Regstar：对抗巡逻游戏的有效策略合成
Regstar: Efficient Strategy Synthesis for Adversarial Patrolling Games
摘要：
我们设计了一个新的有效的策略合成方法适用于对抗巡逻问题的图与任意长度的边缘和可能不完善的入侵检测。核心成分是一个有效的算法，用于计算值和梯度的功能分配给每一个战略的“保护”实现。这使得设计一个有效的策略改进算法的微分规划和优化技术。我们的方法是第一个适用于现实世界的巡逻图的合理大小。它优于国家的最先进的战略合成算法的利润。
英文摘要：
We design a new efficient strategy synthesis method applicable to adversarial patrolling problems on graphs with arbitrary-length edges and possibly imperfect intrusion detection. The core ingredient is an efficient algorithm for computing the value and the gradient of a function assigning to every strategy its "protection" achieved. This allows for designing an efficient strategy improvement algorithm by differentiable programming and optimization techniques. Our method is the first one applicable to real-world patrolling graphs of reasonable sizes. It outperforms the state-of-the-art strategy synthesis algorithm by a margin.
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。
