Edith Elkind – författare

This book constitutes the refereed proceedings of the Second International Conference on Distributed Artificial Intelligence, DAI 2020, held in Nanjing, China, in October 2020.The 9 full papers presented in this book were carefully reviewed and selected from 22 submissions. DAI aims at bringing together international researchers and practitioners in related areas including general AI, multiagent systems, distributed learning, computational game theory, etc., to provide a single, high-profile, internationally renowned forum for research in the theory and practice of distributed AI. Due to the Corona pandemic this event was held virtually.

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.

This book constitutes the refereed proceedings of the 7th International Workshop on Internet and Network Economics, WINE 2011, held in Singapore, in December 2011. The 31 revised full papers and 5 revised short papers presented together with the abstracts of 3 papers about work in progress were carefully reviewed and selected from 100 submissions. The papers are organized in topical sections on algorithmic game theory, algorithmic mechanism design, computational advertising, computational social choice, convergence and learning in games, economics aspects of security and privacy, information and attention economics, network games and social networks.

This book constitutes the refereed proceedings of the 7th International Workshop on Internet and Network Economics, WINE 2011, held in Singapore, in December 2011. The 31 revised full papers and 5 revised short papers presented together with the abstracts of 3 papers about work in progress were carefully reviewed and selected from 100 submissions. The papers are organized in topical sections on algorithmic game theory, algorithmic mechanism design, computational advertising, computational social choice, convergence and learning in games, economics aspects of security and privacy, information and attention economics, network games and social networks.

This book constitutes the refereed proceedings of the 16th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2013, held in Dunedin, New Zealand, in December 2013. The conference was co-located with the 26th Australasian Artificial International Conference, AI 2013. The 24 revised full papers presented together with 18 short papers and 2 invited papers were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on foundations of agents and multi-agent systems; agent and multi-agent system architectures; agent-oriented software engineering; agent-based modelling and simulation; cooperation/collaboration, coordination/communication; hybrid technologies, application domains; and applications.