Coping with Selfishness in Congestion Games
Analysis and Design via LP Duality
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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 pe...
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.
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.
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