Computational Aspects Of Cooperative Game Theory

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.

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.

In this book applications of cooperative game theory that arise from combinatorial optimization problems are described. It is well known that the mathematical modeling of various real-world decision-making situations gives rise to combinatorial optimization problems. For situations where more than one decision-maker is involved classical combinatorial optimization theory does not suffice and it is here that cooperative game theory can make an important contribution. If a group of decision-makers decide to undertake a project together in order to increase the total revenue or decrease the total costs, they face two problems. The first one is how to execute the project in an optimal way so as to increase revenue. The second one is how to divide the revenue attained among the participants. It is with this second problem that cooperative game theory can help. The solution concepts from cooperative game theory can be applied to arrive at revenue allocation schemes. In this book the type of problems described above are examined. Although the choice of topics is application-driven, it also discusses theoretical questions that arise from the situations that are studied. For all the games described attention will be paid to the appropriateness of several game-theoretic solution concepts in the particular contexts that are considered. The computation complexity of the game-theoretic solution concepts in the situation at hand will also be considered.

This book systematically presents the main solutions of cooperative games: the core, bargaining set, kernel, nucleolus, and the Shapley value of TU games as well as the core, the Shapley value, and the ordinal bargaining set of NTU games. The authors devote a separate chapter to each solution, wherein they study its properties in full detail. In addition, important variants are defined or even intensively analyzed.

This book analyzes coalitional control schemes by incorporating concepts of cooperative game theory into a distributed control framework. It considers a networked architecture where the nodes are the agents and the edges are their communication links and either the agents or the links are established as the players of cooperative games related to the cost function of the coalitional schemes. The book discusses various cooperative game theory tools that are used to measure/analyze the players’ features, impose constraints on them, provide alternative methods of game computation, detect critical players inside the control scheme, and perform system partitioning of large-scale systems, such as the Barcelona drinking water network, which is described in a case study.

This book introduces new concepts for cooperative game theory, and particularly solutions that determine the distribution of a coalitional surplus among the members of the coalition. It also addresses several generalizations of cooperative game theory. Drawing on methods of welfare economics, new value solutions are derived for Non-Transferable Utility games with and without differences of bargaining power among the members of the coalition. Cooperation in intertemporal games is examined, and conditions that permit the reduction of these games to games in coalition function form are outlined. Biform games and games that combine non-cooperative search and matching of coalition members with cooperative solutions (i.e., efficient contracts) within the coalition are considered. Contents:Value Solutions for Superadditive Transferable Utility Games in Coalition Function FormZeuthen–Nash BargainingNontransferable Utility Games and Games in Partition Function FormA Shapley Value Algorithm for Games in Partition Function FormExtension of the Nucleolus to Nontransferable Utility Games in Partition Function FormA Core Imputation with Variable Bargaining PowerBargaining Power Biform GamesIntertemporal Cooperative Games: A Sketch of a TheoryA Theory of Enterprise Readership: Graduate students and researchers in the field of game theory. Keywords:Cooperative Games;Value;Imputation;Bargaining TheoryKey Features:Proposes a value solution for games of two or more players that: (i) is the Nash bargaining solution in a special case, (ii) allows for unsymmetrical bargaining power, (iii) allows for group-to-group bargaining, and (iv) is always a point in the core of the game if the game is not nullUses methods from mathematical welfare economics to bridge the gap from non-transferable utility to transferable utilityRelying on Biform Games (Brandenburger and Stuart), constructs a model of cooperative value creation in coalitions formed by non-cooperative search and matching

This textbook connects three vibrant areas at the interface between economics and computer science: algorithmic game theory, computational social choice, and fair division. It thus offers an interdisciplinary treatment of collective decision making from an economic and computational perspective. Part I introduces to algorithmic game theory, focusing on both noncooperative and cooperative game theory. Part II introduces to computational social choice, focusing on both preference aggregation (voting) and judgment aggregation. Part III introduces to fair division, focusing on the division of both a single divisible resource ("cake-cutting") and multiple indivisible and unshareable resources ("multiagent resource allocation"). In all these parts, much weight is given to the algorithmic and complexity-theoretic aspects of problems arising in these areas, and the interconnections between the three parts are of central interest.

Essays on Cooperative Games collates selected contributions on Cooperative Games. The papers cover both theoretical aspects (Coalition Formation, Values, Simple Games and Dynamic Games) and applied aspects (in Finance, Production, Transportation and Market Games). A contribution on Minimax Theorem (by Ken Binmore) and a brief history of early Game Theory (by Gianfranco Gambarelli and Guillermo Owen) are also enclosed.