms and the generation of ever larger quantities of genomic sequence data and electronic health records. However, relevance and accuracy of the data are as important as quantity of data in the advancement of ML for precision medicine. For common diseases, physiological genomic readouts in disease-applicable tissues may be an effective surrogate to measure the effect of genetic and environmental factors and their interactions that underlie disease development and progression. Disease-applicable tissue may be difficult to obtain, but there are important exceptions such as kidney needle biopsy specimens. As AI continues to advance, new analytical approaches, including those that go beyond data correlation, need to be developed and ethical issues of AI need to be addressed. Physiological genomic readouts in disease-relevant tissues, combined with advanced AI, can be a powerful approach for precision medicine for common diseases.

  1. Fourth Conference on Artificial Intelligence for Space Applications

    Science.gov (United States)

    Odell, Stephen L. (Compiler); Denton, Judith S. (Compiler); Vereen, Mary (Compiler)

    1988-01-01

    Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming.

  2. Modeling of steam distillation mechanism during steam injection process using artificial intelligence.

    Science.gov (United States)

    Daryasafar, Amin; Ahadi, Arash; Kharrat, Riyaz

    2014-01-01

    Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods.

  3. Modeling of Steam Distillation Mechanism during Steam Injection Process Using Artificial Intelligence

    Science.gov (United States)

    Ahadi, Arash; Kharrat, Riyaz

    2014-01-01

    Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods. PMID:24883365

  4. Plant intelligence

    Science.gov (United States)

    Lipavská, Helena; Žárský, Viktor

    2009-01-01

    The concept of plant intelligence, as proposed by Anthony Trewavas, has raised considerable discussion. However, plant intelligence remains loosely defined; often it is either perceived as practically synonymous to Darwinian fitness, or reduced to a mere decorative metaphor. A more strict view can be taken, emphasizing necessary prerequisites such as memory and learning, which requires clarifying the definition of memory itself. To qualify as memories, traces of past events have to be not only stored, but also actively accessed. We propose a criterion for eliminating false candidates of possible plant intelligence phenomena in this stricter sense: an “intelligent” behavior must involve a component that can be approximated by a plausible algorithmic model involving recourse to stored information about past states of the individual or its environment. Re-evaluation of previously presented examples of plant intelligence shows that only some of them pass our test. “You were hurt?” Kumiko said, looking at the scar. Sally looked down. “Yeah.” “Why didn't you have it removed?” “Sometimes it's good to remember.” “Being hurt?” “Being stupid.”—(W. Gibson: Mona Lisa Overdrive) PMID:19816094

  5. Speech Intelligibility

    Science.gov (United States)

    Brand, Thomas

    Speech intelligibility (SI) is important for different fields of research, engineering and diagnostics in order to quantify very different phenomena like the quality of recordings, communication and playback devices, the reverberation of auditoria, characteristics of hearing impairment, benefit using hearing aids or combinations of these things.

  6. Continuous surveillance of transformers using artificial intelligence methods; Surveillance continue des transformateurs: application des methodes d'intelligence artificielle

    Energy Technology Data Exchange (ETDEWEB)

    Schenk, A.; Germond, A. [Ecole Polytechnique Federale de Lausanne, Lausanne (Switzerland); Boss, P.; Lorin, P. [ABB Secheron SA, Geneve (Switzerland)

    2000-07-01

    The article describes a new method for the continuous surveillance of power transformers based on the application of artificial intelligence (AI) techniques. An experimental pilot project on a specially equipped, strategically important power transformer is described. Traditional surveillance methods and the use of mathematical models for the prediction of faults are described. The article describes the monitoring equipment used in the pilot project and the AI principles such as self-organising maps that are applied. The results obtained from the pilot project and methods for their graphical representation are discussed.

  7. Artificial intelligence and engineering curricula - are changes needed?

    International Nuclear Information System (INIS)

    Jenkins, J.P.

    1988-01-01

    The purpose of this paper is to identify the expected impact of artificial intelligence (AI) on curricula and training courses. From this examination, new elements are proposed for the academic preparation and training of engineers who will evaluate and use these systems and capabilities. Artificial intelligence, from an operational viewpoint, begins with a set of rules governing the operation of logic, implemented via computer software and userware. These systems apply logic and experience to handling problems in an intelligent approach, especially when the number of alternatives to problem solution is beyond the scope of the human user. Usually, AI applications take the form of expert systems. An expert system embodies in the computer the knowledge-based component of an expert, such as domain knowledge and reasoning techniques, in such a form that the system can offer intelligent advice and, on demand, justify its own line of reasoning. Two languages predominate, LISP and Prolog. The AI user may interface with the knowledge base via one of these languages or by means of menu displays, cursor selections, or other conventional user interface methods

  8. Joint application of AI techniques, PRA and disturbance analysis methodology to problems in the maintenance and design of nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Okrent, D.

    1989-03-01

    This final report summarizes the accomplishments of a two year research project entitled Joint Application of Artificial Intelligence Techniques, Probabilistic Risk Analysis, and Disturbance Analysis Methodology to Problems in the Maintenance and Design of Nuclear Power Plants. The objective of this project is to develop and apply appropriate combinations of techniques from artificial intelligence, (AI), reliability and risk analysis and disturbance analysis to well-defined programmatic problems of nuclear power plants. Reactor operations issues were added to those of design and maintenance as the project progressed.

  9. Joint application of AI techniques, PRA and disturbance analysis methodology to problems in the maintenance and design of nuclear power plants. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Okrent, D.

    1989-03-01

    This final report summarizes the accomplishments of a two year research project entitled ``Joint Application of Artificial Intelligence Techniques, Probabilistic Risk Analysis, and Disturbance Analysis Methodology to Problems in the Maintenance and Design of Nuclear Power Plants. The objective of this project is to develop and apply appropriate combinations of techniques from artificial intelligence, (AI), reliability and risk analysis and disturbance analysis to well-defined programmatic problems of nuclear power plants. Reactor operations issues were added to those of design and maintenance as the project progressed.

  10. Joint application of AI techniques, PRA and disturbance analysis methodology to problems in the maintenance and design of nuclear power plants

    International Nuclear Information System (INIS)

    Okrent, D.

    1989-01-01

    This final report summarizes the accomplishments of a two year research project entitled ''Joint Application of Artificial Intelligence Techniques, Probabilistic Risk Analysis, and Disturbance Analysis Methodology to Problems in the Maintenance and Design of Nuclear Power Plants. The objective of this project is to develop and apply appropriate combinations of techniques from artificial intelligence, (AI), reliability and risk analysis and disturbance analysis to well-defined programmatic problems of nuclear power plants. Reactor operations issues were added to those of design and maintenance as the project progressed

  11. Dicty_cDB: FC-AI12 [Dicty_cDB

    Lifescience Database Archive (English)

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  12. Dicty_cDB: FC-AI07 [Dicty_cDB

    Lifescience Database Archive (English)

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  13. Dicty_cDB: FC-AI19 [Dicty_cDB

    Lifescience Database Archive (English)

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  14. Dicty_cDB: FC-AI14 [Dicty_cDB

    Lifescience Database Archive (English)

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  15. Dicty_cDB: FC-AI15 [Dicty_cDB

    Lifescience Database Archive (English)

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  16. Dicty_cDB: FC-AI24 [Dicty_cDB

    Lifescience Database Archive (English)

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  17. Dicty_cDB: FC-AI06 [Dicty_cDB

    Lifescience Database Archive (English)

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  18. Dicty_cDB: FC-AI09 [Dicty_cDB

    Lifescience Database Archive (English)

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  19. Dicty_cDB: FC-AI22 [Dicty_cDB

    Lifescience Database Archive (English)

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  20. Dicty_cDB: FC-AI08 [Dicty_cDB

    Lifescience Database Archive (English)

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