Download Algorithmic Game Theory: 9th International Symposium, SAGT by Martin Gairing, Rahul Savani PDF

By Martin Gairing, Rahul Savani

This publication constitutes the refereed court cases of the ninth foreign Symposium on Algorithmic online game concept, SAGT 2016, held in Liverpool, united kingdom, in September 2016.The 26 complete papers awarded including 2 one-page abstracts have been rigorously reviewed and chosen from sixty two submissions.
The authorised submissions hide a number of vital aspectsof algorithmic video game thought akin to computational facets of video games, congestion video games and networks, matching and balloting, auctions and markets, and mechanism design.

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Extra resources for Algorithmic Game Theory: 9th International Symposium, SAGT 2016, Liverpool, UK, September 19–21, 2016, Proceedings

Example text

The graph G defines a coloring game. We fix any Nash equilibrium for this game, that exists by Theorem 1. By Claim 5, any two vertices in X have the same colour c0 . We will prove that there is at least one vertex in Ym with colour c0 if and only if the circuit C outputs 1 when it takes w as input. Since Monotone Circuit Value is PTIME-complete [9], the latter will prove that computing a Nash equilibrium for coloring games is PTIME-hard. By Claim 6, we only need to prove that for every 1 ≤ j ≤ m, there is at least one vertex in Yj ∪ Nj with colour c0 .

In what follows, we will use the fact that processors are numbered. We will handle with read/write conflicts between processors with the strategy CREW-PRAM (concurrent read, exclusive write). Let PTIME contain the decision problems that can be solved in sequential polynomial-time (that is, with a single processor). Problem A reduces to problem B if given an oracle to solve B, A can be solved in polylogarithmic-time with a polynomial number of processors. In particular, a problem B is PTIME-hard if every problem in PTIME reduces to B (this is formally defined as quasi-PTIME-hardness in [9]).

2) is to construct an approximation of the behavior of BRA over a potential game. This approximation is called IFA in the paper, for Intersection-Free Approximation because it discards strategies already explored 42 S. Durand and B. Gaujal by BRA. We show that the execution time of BRA is smaller than the execution time of its IFA approximation for the strong stochastic order. This is done by constructing a non-trivial coupling between both executions. This powerful technique is exploited to our great benefit here.

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