An adaptive work distribution mechanism based on reinforcement learning

作者：Huang Zhengxing; van der Aalst W M P; Lu Xudong; Duan Huilong

来源：Expert Systems with Applications, 2010, 37(12): 7533-7541.

DOI：10.1016/j.eswa.2010.04.091

• Work distribution
• Business process
• Process condition
• Reinforcement learning
• Rough set theory

Work distribution, as an integral part of business process management, is more widely acknowledged by its importance for Process-aware Information Systems. Although there are emerging a wide variety of mechanisms to support work distribution, they less concern performance considerations and cannot balance work distribution requirements and process performance within the change of process conditions. This paper presents an adaptive work distribution mechanism based on reinforcement learning. It considers process performance goals, and then can learn, reason suitable work distribution policies within the change of process conditions. Also, learning-based simulation experiment for addressing work distribution problems of business process management is introduced. The experiment results show that our mechanism outperforms reasonable heuristic or hand-coded approaches to satisfy process performance goals and is feasible to improve current state of business process management.

• 出版日期2010-12
• 单位浙江大学