Nash equilibrium

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In game theory, Nash equilibrium (named after John Forbes Nash, who proposed it) is a solution concept of a game involving two or more players, in which each player is assumed to know the equilibrium strategies of the other players, and no player has anything to gain by changing only his own strategy unilaterally. (Wikipedia.org)






Conferences related to Nash equilibrium

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2016 IEEE 55th IEEE Conference on Decision and Control (CDC)

The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.

  • 2014 IEEE 53rd Annual Conference on Decision and Control (CDC)

    Largest annual conference in control theory and its applications. Areas covered all applied math, communication, control, aerospace, biology, etc.

  • 2013 IEEE 52nd Annual Conference on Decision and Control (CDC)

    The 52nd IEEE Conference on Decision and Control will be held Tuesday through Friday, December 10-13, 2013 at the Congress Centre in Firenze, Italy. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss the latest advancements of the discipline, shape its future directions, and promote its diffusion among the scientific community at large. The 52nd CDC will feature the presentation of contributed and invited papers, as well as tutorial sessions and workshops. The CDC is hosted by the IEEE Control Systems Society (CSS), and is organized in cooperation with the Society for Industrial and Applied Mathematics (SIAM), the Institute for Operations Research and the Management Sciences (INFORMS), the Japanese Society for Instrument and Control Engineers (SICE), and the European Union Control Association (EUCA).

  • 2012 IEEE 51st Annual Conference on Decision and Control (CDC)

    The conference discusses advances in theory, design and application of control systems. Papers will highlight the latest knowledge, exploratory developments, and practical applications in all aspects of the control systems from analysis and design through simulation and hardware. Its scope shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organiz

  • 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011)

    This conference is dedicated to the advancement of the theory and practice of systems and control, bringing together an international community of researchers and practitioners to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.

  • 2010 49th IEEE Conference on Decision and Control (CDC)

    Theory and applications of control theory and control systems technology

  • 2009 Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC)

    This conference is dedicated to the advancement of the theory and practice of systems and control, bringing together an international community of researchers and practitioners to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.

  • 2008 47th IEEE Conference on Decision and Control (CDC)

    The CDC is the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control, bringing together an international community of researchers and practitioners to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.

  • 2007 46th IEEE Conference on Decision and Control (CDC)


2013 6th International Conference on Information Management, Innovation Management and Industrial Engineering (ICIII)

This conference provides an idea-exchange and discussion platform for researchers and practitioners interested in information management, innovation management and industrial engineering. The topics will arrange from the technology management theories to the management practice methods and technology.


2012 IEEE International Conference on Power System Technology - (POWERCON 2012)

The theme of this conference is Towards Smarter Resilient and Economic Power Systems . This is topical in the context of emerging trends of Smart Grids; resilience of electricity infrastructure to recent earthquakes, floods, nuclear-meltdown in the Asia-Pacifc region; and, trends towards Emission Trading Scheme and increased participation of private capital markets into electricity generation. A flavour of this theme in the context of New Zealand will be highlight to all our international participants.

  • 2010 International Conference on Power System Technology - (POWERCON 2010)

    distributed generation, renewables generation and its integration into power systems, UHV transmission, wide area interconnections, development of smart grid, energy storage, energy saving and emission reduction.

  • 2008 Joint International Conference on Power System Technology (POWERCON) and IEEE Power India Conference

    State-of-the-art lectures and tutorials by experts, and papers by practicing Engineers and Researchers will be presented in the areas of Power System Analysis , Computing and Economics, Modelling and Dynamic Performance, FACTS and HVDC, Restructured Energy Systems, Control and Operation, Communication and Control, Relaying and Protection, Energy Management System and Distribution Automation, Applications of Power Electronics and Power Quality, Distributed Generation & Renewable Energy Sources

  • 2006 International Conference on Power System Technology - (POWERCON 2006)


2009 International Conference on Game Theory for Networks (GameNets 2009)

The conference will bring together researchers who apply game theory to analyze, design, and assess the performance of networks. It will highlight synergies between various related research areas and encourage discussions regarding the benefits and limitations of game theory as a performance assessment and design tool for networks.



Periodicals related to Nash equilibrium

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Power Systems, IEEE Transactions on

Requirements, planning, analysis, reliability, operation, and economics of electrical generating, transmission, and distribution systems for industrial, commercial, public, and domestic consumption.


Selected Areas in Communications, IEEE Journal on

All telecommunications, including telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space, and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; communication theory; and wireless communications.



Most published Xplore authors for Nash equilibrium

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Xplore Articles related to Nash equilibrium

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Resource Selection Game with Cost Constraint Oriented to Microeconomic Data Mining

Jin Li; WeiYi Liu; Kun Yue 2009 International Conference on Artificial Intelligence and Computational Intelligence, 2009

Game theory, which has provided a powerful tool to describe strategic interaction in economic environment, is a mathematical model of competitions among individual decision makers. In this paper, we present a study on combining game theory and microeconomic data mining by introducing the concept of resource selection game analysis. We present a universal multiple resources selection model, where each resource ...


On degenerate and non-degenerate correspondences of differential games with a feedback Nash equilibrium

D. W. K. Yeung Proceedings of 32nd IEEE Conference on Decision and Control, 1993

In differential games, open-loop Nash equilibrium and feedback Nash equilibrium (FNE) are, in general, different. Only in the case of a degenerate FNE do these equilibria coincide. So far, only a countable number of games with a degenerate FNE or a non-degenerate FNE have been found. In this paper, the author shows that (i) a class of games with a ...


Fuzzy Nash Equilibriums in Crisp and Fuzzy Games

Alireza Chakeri; Farid Sheikholeslam IEEE Transactions on Fuzzy Systems, 2013

In this paper, we introduce fuzzy Nash equilibrium to determine a graded representation of Nash equilibriums in crisp and fuzzy games. This interpretation shows the distribution of equilibriums in the matrix form of a game and handles uncertainties in payoffs. In addition, a new method to rank fuzzy values with the user's viewpoint is investigated. By this means, the definition ...


A Game-Theoretic Social Model for Multiagent Systems

Wynn C. Stirling 2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013

A collective of autonomous decision-making agents that is tasked to function cooperatively must take into account the effects of their actions on other agents as well as themselves. Although game theory provides a framework within which to achieve rational behavior, classical approaches are limited in their ability to account for sophisticated social relationships such as cooperation, altruism, and negotiation, since ...


Using game theory to analyze wireless ad hoc networks

V. Srivastava; J. Neel; A. B. Mackenzie; R. Menon; L. A. Dasilva; J. E. Hicks; J. H. Reed; R. P. Gilles IEEE Communications Surveys & Tutorials, 2005

First Page of the Article ![](/xploreAssets/images/absImages/01593279.png)


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Educational Resources on Nash equilibrium

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eLearning

Resource Selection Game with Cost Constraint Oriented to Microeconomic Data Mining

Jin Li; WeiYi Liu; Kun Yue 2009 International Conference on Artificial Intelligence and Computational Intelligence, 2009

Game theory, which has provided a powerful tool to describe strategic interaction in economic environment, is a mathematical model of competitions among individual decision makers. In this paper, we present a study on combining game theory and microeconomic data mining by introducing the concept of resource selection game analysis. We present a universal multiple resources selection model, where each resource ...


On degenerate and non-degenerate correspondences of differential games with a feedback Nash equilibrium

D. W. K. Yeung Proceedings of 32nd IEEE Conference on Decision and Control, 1993

In differential games, open-loop Nash equilibrium and feedback Nash equilibrium (FNE) are, in general, different. Only in the case of a degenerate FNE do these equilibria coincide. So far, only a countable number of games with a degenerate FNE or a non-degenerate FNE have been found. In this paper, the author shows that (i) a class of games with a ...


Fuzzy Nash Equilibriums in Crisp and Fuzzy Games

Alireza Chakeri; Farid Sheikholeslam IEEE Transactions on Fuzzy Systems, 2013

In this paper, we introduce fuzzy Nash equilibrium to determine a graded representation of Nash equilibriums in crisp and fuzzy games. This interpretation shows the distribution of equilibriums in the matrix form of a game and handles uncertainties in payoffs. In addition, a new method to rank fuzzy values with the user's viewpoint is investigated. By this means, the definition ...


A Game-Theoretic Social Model for Multiagent Systems

Wynn C. Stirling 2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013

A collective of autonomous decision-making agents that is tasked to function cooperatively must take into account the effects of their actions on other agents as well as themselves. Although game theory provides a framework within which to achieve rational behavior, classical approaches are limited in their ability to account for sophisticated social relationships such as cooperation, altruism, and negotiation, since ...


Using game theory to analyze wireless ad hoc networks

V. Srivastava; J. Neel; A. B. Mackenzie; R. Menon; L. A. Dasilva; J. E. Hicks; J. H. Reed; R. P. Gilles IEEE Communications Surveys & Tutorials, 2005

First Page of the Article ![](/xploreAssets/images/absImages/01593279.png)


More eLearning Resources

IEEE-USA E-Books

  • Plant Reliability in Monopolies and Duopolies: A Comparison of Market Outcomes with Socially Optimal Levels

    This chapter contains sections titled: Introduction Modeling Framework Profit Maximizing Outcome of a Monopolistic Generator Nash Equilibrium in a Duopolistic Market Structure Social Optimum Comparison of Equilibria and Discussion Asymmetric Maintenance Policies Conclusion Acknowledgment Bibliography

  • No title

    Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self- interested agents. Chapter 7 provides a s ort introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.

  • A Small World Threshold for Economic Network Formation

    We introduce a game-theoretic model for network formation inspired by earlier stochastic models that mix localized and long-distance connectivity. In this model, players may purchase edges at distance d at a cost of dα, and wish to minimize the sum of their edge purchases and their average distance to other players. In this model, we show there is a striking "small world" threshold phenomenon: in two dimensions, if α < 2 then every Nash equilibrium results in a network of constant diameter (independent of network size), and if α > 2 then every Nash equilibrium results in a network whose diameter grows as a root of the network size, and thus is unbounded. We contrast our results with those of Kleinberg [8] in a stochastic model, and empirically investigate the "navigability" of equilibrium networks. Our theoretical results all generalize to higher dimensions.

  • Algorithmic Game Theory and Applications

    Methods from game theory and mechanism design have been proven to be a powerful mathematical tool in order to understand, control, and efficiently design dynamic, complex networks, such as the Internet. Game theory provides a good starting point for computer scientists to understand selfish rational behavior of complex networks with many agents. Such a scenario is readily modeled using game theory techniques, in which players with potentially different goals participate under a common setting with well prescribed interactions. The Nash equilibrium stands out as the predominant concept of rationality in noncooperative settings. Thus, game theory and its notions of equilibria provide a rich framework for modeling the behavior of selfish agents in these kinds of distributed and networked environments and offering mechanisms to achieve efficient and desirable global outcomes despite selfish behavior. The most important algorithmic solutions and advances achieved through game theory are reviewed.



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