标题：The Method Based on Q-Learning Path Planning in Migrating Workflow
作者：Xiao, Song; Wang, Xiao-lin
作者机构：[Xiao, Song; Wang, Xiao-lin] Shandong Univ, Sch Comp Sci & Technol, Jinan 250100, Peoples R China.
会议名称：International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC)
会议日期：DEC 20-22, 2013
来源：PROCEEDINGS 2013 INTERNATIONAL CONFERENCE ON MECHATRONIC SCIENCES, ELECTRIC ENGINEERING AND COMPUTER (MEC)
关键词：reinforcement learning; migrating path; mobile agent; social; acquaintance network
摘要：In a goal-oriented migrating workflow management system, each migrating instance is regarded as a mobile agent, the path planning for migrating instance is the path planning for mobile agent. The migrating workflow path is an ordered set of working positions that can achieve the sequence of goals carried by mobile agent. How to plan out a most efficient and most rational migrating path is one of the problems needs to be solved in the research of migrating workflow. This article puts forward a method that in a based-on social acquaintance network environment, mobile agent dynamically plan out a migrating work path by reinforcement learning. This method is suitable for the target-oriented migrating workflow management system, which can well solve the problem of the migrating path planning in the uncertain or partially observable environment of mobile agent.