多目标析取随机博弈（技术报告）
Stochastic Games with Disjunctions of Multiple Objectives (Technical Report)
摘要：
随机博弈将可控和对抗的非确定性与随机行为结合起来，是控制、验证和合成面临不确定性的反应系统的常用工具。多目标随机游戏是自然的情况下，几个可能相互冲突的性能标准，如时间和能源消耗是相关的。这种合取组合是文献中研究最多的多目标设置。本文考虑对偶析取问题。更具体地说，我们研究了图上的回合制随机二人博弈，其中获胜条件是保证至少一个可达性或安全目标，从一组给定的替代品。我们提出了一个细粒度的战略和计算复杂性的概述，这样的\emph{disjunctive queries}（DQ），并提供了新的下限和上限的几个变种的问题，显着扩展以前的作品。我们还提出了一种新的值迭代式算法，用于近似给定DQ的Pareto最优阈值集。
英文摘要：
Stochastic games combine controllable and adversarial non-determinism with stochastic behavior and are a common tool in control, verification and synthesis of reactive systems facing uncertainty. Multi-objective stochastic games are natural in situations where several - possibly conflicting - performance criteria like time and energy consumption are relevant. Such conjunctive combinations are the most studied multi-objective setting in the literature. In this paper, we consider the dual disjunctive problem. More concretely, we study turn-based stochastic two-player games on graphs where the winning condition is to guarantee at least one reachability or safety objective from a given set of alternatives. We present a fine-grained overview of strategy and computational complexity of such \emph{disjunctive queries} (DQs) and provide new lower and upper bounds for several variants of the problem, significantly extending previous works. We also propose a novel value iteration-style algorithm for approximating the set of Pareto optimal thresholds for a given DQ.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
