Evolutionary game dynamics : American Mathematical Society Short Course, January 45, 2011, New Orleans, Louisiana
 Responsibility
 Karl Sigmund, editor.
 Language
 English.
 Imprint
 Providence, R.I. : American Mathematical Society, c2011.
 Physical description
 viii, 175 p. : ill. ; 27 cm.
 Series
 Proceedings of symposia in applied mathematics ; v. 69.
Access
Creators/Contributors
 Corporate Author
 American Mathematical Society. Short Course (2011 : New Orleans, La.)
 Contributor
 Sigmund, Karl, 1945
Contents/Summary
 Bibliography
 Includes bibliographical references and index.
 Contents

 Introduction to evolutionary game theory by K. Sigmund Beyond the symmetric normal form: Extensive form games, asymmetric games and games with continuous strategy spaces by R. Cressman Deterministic evolutionary game dynamics by J. Hofbauer On some global and unilateral adaptive dynamics by S. Sorin Stochastic evolutionary game dynamics: Foundations, deterministic approximation, and equilibrium selection by W. H. Sandholm Evolution of cooperation in finite populations by S. Lessard Index.
 (source: Nielsen Book Data)
 Publisher's Summary
 This volume is based on lectures delivered at the 2011 AMS Short Course on Evolutionary Game Dynamics, held January 45, 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 Z99 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 multiagent 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.
(source: Nielsen Book Data)
Subjects
Bibliographic information
 Publication date
 2011
 Series
 Proceedings of symposia in applied mathematics ; v. 69
 ISBN
 9780821853269 (alk. paper)
 0821853260 (alk. paper)