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

ISBN-10: 3642339956

ISBN-13: 9783642339950

ISBN-10: 3642339964

ISBN-13: 9783642339967

This publication constitutes the refereed court cases of the fifth overseas Symposium on Algorithmic video game thought, 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 learn on the intersection of Algorithms and video game thought and deal with quite a few present themes akin to answer recommendations in online game conception; potency of equilibria and value of anarchy; complexity periods in online game concept; computational elements of equilibria; computational elements of fixed-point theorems; repeated video games; evolution and studying in video games; convergence of dynamics; coalitions, coordination and collective motion; popularity, suggestion and belief structures; 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; monetary points of dispensed computing; web 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

Sample text

In particular, for n = 2 we get, as already argued in Example 1, that the selfishness level of the original Prisoner’s Dilemma game is 1. Public Goods. We consider the public goods game with n players. Every player i ∈ N = {1, . . , n} chooses an amount si ∈ [0, b] that he contributes to a public good, where b ∈ R+ is the budget. The game designer collects the individual contributions of all players, multiplies their sum by c > 1 and distributes the resulting amount evenly among all players. The payoff of player i is thus pi (s) := b − si + nc j∈N sj .

We represent an allocation by a matrix x = (xih ), where xih ∈ {0, 1} and xih = 1 iff job h is assigned to machine i (since every job is assigned to exactly one machine, i xih = 1). Given an allocation x and machine types t, we define the load of machine i as the set of jobs allocated to i in x and denote by Ci (x, t) := h xih tih the cost of machine i. The makespan of x with respect to t is maxi Ci (x, t). An exact or optimal allocation x is an allocation that, for the given input t, minimizes the makespan.

Kuˇcera, A. ) MFCS 2007. LNCS, vol. 4708, pp. 454–464. Springer, Heidelberg (2007) 10. : Truthful mechanism design for multidimensional scheduling via cycle monotonicity. Games and Economic Behavior 67(1), 99–124 (2009) 11. : On 2-Player Randomized Mechanisms for Scheduling. In: Leonardi, S. ) WINE 2009. LNCS, vol. 5929, pp. 30–41. Springer, Heidelberg (2009) 12. : An Improved Randomized Truthful Mechanism for Scheduling Unrelated Machines. In: Proc. of 25th STACS. LIPIcs, vol. 1, pp. 527–538 (2008) 13.

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Algorithmic Game Theory: 5th International Symposium, SAGT 2012, Barcelona, Spain, October 22-23, 2012. Proceedings by Krzysztof R. Apt, Sunil Simon (auth.), Maria Serna (eds.)


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