Smoothed Efficient Algorithms and Reductions for Network Coordination Games

Authors Shant Boodaghians, Rucha Kulkarni, Ruta Mehta

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Shant Boodaghians
  • University of Illinois at Urbana-Champaign, Urbana, IL, USA
Rucha Kulkarni
  • University of Illinois at Urbana-Champaign, Urbana, IL, USA
Ruta Mehta
  • University of Illinois at Urbana-Champaign, Urbana, IL, USA


We would like to thank Pravesh Kothari for the insightful discussions in the initial stages of this work.

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Shant Boodaghians, Rucha Kulkarni, and Ruta Mehta. Smoothed Efficient Algorithms and Reductions for Network Coordination Games. In 11th Innovations in Theoretical Computer Science Conference (ITCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 151, pp. 73:1-73:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


We study the smoothed complexity of finding pure Nash equilibria in Network Coordination Games, a PLS-complete problem in the worst case, even when each player has two strategies. This is a potential game where the sequential-better-response algorithm is known to converge to a pure NE, albeit in exponential time. First, we prove polynomial (respectively, quasi-polynomial) smoothed complexity when the underlying game graph is complete (resp. arbitrary), and every player has constantly many strategies. The complete graph assumption is reminiscent of perturbing all parameters, a common assumption in most known polynomial smoothed complexity results. We develop techniques to bound the probability that an (adversarial) better-response sequence makes slow improvements to the potential. Our approach combines and generalizes the local-max-cut approaches of Etscheid and Röglin (SODA `14; ACM TALG, `17) and Angel, Bubeck, Peres, and Wei (STOC `17), to handle the multi-strategy case. We believe that the approach and notions developed herein could be of interest in addressing the smoothed complexity of other potential games. Further, we define a notion of a smoothness-preserving reduction among search problems, and obtain reductions from 2-strategy network coordination games to local-max-cut, and from k-strategy games (k arbitrary) to local-max-bisection. The former, with the recent result of Bibak, Chandrasekaran, and Carlson (SODA `18) gives an alternate O(n^8)-time smoothed algorithm when k=2. These reductions extend smoothed efficient algorithms from one problem to another.

Subject Classification

ACM Subject Classification
  • Theory of computation → Algorithmic game theory
  • Network Coordination Games
  • Smoothed Analysis


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