An adaptive work distribution mechanism based on reinforcement learning

Z. Huang, W.M.P. Aalst, van der, X. Lu, H. Duan

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Scopus)
1 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)7533-7541
JournalExpert Systems with Applications
Volume37
Issue number12
DOIs
Publication statusPublished - 2010

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