A Course In Stochastic Game Theory
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Author | : Eilon Solan |
Publisher | : Cambridge University Press |
Total Pages | : 279 |
Release | : 2022-05-26 |
Genre | : Business & Economics |
ISBN | : 1316516334 |
This book for beginning graduate students presents a course on stochastic games and the mathematical methods used in their analysis.
Author | : Michael Maschler |
Publisher | : Cambridge University Press |
Total Pages | : 1053 |
Release | : 2020-06-25 |
Genre | : Business & Economics |
ISBN | : 1108493459 |
This new edition is unparalleled in breadth of coverage, thoroughness of technical explanations and number of worked examples.
Author | : Sylvain Sorin |
Publisher | : Springer Science & Business Media |
Total Pages | : 228 |
Release | : 2002-03-07 |
Genre | : Business & Economics |
ISBN | : 9783540430285 |
This volume aims to present the basic results in the theory of two-person zero-sum repeated games including stochastic games and repeated games with incomplete information. It is intended for graduate students with no previous knowledge of the field.
Author | : Kevin Gebser |
Publisher | : Springer Nature |
Total Pages | : 88 |
Release | : 2022-05-31 |
Genre | : Computers |
ISBN | : 3031015452 |
Game theory is the mathematical study of interaction among independent, self-interested agents. The audience for game theory has grown dramatically in recent years, and now spans disciplines as diverse as political science, biology, psychology, economics, linguistics, sociology, and computer science, among others. What has been missing is a relatively short introduction to the field covering the common basis that anyone with a professional interest in game theory is likely to require. Such a text would minimize notation, ruthlessly focus on essentials, and yet not sacrifice rigor. This Synthesis Lecture aims to fill this gap by providing a concise and accessible introduction to the field. It covers the main classes of games, their representations, and the main concepts used to analyze them.
Author | : Michael Ummels |
Publisher | : Amsterdam University Press |
Total Pages | : 174 |
Release | : 2010-12 |
Genre | : Computers |
ISBN | : 9085550408 |
Stochastic games provide a versatile model for reactive systems that are affected by random events. This dissertation advances the algorithmic theory of stochastic games to incorporate multiple players, whose objectives are not necessarily conflicting. The basis of this work is a comprehensive complexity-theoretic analysis of the standard game-theoretic solution concepts in the context of stochastic games over a finite state space. One main result is that the constrained existence of a Nash equilibrium becomes undecidable in this setting. This impossibility result is accompanied by several positive results, including efficient algorithms for natural special cases.
Author | : American Mathematical Society. Short Course |
Publisher | : American Mathematical Soc. |
Total Pages | : 186 |
Release | : 2011-10-27 |
Genre | : Mathematics |
ISBN | : 0821853260 |
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.
Author | : Thomas S Ferguson |
Publisher | : World Scientific |
Total Pages | : 409 |
Release | : 2020-07-20 |
Genre | : Mathematics |
ISBN | : 9813227370 |
Game theory is a fascinating subject. We all know many entertaining games, such as chess, poker, tic-tac-toe, bridge, baseball, computer games — the list is quite varied and almost endless. In addition, there is a vast area of economic games, discussed in Myerson (1991) and Kreps (1990), and the related political games [Ordeshook (1986), Shubik (1982), and Taylor (1995)]. The competition between firms, the conflict between management and labor, the fight to get bills through congress, the power of the judiciary, war and peace negotiations between countries, and so on, all provide examples of games in action. There are also psychological games played on a personal level, where the weapons are words, and the payoffs are good or bad feelings [Berne (1964)]. There are biological games, the competition between species, where natural selection can be modeled as a game played between genes [Smith (1982)]. There is a connection between game theory and the mathematical areas of logic and computer science. One may view theoretical statistics as a two-person game in which nature takes the role of one of the players, as in Blackwell and Girshick (1954) and Ferguson (1968).Games are characterized by a number of players or decision makers who interact, possibly threaten each other and form coalitions, take actions under uncertain conditions, and finally receive some benefit or reward or possibly some punishment or monetary loss. In this text, we present various mathematical models of games and study the phenomena that arise. In some cases, we will be able to suggest what courses of action should be taken by the players. In others, we hope simply to be able to understand what is happening in order to make better predictions about the future.
Author | : Eilon Solan |
Publisher | : Cambridge University Press |
Total Pages | : 280 |
Release | : 2022-05-26 |
Genre | : Mathematics |
ISBN | : 1009034340 |
Stochastic games have an element of chance: the state of the next round is determined probabilistically depending upon players' actions and the current state. Successful players need to balance the need for short-term payoffs while ensuring future opportunities remain high. The various techniques needed to analyze these often highly non-trivial games are a showcase of attractive mathematics, including methods from probability, differential equations, algebra, and combinatorics. This book presents a course on the theory of stochastic games going from the basics through to topics of modern research, focusing on conceptual clarity over complete generality. Each of its chapters introduces a new mathematical tool – including contracting mappings, semi-algebraic sets, infinite orbits, and Ramsey's theorem, among others – before discussing the game-theoretic results they can be used to obtain. The author assumes no more than a basic undergraduate curriculum and illustrates the theory with numerous examples and exercises, with solutions available online.
Author | : Olivier Sigaud |
Publisher | : John Wiley & Sons |
Total Pages | : 367 |
Release | : 2013-03-04 |
Genre | : Technology & Engineering |
ISBN | : 1118620100 |
Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as reinforcement learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in artificial intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, reinforcement learning, partially observable MDPs, Markov games and the use of non-classical criteria). It then presents more advanced research trends in the field and gives some concrete examples using illustrative real life applications.
Author | : Drew Fudenberg |
Publisher | : MIT Press |
Total Pages | : 304 |
Release | : 1998 |
Genre | : Business & Economics |
ISBN | : 9780262061940 |
This work explains that equilibrium is the long-run outcome of a process in which non-fully rational players search for optimality over time. The models they e×plore provide a foundation for equilibrium theory and suggest ways for economists to evaluate and modify traditional equilibrium concepts.