Comparison of algorithms for simple stochastic games

Jan Křetínský, Emanuel Ramneantu, Alexander Slivinskiy, Maximilian Weininger

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Simple stochastic games are turn-based 2½-player zero-sum graph games with a reachability objective. The problem is to compute the winning probabilities as well as the optimal strategies of both players. In this paper, we compare the three known classes of algorithms – value iteration, strategy iteration and quadratic programming – both theoretically and practically. Further, we suggest several improvements for all algorithms, including the first approach based on quadratic programming that avoids transforming the stochastic game to a stopping one. Our extensive experiments show that these improvements can lead to significant speed-ups. We implemented all algorithms in PRISM-games 3.0, thereby providing the first implementation of quadratic programming for solving simple stochastic games.

Original languageEnglish
Article number104885
JournalInformation and Computation
Volume289
DOIs
StatePublished - Nov 2022

Keywords

  • Algorithms
  • Formal methods
  • Probabilistic verification
  • Quadratic programming
  • Stochastic games
  • Strategy iteration
  • Value iteration

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