An adaptive work distribution mechanism based on reinforcement learning

被引：18

作者：

Huang, Zhengxing ^{[1
,2
]}

van der Aalst, W. M. P. ^{[1
]}

Lu, Xudong ^{[2
]}

Duan, Huilong ^{[2
]}

机构：

[1] Eindhoven Univ Technol, NL-5600 MB Eindhoven, Netherlands

[2] Zhejiang Univ, Coll Biomed Engn & Instrument Sci, Key Lab Biomed Engn, Minist Educ, Hangzhou, Zhejiang, Peoples R China

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2010年 / 37卷 / 12期

关键词：

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

D O I：

10.1016/j.eswa.2010.04.091

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：7533 / 7541

页数：9

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