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The Price of Defense

  • Marios Mavronicolas
  • Loizos Michael
  • Vicky Papadopoulou
  • Anna Philippou
  • Paul Spirakis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4162)

Abstract

We consider a strategic game with two classes of confronting randomized players on a graph G(V, E): ν attackers, each choosing vertices and wishing to minimize the probability of being caught, and a defender, who chooses edges and gains the expected number of attackers it catches. The Price of Defense is the worst-case ratio, over all Nash equilibria, of the optimal gain of the defender over its gain at a Nash equilibrium. We provide a comprehensive collection of trade-offs between the Price of Defense and the computational efficiency of Nash equilibria.

– Through reduction to a Two-Players, Constant-Sum Game, we prove that a Nash equilibrium can be computed in polynomial time. The reduction does not provide any apparent guarantees on the Price of Defense.

– To obtain such, we analyze several structured Nash equilibria:

– In a Matching Nash equilibrium, the support of the defender is an Edge Cover. We prove that they can be computed in polynomial time, and they incur a Price of Defense of α(G), the Independence Number of G.

– In a Perfect Matching Nash equilibrium, the support of the defender is a Perfect Matching. We prove that they can be computed in polynomial time, and they incur a Price of Defense of \(\frac{|V|}{2}\).

– In a Defender Uniform Nash equilibrium, the defender chooses uniformly each edge in its support. We prove that they incur a Price of Defense falling between those for Matching and Perfect Matching Nash Equilibria; however, it is \({\cal NP}\)-complete to decide their existence.

– In an Attacker Symmetric and Uniform Nash equilibrium, all attackers have a common support on which each uses a uniform distribution. We prove that they can be computed in polynomial time and incur a Price of Defense of either \(\frac{|V|}{2}\) or α(G).

Keywords

Nash Equilibrium Perfect Match Polynomial Time Algorithm Vertex Cover Strategic Game 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Marios Mavronicolas
    • 1
  • Loizos Michael
    • 2
  • Vicky Papadopoulou
    • 1
  • Anna Philippou
    • 1
  • Paul Spirakis
    • 3
    • 4
  1. 1.Department of Computer ScienceUniversity of CyprusNicosiaCyprus
  2. 2.Division of Engineering and Applied SciencesHarvard UniversityCambridgeUSA
  3. 3.Research Academic Computer Technology Institute (RACTI), RionPatrasGreece
  4. 4.Department of Computer Engineering and InformaticsUniversity of Patras, RionPatrasGreece

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