An Abstraction-Refinement Methodology for Reasoning about Network Games.

Guy Avni, Shibashis Guha, Orna Kupferman*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Network games (NGs) are played on directed graphs and are extensively used in network design and analysis. Search problems for NGs include finding special strategy profiles such as a Nash equilibrium and a globally-optimal solution. The networks modeled by NGs may be huge. In formal verification, abstraction has proven to be an extremely effective technique for reasoning about systems with big and even infinite state spaces. We describe an abstraction-refinement methodology for reasoning about NGs. Our methodology is based on an abstraction function that maps the state space of an NG to a much smaller state space. We search for a global optimum and a Nash equilibrium by reasoning on an under-and an over-approximation defined on top of this smaller state space. When the approximations are too coarse to find such profiles, we refine the abstraction function. We extend the abstraction-refinement methodology to labeled networks, where the objectives of the players are regular languages. Our experimental results demonstrate the effectiveness of the methodology.

Original languageEnglish
Article number39
Pages (from-to)1-21
Number of pages21
Issue number3
StatePublished - Sep 2018

Bibliographical note

Publisher Copyright:
© 2018 by the authors. Licensee MDPI, Basel, Switzerland.


  • Abstraction-refinement
  • Nash equilibrium
  • Network formation games
  • Social optimum


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