An adaptive work distribution mechanism based on reinforcement learning

  • Authors:

  • Zhengxing Huang;W. M. P. van der Aalst;Xudong Lu;Huilong Duan

  • Affiliations:

  • Eindhoven University of Technology, P.O. Box 513, NL-5600 MB, Eindhoven, The Netherlands and College of Biomedical Engineering and Instrument Science of Zhejiang University, The Key Laboratory of ...;Eindhoven University of Technology, P.O. Box 513, NL-5600 MB, Eindhoven, The Netherlands;College of Biomedical Engineering and Instrument Science of Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, China;College of Biomedical Engineering and Instrument Science of Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2010

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Abstract

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.