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Probabilistic Model Checking for Strategic Equilibria-Based Decision Making: Advances and Challenges (Invited Talk)

Authors Marta Kwiatkowska , Gethin Norman , David Parker , Gabriel Santos , Rui Yan



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Marta Kwiatkowska
  • University of Oxford, Oxford, UK
Gethin Norman
  • University of Glasgow, Glasgow, UK
  • University of Oxford, Oxford, UK
David Parker
  • University of Birmingham, Birmingham, UK
Gabriel Santos
  • University of Oxford, Oxford, UK
Rui Yan
  • University of Oxford, Oxford, UK

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Marta Kwiatkowska, Gethin Norman, David Parker, Gabriel Santos, and Rui Yan. Probabilistic Model Checking for Strategic Equilibria-Based Decision Making: Advances and Challenges (Invited Talk). In 47th International Symposium on Mathematical Foundations of Computer Science (MFCS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 241, pp. 4:1-4:22, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/LIPIcs.MFCS.2022.4

Abstract

Game-theoretic concepts have been extensively studied in economics to provide insight into competitive behaviour and strategic decision making. As computing systems increasingly involve concurrently acting autonomous agents, game-theoretic approaches are becoming widespread in computer science as a faithful modelling abstraction. These techniques can be used to reason about the competitive or collaborative behaviour of multiple rational agents with distinct goals or objectives. This paper provides an overview of recent advances in developing a modelling, verification and strategy synthesis framework for concurrent stochastic games implemented in the probabilistic model checker PRISM-games. This is based on a temporal logic that supports finite- and infinite-horizon temporal properties in both a zero-sum and nonzero-sum setting, the latter using Nash and correlated equilibria with respect to two optimality criteria, social welfare and social fairness. We summarise the key concepts, logics and algorithms and the currently available tool support. Future challenges and recent progress in adapting the framework and algorithmic solutions to continuous environments and neural networks are also outlined.

Subject Classification

ACM Subject Classification
  • Theory of computation
Keywords
  • Probabilistic model checking
  • stochastic games
  • equilibria

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