论文部分内容阅读
任务分解是多Agent系统中合作问题求解的重要步骤之一。常用任务分解方法大多是基于任务本身的特征进行的,较少考虑任务执行体Agent的特征,这样可能导致分解的任务不能实现或带来过多的协调费用。针对该问题,本文利用基于Agent能力的形式化方法对任务分解问题进行描述,将该问题转化为可行操作集的求解问题。设计了一种基于启发式算法的分解策略,并对该算法进行了性能分析和示例。
Task decomposition is one of the most important steps in solving cooperative problems in multi-agent systems. Most commonly used task decomposition methods are based on the characteristics of the task itself, and less consider the characteristics of the task execution agent, which may lead to the task of decomposition can not be achieved or bring too much coordination costs. In order to solve this problem, this paper describes the problem of task decomposition by using formal ability based on agent ability, and transforms this problem into solving problem of feasible operation set. A decomposition strategy based on heuristic algorithm is designed, and the performance analysis and examples are given.