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arXiv · 1903.06288

Optimal Price of Anarchy in Cost-Sharing Games

Rahul Chandan·Dario Paccagnan·Jason R. Marden
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Abstract

The design of distributed algorithms is central to the study of multiagent systems control. In this paper, we consider a class of combinatorial cost-minimization problems and propose a framework for designing distributed algorithms with a priori performance guarantees that are near-optimal. We approach this problem from a game-theoretic perspective, assigning agents cost functions such that the equilibrium efficiency (price of anarchy) is optimized. Once agents' cost functions have been specified, any algorithm capable of computing a Nash equilibrium of the system inherits a performance guarantee matching the price of anarchy. Towards this goal, we formulate the problem of computing the price of anarchy as a tractable linear program. We then present a framework for designing agents' local cost functions in order to optimize for the worst-case equilibrium efficiency. Finally, we investigate the implications of our findings when this framework is applied to systems with convex, nondecreasing costs.

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BibTeXRIS

Rahul Chandan, Dario Paccagnan, Jason R. Marden. 2019-03-14. Optimal Price of Anarchy in Cost-Sharing Games. https://arxiv.org/abs/1903.06288

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