时序逻辑约束下概率环境中的增量式控制综合
Incremental Control Synthesis in Probabilistic Environments with Temporal Logic Constraints
摘要：
在本文中，我们提出了一种最优控制合成的植物，一组代理人在一个图形的环境中相互作用的方法。控制规范是作为一个时间逻辑声明的一些属性，在环境的顶点举行。工厂被假定为是确定性的，而代理的概率马尔可夫模型。我们的目标是控制植物，使满足语法共同安全的线性时序逻辑公式的概率最大化。我们提出了一个计算效率高的增量方法的基础上，时序逻辑验证是计算成本比合成。我们提出了一个案例研究，我们比较我们的方法，经典的非增量方法的计算时间和内存使用。
英文摘要：
In this paper, we present a method for optimal control synthesis of a plant that interacts with a set of agents in a graph-like environment. The control specification is given as a temporal logic statement about some properties that hold at the vertices of the environment. The plant is assumed to be deterministic, while the agents are probabilistic Markov models. The goal is to control the plant such that the probability of satisfying a syntactically co-safe Linear Temporal Logic formula is maximized. We propose a computationally efficient incremental approach based on the fact that temporal logic verification is computationally cheaper than synthesis. We present a case-study where we compare our approach to the classical non-incremental approach in terms of computation time and memory usage.
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。
