Download PDF by Ron Lavi: Algorithmic Game Theory: 7th International Symposium, SAGT

International 1

By Ron Lavi

ISBN-10: 3662448025

ISBN-13: 9783662448021

ISBN-10: 3662448033

ISBN-13: 9783662448038

This publication constitutes the refereed court cases of the seventh overseas Symposium on Algorithmic video game conception, SAGT 2014, held in Haifa, Israel, in October 2014. The 24 complete papers and five brief papers awarded have been rigorously reviewed and chosen from sixty five submissions. They conceal numerous vital facets of algorithmic video game thought, reminiscent of matching idea, video game dynamics, video games of coordination, networks and social selection, markets and auctions, fee of anarchy, computational features of video games, mechanism layout and auctions.

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Extra info for Algorithmic Game Theory: 7th International Symposium, SAGT 2014, Haifa, Israel, September 30 – October 2, 2014. Proceedings

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In order to better capture such situations there is a need for a model that allows for more general preferences. Addressing this need we propose the Stable Marriage with General Preferences (SMG) problem. As in SM, in an instance of SMG we are given n men, and n women, and the preferences of men are complete total orders over the set of women. The preferences of women, on the other hand, are given in terms of arbitrary binary relations over the men. Each of these binary relations will be represented by a set of ordered pairs of men.

Assume that n = i(i + 1)/2 − j where 0 < j < i. In this case, first we create a staircase packing of a subset of n = i(i − 1)/2 items, leaving i − j free items. For k = 1, . . , i − j, the k-th free item is moved from its bin, to the bins B1 , B2 , . , Bi−k , in this order. The bin Bi−k will contain i − k + 1 items as a result and will not be used for later steps. After this is done for i − j items, Bη will contain η + 1 items for j ≤ η ≤ i − 1, and for 1 ≤ η ≤ j − 1, Bη still contains η items.

One can imagine that sometimes an agent can be adversarial, and he would not admit that he does not value any of the remaining items. To address this issue, in the next section we present an analysis of RSD mechanism in which every agent can be adversarial. 20 M. Adamczyk, P. Sankowski, and Q. Zhang Algorithm 1. , n} be the ranking of items; For each agent a ∈ A in random order: ask agent a about his preference profile da ∈ V = {0, 1}I ; if there is no unmatched item i such that da (i) = 1, then discard agent a; otherwise, assign a to unmatched item i that has the highest rank σ (i); Match any unmatched items to unmatched agents anyhow.

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Algorithmic Game Theory: 7th International Symposium, SAGT 2014, Haifa, Israel, September 30 – October 2, 2014. Proceedings by Ron Lavi


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