EAN: 9783031004308

SYNTHESIS LECTURES ON ARTIFICIAL INTELLIGENCE A...

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.

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