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Algorithmic Game Theory: 5th International Symposium, SAGT by Krzysztof R. Apt, Sunil Simon (auth.), Maria Serna (eds.)

By Krzysztof R. Apt, Sunil Simon (auth.), Maria Serna (eds.)

This booklet constitutes the refereed lawsuits of the fifth foreign Symposium on Algorithmic online game idea, SAGT 2012, held in Barcelona, Spain, in October 2012. The 22 revised complete papers awarded including 2 invited lectures have been rigorously reviewed and chosen from sixty five submissions. The papers current unique study on the intersection of Algorithms and video game thought and handle a number of present themes similar to resolution recommendations in video game conception; potency of equilibria and cost of anarchy; complexity sessions in online game thought; computational features of equilibria; computational points of fixed-point theorems; repeated video games; evolution and studying in video games; convergence of dynamics; coalitions, coordination and collective motion; recognition, advice and belief platforms; graph-theoretic points of social networks; community video games; cost-sharing algorithms and research; computing with incentives; algorithmic mechanism layout; computational social selection; determination thought, and pricing; public sale algorithms and research; fiscal facets of dispensed computing; net economics and computational advertising.

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Additional resources for Algorithmic Game Theory: 5th International Symposium, SAGT 2012, Barcelona, Spain, October 22-23, 2012. Proceedings

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T. for each player i ∈ [r], Ui (σ) ≤ u? : A game SG. : Does SG have at least two Nash equilibria? : A game SG, and a subset of strategies Ti ⊆ Σi for each player i ∈ [r]. t. for each player i ∈ [r], Supp(σi ) ⊆ Ti ? : A game SG, and a subset of strategies Ti ⊆ Σi for each player i ∈ [r]. t. for each player i ∈ [r], Ti ⊆ Supp(σi )? : A game SG and an integer k ≥ 1. t. for each player i ∈ [r], |Supp(σi )| ≥ k? : A game SG and an integer k ≥ 1. t. for each player i ∈ [r], |Supp(σi )| ≤ k? : A game SG and a number u.

We explore the effects of truthfulness (both randomized and deterministic) in this restricted setting: (1) Power of truthful-in-expectation mechanisms. There is a class of two-values scheduling problems for which every algorithm (thus including optimal ones) can be turned into a truthful-in-expectation mechanism with the same approximation guarantee (Theorem 3). On the contrary, randomized universally truthful mechanisms cannot achieve an approximation better than 31/30 (Theorem 17), and the 11/10 lower bound for deterministic mechanisms in [10] also applies.

A strategic game SG satisfies the positive utility property if for each player i ∈ [r] and each partial pure profile s−i ∈ Σ−i , there is a strategy t(s−i ) ∈ Σi for which Ui (s−i t(s−i )) > 0. The main results follow: Theorem 1. Fix a win-lose game SG with the positive utility property. Then, restricted to win-lose games, NASH-EQUIVALENCE(SG) is co-N P-hard. By suitable choices for the gadget game SG, the Nash-equivalence of the given game SG to the gadget game SG becomes equivalent to the fact that SG does not have a Nash equilibrium with certain properties.

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