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Convergence To Equilibrium In Multi Stage Games
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Book Synopsis Distributed Optimization-Based Control of Multi-Agent Networks in Complex Environments by : Minghui Zhu
Download or read book Distributed Optimization-Based Control of Multi-Agent Networks in Complex Environments written by Minghui Zhu and published by Springer. This book was released on 2015-06-11 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a concise and in-depth exposition of specific algorithmic solutions for distributed optimization based control of multi-agent networks and their performance analysis. It synthesizes and analyzes distributed strategies for three collaborative tasks: distributed cooperative optimization, mobile sensor deployment and multi-vehicle formation control. The book integrates miscellaneous ideas and tools from dynamic systems, control theory, graph theory, optimization, game theory and Markov chains to address the particular challenges introduced by such complexities in the environment as topological dynamics, environmental uncertainties, and potential cyber-attack by human adversaries. The book is written for first- or second-year graduate students in a variety of engineering disciplines, including control, robotics, decision-making, optimization and algorithms and with backgrounds in aerospace engineering, computer science, electrical engineering, mechanical engineering and operations research. Researchers in these areas may also find the book useful as a reference.
Book Synopsis Adaptive Agents and Multi-Agent Systems II by : Daniel Kudenko
Download or read book Adaptive Agents and Multi-Agent Systems II written by Daniel Kudenko and published by Springer. This book was released on 2005-02-18 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.
Book Synopsis Handbook of Industrial Organization by : Mark Armstrong
Download or read book Handbook of Industrial Organization written by Mark Armstrong and published by Elsevier. This book was released on 2007-10-05 with total page 943 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is Volume 3 of the Handbook of Industrial Organization series (HIO). Volumes 1 & 2 published simultaneously in 1989 and many of the chapters were widely cited and appeared on graduate reading lists. Since the first volumes published, the field of industrial organization has continued to evolve and this volume fills the gaps. While the first two volumes of HIO contain much more discussion of the theoretical literature than of the empirical literature, it was representative of the field at that time. Since then, the empirical literature has flourished, while the theoretical literature has continued to grow, and this new volume reflects that change of emphasis.Thie volume is an excellent reference and teaching supplement for industrial organization or industrial economics, the microeconomics field that focuses on business behavior and its implications for both market structures and processes, and for related public policies.*Part of the renowned Handbooks in Economics series*Chapters are contributed by some of the leading experts in their fields*A source, reference and teaching supplement for industrial organizations or industrial economists
Book Synopsis Twenty Lectures on Algorithmic Game Theory by : Tim Roughgarden
Download or read book Twenty Lectures on Algorithmic Game Theory written by Tim Roughgarden and published by Cambridge University Press. This book was released on 2016-08-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.
Book Synopsis Learning and Adaption in Multi-Agent Systems by : Karl Tuyls
Download or read book Learning and Adaption in Multi-Agent Systems written by Karl Tuyls and published by Springer Science & Business Media. This book was released on 2006-04-10 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Learning and Adaption in Multi-Agent Systems, LAMAS 2005, held in The Netherlands, in July 2005, as an associated event of AAMAS 2005. The 13 revised papers presented together with two invited talks were carefully reviewed and selected from the lectures given at the workshop.
Book Synopsis The Master Equation and the Convergence Problem in Mean Field Games by : Pierre Cardaliaguet
Download or read book The Master Equation and the Convergence Problem in Mean Field Games written by Pierre Cardaliaguet and published by Princeton University Press. This book was released on 2019-08-13 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the latest advances in the theory of mean field games, which are optimal control problems with a continuum of players, each of them interacting with the whole statistical distribution of a population. While it originated in economics, this theory now has applications in areas as diverse as mathematical finance, crowd phenomena, epidemiology, and cybersecurity. Because mean field games concern the interactions of infinitely many players in an optimal control framework, one expects them to appear as the limit for Nash equilibria of differential games with finitely many players as the number of players tends to infinity. This book rigorously establishes this convergence, which has been an open problem until now. The limit of the system associated with differential games with finitely many players is described by the so-called master equation, a nonlocal transport equation in the space of measures. After defining a suitable notion of differentiability in the space of measures, the authors provide a complete self-contained analysis of the master equation. Their analysis includes the case of common noise problems in which all the players are affected by a common Brownian motion. They then go on to explain how to use the master equation to prove the mean field limit. This groundbreaking book presents two important new results in mean field games that contribute to a unified theoretical framework for this exciting and fast-developing area of mathematics.
Book Synopsis Nonlinear Output Regulation by : Jie Huang
Download or read book Nonlinear Output Regulation written by Jie Huang and published by SIAM. This book was released on 2004-01-01 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Output Regulation: Theory and Applications provides a comprehensive and in-depth treatment of the nonlinear output regulation problem. It contains up-to-date research results and algorithms and tools for approaching and solving the output regulation problem and related problems, such as robust stabilization of nonlinear systems. Output regulation is a general mathematical formulation of many control problems encountered in daily life including cruise control of automobiles, landing and takeoff of aircraft, manipulation of robot arms, orbiting of satellites, and speed regulation of motors. The book provides a self-contained treatment starting with an introduction to the linear output regulation problem and a review of the fundamental nonlinear control theory. The author's presentation strikes a balance between the theoretical foundation of the problem and the practical applications of the theory. The book is accompanied by many examples, including practical case studies with numerical simulations based on MATLAB/SIMULINK. Audience: graduate students, professors, and researchers in applied mathematics, electrical engineering, mechanical engineering, and aerospace engineering. The book can be used in a graduate-level control systems course as well as by control design engineers in industry.
Book Synopsis Innovations in Multi-Agent Systems and Application – 1 by : Dipti Srinivasan
Download or read book Innovations in Multi-Agent Systems and Application – 1 written by Dipti Srinivasan and published by Springer Science & Business Media. This book was released on 2010-08-10 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of multi-agent systems and several applications that have been developed for real-world problems. Multi-agent systems is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexities arising from their interactions. Multi-agent systems allow the subproblems of a constraint satisfaction problem to be subcontracted to different problem solving agents with their own interest and goals. This increases the speed, creates parallelism and reduces the risk of system collapse on a single point of failure. Different multi-agent architectures, that are tailor-made for a specific application are possible. They are able to synergistically combine the various computational intelligent techniques for attaining a superior performance. This gives an opportunity for bringing the advantages of various techniques into a single framework. It also provides the freedom to model the behavior of the system to be as competitive or coordinating, each having its own advantages and disadvantages.
Book Synopsis Multi-Agent Machine Learning by : H. M. Schwartz
Download or read book Multi-Agent Machine Learning written by H. M. Schwartz and published by John Wiley & Sons. This book was released on 2014-08-26 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD learning with eligibility traces. Chapter 3 discusses two player games including two player matrix games with both pure and mixed strategies. Numerous algorithms and examples are presented. Chapter 4 covers learning in multi-player games, stochastic games, and Markov games, focusing on learning multi-player grid games—two player grid games, Q-learning, and Nash Q-learning. Chapter 5 discusses differential games, including multi player differential games, actor critique structure, adaptive fuzzy control and fuzzy interference systems, the evader pursuit game, and the defending a territory games. Chapter 6 discusses new ideas on learning within robotic swarms and the innovative idea of the evolution of personality traits. • Framework for understanding a variety of methods and approaches in multi-agent machine learning. • Discusses methods of reinforcement learning such as a number of forms of multi-agent Q-learning • Applicable to research professors and graduate students studying electrical and computer engineering, computer science, and mechanical and aerospace engineering
Book Synopsis Multi-Level Decision Making by : Guangquan Zhang
Download or read book Multi-Level Decision Making written by Guangquan Zhang and published by Springer. This book was released on 2015-02-07 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.
Book Synopsis Reinforcement Learning by : Marco Wiering
Download or read book Reinforcement Learning written by Marco Wiering and published by Springer Science & Business Media. This book was released on 2012-03-05 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.
Book Synopsis Decentralised Reinforcement Learning in Markov Games by : Peter Vrancx
Download or read book Decentralised Reinforcement Learning in Markov Games written by Peter Vrancx and published by ASP / VUBPRESS / UPA. This book was released on 2011 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing a new approach to multiagent reinforcement learning and distributed artificial intelligence, this guide shows how classical game theory can be used to compose basic learning units. This approach to creating agents has the advantage of leading to powerful, yet intuitively simple, algorithms that can be analyzed. The setup is demonstrated here in a number of different settings, with a detailed analysis of agent learning behaviors provided for each. A review of required background materials from game theory and reinforcement learning is also provided, along with an overview of related multiagent learning methods.
Book Synopsis Repeated Games with Incomplete Information by : Robert J. Aumann
Download or read book Repeated Games with Incomplete Information written by Robert J. Aumann and published by MIT Press. This book was released on 1995 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: The basic model studied throughout the book is one in which players ignorant about the game being played must learn what they can from the actions of the others.
Book Synopsis Robust Autonomous Guidance by : Alberto Isidori
Download or read book Robust Autonomous Guidance written by Alberto Isidori and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the reviews: "The book is an excellent combination of theory and real-world applications. Each application not only demonstrates the power of the theoretical results but also is important on its own behalf." IEEE Control Systems Magazine
Book Synopsis Some Topics in Two-person Games by : T. Parthasarathy
Download or read book Some Topics in Two-person Games written by T. Parthasarathy and published by Elsevier Publishing Company. This book was released on 1971 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Strategic Learning and Its Limits by : H. Peyton Young
Download or read book Strategic Learning and Its Limits written by H. Peyton Young and published by Oxford University Press, USA. This book was released on 2004 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Table of contents
Book Synopsis Evolutionary Game Dynamics by : American Mathematical Society. Short Course
Download or read book Evolutionary Game Dynamics written by American Mathematical Society. Short Course and published by American Mathematical Soc.. This book was released on 2011-10-27 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is based on lectures delivered at the 2011 AMS Short Course on Evolutionary Game Dynamics, held January 4-5, 2011 in New Orleans, Louisiana. Evolutionary game theory studies basic types of social interactions in populations of players. It combines the strategic viewpoint of classical game theory (independent rational players trying to outguess each other) with population dynamics (successful strategies increase their frequencies). A substantial part of the appeal of evolutionary game theory comes from its highly diverse applications such as social dilemmas, the evolution of language, or mating behaviour in animals. Moreover, its methods are becoming increasingly popular in computer science, engineering, and control theory. They help to design and control multi-agent systems, often with a large number of agents (for instance, when routing drivers over highway networks or data packets over the Internet). While these fields have traditionally used a top down approach by directly controlling the behaviour of each agent in the system, attention has recently turned to an indirect approach allowing the agents to function independently while providing incentives that lead them to behave in the desired way. Instead of the traditional assumption of equilibrium behaviour, researchers opt increasingly for the evolutionary paradigm and consider the dynamics of behaviour in populations of agents employing simple, myopic decision rules.
