Two-player graph games have found numerous applications, most notably in the synthesis of reactive systems from temporal specifications, but also in verification. The relevance of infinite-state systems in these areas has lead to significant attention towards developing techniques for solving infinite-state games.
We propose novel symbolic semi-algorithms for solving infinite-state games with $\omega$-regular winning conditions. The novelty of our approach lies in the introduction of an acceleration technique that enhances fixpoint-based game-solving methods and helps to avoid divergence. Classical fixpoint-based algorithms, when applied to infinite-state games, are bound to diverge in many cases, since they iteratively compute the set of states from which one player has a winning strategy. Our proposed approach can lead to convergence in cases where existing algorithms require an infinite number of iterations. This is achieved by acceleration: computing an infinite set of states from which a simpler sub-strategy can be iterated an unbounded number of times in order to win the game. Ours is the first method for solving infinite-state games to employ acceleration. Thanks to this, it is able to outperform state-of-the-art techniques on a range of benchmarks, as evidenced by our evaluation of a prototype implementation.
Thu 18 JanDisplayed time zone: London change
15:30 - 16:50 | |||
15:30 20mTalk | Polyregular functions on unordered trees of bounded height POPL | ||
15:50 20mTalk | Solving Infinite-State Games via Acceleration POPL Philippe Heim CISPA Helmholtz Center for Information Security, Rayna Dimitrova CISPA Helmholtz Center for Information Security Pre-print | ||
16:10 20mTalk | Ramsey Quantifiers in Linear Arithmetics POPL Pascal Bergsträßer University of Kaiserslautern-Landau, Moses Ganardi MPI-SWS, Anthony Widjaja Lin TU Kaiserslautern; MPI-SWS, Georg Zetzsche MPI-SWS Pre-print | ||
16:30 20mTalk | Reachability in Continuous Pushdown VASS POPL A. R. Balasubramanian Technical University of Munich, Rupak Majumdar MPI-SWS, Ramanathan S. Thinniyam Uppsala University, Georg Zetzsche MPI-SWS Pre-print |