On Pareto Optimality in Social Distance Games

Authors

  • Alkida Balliu Gran Sasso Science Institute
  • Michele Flammini University of L'Aquila and Gran Sasso Science Institute
  • Dennis Olivetti Gran Sasso Science Institute

DOI:

https://doi.org/10.1609/aaai.v31i1.10607

Keywords:

Algorithmic Game Theory, Coalition Formation, Social Distance Games, Pareto Stability

Abstract

We investigate Pareto stability in Social Distance Games, that are coalition forming games in which agents utilities are proportional to their harmonic centralities in the respective coalitions, i.e., to the average inverse distance from the other agents. Pareto optimal solutions have been already considered in the literature as outcomes arising from the strategic interaction of the agents. In particular, they are stable under the deviation of the grand coalition, as they do not permit a simultaneous deviation by all the agents making all of them weakly better off and some strictly better off. We first show that, while computing a Pareto stable solution maximizing the social welfare is NP-hard in bounded degree graphs, a 2 min{Delta,sqrt n}-approximating one can be determined in polynomial time, where n is the number of agents and Delta the maximum node degree. We then determine asymptotically tight bounds on the Price of Pareto Optimality for several classes of social graphs arising from the following combinations: unbounded and bounded node degree, undirected and directed edges, unweighted and weighted edges.

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Published

2017-02-10

How to Cite

Balliu, A., Flammini, M., & Olivetti, D. (2017). On Pareto Optimality in Social Distance Games. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.10607

Issue

Section

AAAI Technical Track: Game Theory and Economic Paradigms