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Exact capacitated domination: on the computational complexity of uniqueness

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  • Gregory Gutin
  • Philip R Neary
  • Anders Yeo

Abstract

In this paper we consider a local service-requirement assignment problem named exact capacitated domination from an algorithmic point of view. This problem aims to find a solution (a Nash equilibrium) to a game-theoretic model of public good provision. In the problem we are given a capacitated graph, a graph with a parameter defined on each vertex that is interpreted as the capacity of that vertex. The objective is to find a DP-Nash subgraph: a spanning bipartite subgraph with partite sets D and P, called the D-set and P-set respectively, such that no vertex in P is isolated and that each vertex in D is adjacent to a number of vertices equal to its capacity. We show that whether a capacitated graph has a unique DP-Nash subgraph can be decided in polynomial time. However, we also show that the nearby problem of deciding whether a capacitated graph has a unique D-set is co-NP-complete.

Suggested Citation

  • Gregory Gutin & Philip R Neary & Anders Yeo, 2020. "Exact capacitated domination: on the computational complexity of uniqueness," Papers 2003.07106, arXiv.org, revised Jul 2022.
  • Handle: RePEc:arx:papers:2003.07106
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    References listed on IDEAS

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    1. Morris, Stephen & Shin, Hyun Song, 1998. "Unique Equilibrium in a Model of Self-Fulfilling Currency Attacks," American Economic Review, American Economic Association, vol. 88(3), pages 587-597, June.
    2. Alvin Roth, 2008. "Deferred acceptance algorithms: history, theory, practice, and open questions," International Journal of Game Theory, Springer;Game Theory Society, vol. 36(3), pages 537-569, March.
    3. Stefanie Gerke & Gregory Gutin & Sung-Ha Hwang & Philip Neary, 2019. "Public goods in networks with constraints on sharing," Papers 1905.01693, arXiv.org, revised Jun 2023.
    4. Bramoulle, Yann & Kranton, Rachel, 2007. "Public goods in networks," Journal of Economic Theory, Elsevier, vol. 135(1), pages 478-494, July.
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