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

By Ron Lavi

This publication constitutes the refereed court cases of the seventh overseas Symposium on Algorithmic online 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 hide a variety of very important features of algorithmic video game conception, corresponding to matching thought, video game dynamics, video games of coordination, networks and social selection, markets and auctions, cost of anarchy, computational points of video games, mechanism layout and auctions.

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

Sample text

A 3D matching is said to be stable if there is no (man, woman, dog) triple that is strictly preferred to their current triples in the matching by each of its members. A prominent open question is whether every instance of c3DSM admits a stable matching, and whether it can be computed efficiently. A natural avenue for attacking c3DSM is to solve the following problem which we refer to as Stable Extension (SE): suppose we fix a perfect matching M on dogs and men, can we efficiently determine whether M is extendible to a 3D stable matching?

Finally we will define the preference of woman ci over the set of dogs in J as follows: ci will rank the dogs that are matched in M to men from the first position in P (ci ) at the top of its list, in any arbitrary order among them, followed by the dog ai,1 ; then the dogs that are matched in M to men from the second position in P (ci ) followed by the dog ai,2 , and so on until the dogs that are matched in M to men from the last position in P (ci ) followed by the dog ai,ti . The remainder of ci ’s preference list will be completed arbitrarily.

We can now finish lowerbounding Lt ≥ ν (O)−n+n·e− ν(O) n ≥ 1 ν (O)2 , e n where the last inequality follows from x − 1 + e−x ≥ 1e x2 for x ∈ [0, 1]. On the hardness side, Result 4 says that no truthful mechanism can achieve 2 social welfare greater than ν(O) n . The proof is deferred to the full version of the paper. 6 Open Question As mentioned in the introduction, we can give the following truthful and symmetric mechanisms that outputs optimal social welfare. The mechanism works as follows. First, collect agents preferences da for all a ∈ A.

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