Computational Aspects of Cooperative Game Theory
by Georgios Chalkiadakis, Edith Elkind, and Michael Wooldridge
Table of contents
Slides
Videos
Endorsements
Acknowledgements
Bibliography
Published Oct 2011 by
Morgan and Claypool
as a part of Synthesis Lectures
on Artificial Intelligence and Machine Learning.
DOI: 10.2200/S00355ED1V01Y201107AIM016
You can download the book from the publisher's website here. The download is free for readers at Synthesis licensing institutions.
This book is intended as a graduate-level textbook. It is based on the tutorials given by the authors at ECAI-2008 (Patras, Greece), AAMAS-2009 (Budapest, Hungary), AAMAS-2010 (Toronto, Canada), AAAI-2010 (Atlanta, Georgia), AAMAS-2011 (Taipei,Taiwan), and IJCAI-2011 (Barcelona, Catalonia, Spain), and can serve as a basis of a 6-week or 12-week graduate or advanced undergraduate course. To aid the reader, we provide the slides as well as a video recording of our IJCAI-2011 tutorial.
Abstract
Cooperative game theory is a branch of (micro-)economics that studies the behavior of self-interested agents in strategic settings where binding agreements among agents are possible. Our aim in this book is to present a survey of work on the computational aspects of cooperative game theory. We begin by formally defining transferable utility games in characteristic function form, and introducing key solution concepts such as the core and the Shapley value. We then discuss two major issues that arise when considering such games from a computational perspective: identifying compact representations for games, and the closely related problem of efficiently computing solution concepts for games. We survey several formalisms for cooperative games that have been proposed in the literature, including, for example, cooperative games defined on networks, as well as general compact representation schemes such as MC-nets and skill games. As a detailed case study, we consider weighted voting games: a widely-used and practically important class of cooperative games that inherently have a natural compact representation. We investigate the complexity of solution concepts for such games, and generalizations of them. We briefly discuss games with non-transferable utility and partition function games. We then overview algorithms for identifying welfare-maximizing coalition structures and methods used by rational agents to form coalitions (even under uncertainty), including bargaining algorithms. We conclude by considering some developing topics, applications, and future research directions.If you have any questions, suggestions, or comments (and, in particular, if you have discovered any errors), please do not hesitate to get in touch with us