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Congestion games are a fundamental class of games widely considered and studied in non-cooperative game theory, introduced to model several realistic scenarios in which people share a limited quantity of goods or services. In congestion games there are several selfish players competing for a set of resources, and each resource incurs a certain latency, expressed by a congestion-dependent function, to the players using it. Each player has a certain weight and an available set of strategies, where each strategy is a non-empty subset of resources, and aims at choosing a strategy minimizing her…mehr

Produktbeschreibung
Congestion games are a fundamental class of games widely considered and studied in non-cooperative game theory, introduced to model several realistic scenarios in which people share a limited quantity of goods or services. In congestion games there are several selfish players competing for a set of resources, and each resource incurs a certain latency, expressed by a congestion-dependent function, to the players using it. Each player has a certain weight and an available set of strategies, where each strategy is a non-empty subset of resources, and aims at choosing a strategy minimizing her personal cost, which is defined as the sum of the latencies experienced on all the selected resources. The impact of selfish behavior in congestion games generally deteriorates the social welfare, thus reducing their performance. This deterioration is generally estimated by the price of anarchy, a metric that compares the worst Nash equilibrium configuration with the optimal social welfare, so that the larger the price of anarchy for a game, the higher the impact of selfish behavior.

The book derives from the first author's thesis, which won the Best Italian PhD Thesis in Theoretical Computer Science in 2019, awarded by the Italian chapter of the EATCS. The book will be revised for broader audience, and the thesis supervisor is joining as coauthor following the suggestion of the series. The authors will introduce examples for initial definitions with detailed explanations, and expand the scope to the broader results in the area rather than their specific work.
Autorenporträt
Vittorio Bilò is an Associate Professor in the Department of Mathematics and Physics "Ennio De Giorgi" at the University of Salento, Italy. He received a PhD in Computer Science from the University of L'Aquila in 2005, upon defence of a thesis that was named the best Italian PhD thesis of the year by the Italian Chapter of the European Association for Theoretical Computer Science. His research interests focus on algorithm design and analysis, with a particular predilection for problems arising at the interface between Theoretical Computer Science and Game Theory (Algorithmic Game Theory). During his career, he has authored and co-authored more than one hundred publications in top-class conferences and journals.  Cosimo Vinci is an Assistant Professor in the Department of Mathematics and Physics "Ennio De Giorgi" at the University of Salento, Italy. He received a PhD in Computer Science from Gran Sasso Science Institute in 2018, discussing a thesis that was awarded as the best Italian PhD thesis of the year by the Italian Chapter of the European Association for Theoretical Computer Science. His research activity covers several areas from Theoretical Computer Science and Applied Mathematics, and is particularly focused on Algorithmic Game Theory, Stochastic Optimization, Approximation and Online Algorithms. He is author of several publications appeared in prestigious conferences and journals.
Rezensionen
"In this monograph on algorithmic game theory, the authors present a summary of their work on applying primal-dual formulations from linear programming to analyze congestion games. They demonstrate that those techniques allow them to solve open problems and to generalize prior results. ... the book is a reference for researchers who are already familiar with algorithmic game theory and with the analysis of congestion games in particular." (Thomas Wiseman, zbMATH 1537.91001, 2024)