Comparison of Algorithms for Simple Stochastic Games
Abstract
Simple stochastic games are turn-based 2.5-player zero-sum graph games with a reachability objective. The problem is to compute the winning probability 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.
Keywords
Cite
@article{arxiv.2009.10882,
title = {Comparison of Algorithms for Simple Stochastic Games},
author = {Jan Křetínský and Emanuel Ramneantu and Alexander Slivinskiy and Maximilian Weininger},
journal= {arXiv preprint arXiv:2009.10882},
year = {2020}
}
Comments
In Proceedings GandALF 2020, arXiv:2009.09360