提出自动求解无限状态多项式可达性博弈的完整方法。
Automated Approach for Solving Infinite-state Polynomial Reachability Games

- 用排名证书证明可达方有必胜策略,形式化且完备。
- 针对多项式约束博弈,实现半完备自动求解,时间复杂度亚指数级。
- 首次为经典灰姑娘-继母游戏计算任意精度下的最优策略。
可达性博弈是玩家在图上进行的二人博弈,其中'可达'方目标是进入目标集,'安全'方则试图避开目标集。这类博弈在人工智能与反应式合成中有重要应用,许多场景涉及无限状态博弈。本文研究基于实数变量赋值的无限状态图上的轮转可达性博弈,重点解决从指定初始状态判断'可达'方是否存在获胜策略并计算该策略的问题。贡献有二:一是提出可达性博弈的排名证书,作为证明'可达'方存在获胜策略的可靠且完备的推理规则;二是针对由实数变量上的多项式约束描述转移与目标的多项式可达性博弈,提出一个全自动算法,可计算获胜策略并生成形式化正确性证明(即排名证书)。该算法具有保真性、半完备性,运行时间低于指数级。实验表明,该方法能解决文献中此前无法处理的难题,首次为经典灰姑娘-继母博弈计算出任意精度参数下的最优获胜策略。
原文摘要 · Abstract (English)
Reachability games are two-player games played on a graph, where the objective of $\texttt{REACH}$ player is to reach the target set whereas the objective of $\texttt{SAFE}$ player is to stay away from the target set. Reachability games have important applications in artificial intelligence and reactive synthesis, and many of these applications give rise to infinite-state reachability games. In this paper, we study turn-based reachability games on infinite-state graphs defined over valuations of a finite set of real variables. We consider the problem of determining the existence of and computing a winning strategy for $\texttt{REACH}$ player. Our contributions are twofold. First, we propose ranking certificates for reachability games, a sound and complete proof rule for proving that $\texttt{REACH}$ player has a winning strategy from the specified initial state. Second, we consider polynomial reachability games, where transitions and objectives are described by polynomial constraints over real variables, and propose a fully automated algorithm for computing a winning strategy for $\texttt{REACH}$ player together with a formal correctness witness in the form of a ranking certificate. The algorithm is sound, semi-complete, and runs in sub-exponential time. Our experiments demonstrate the ability of our method to solve challenging examples from the literature that were out of the reach of existing methods. Specifically, for the classical Cinderella-Stepmother game, we are able to compute an optimal winning strategy for an arbitrary precision parameter for the first time.
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