Population Based Methods for Optimising Infinite Behaviours of Timed Automata

Time Pub Date : 2018-09-26 DOI:10.4230/LIPIcs.TIME.2018.22
Lewis Tolonen, T. French, Mark Reynolds
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Abstract

Timed automata are powerful models for the analysis of real time systems. The optimal infinite scheduling problem for double-priced timed automata is concerned with finding infinite runs of a system whose long term cost to reward ratio is minimal. Due to the state-space explosion occurring when discretising a timed automaton, exact computation of the optimal infinite ratio is infeasible. This paper describes the implementation and evaluation of ant colony optimisation for approximating the optimal schedule for a given double-priced timed automaton. The application of ant colony optimisation to the corner-point abstraction of the automaton proved generally less effective than a random method. The best found optimisation method was obtained by formulating the choice of time delays in a cycle of the automaton as a linear program and utilizing ant colony optimisation in order to determine a sequence of profitable discrete transitions comprising an infinite behaviour. 2012 ACM Subject Classification Theory of computation → Automata over infinite objects
基于种群的时间自动机无限行为优化方法
时间自动机是分析实时系统的强大模型。双价时间自动机的最优无限调度问题涉及寻找长期成本报酬比最小的系统的无限运行。由于离散时间自动机时会出现状态空间爆炸,因此精确计算最优无限比值是不可行的。本文描述了蚁群优化的实现和评估,以逼近给定的双价时间自动机的最优调度。蚁群优化在自动机角点提取中的应用通常不如随机方法有效。最佳优化方法是通过将自动机循环中的时间延迟的选择公式化为线性程序并利用蚁群优化来确定包括无限行为的有利可图的离散转换序列来获得的。2012 ACM学科分类计算理论→ 无限对象上的自动机
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