Analyzing Multi-agent Activity Logs Using Process Mining Techniques

被引：13

作者：

Rozinat, A. ^{[1
,2
]}

Zickler, S. ^{[2
]}

Veloso, M. ^{[2
]}

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

McMillen, C. ^{[2
]}

机构：

[1] Eindhoven Univ Technol, Informat Syst Grp, POB 513, NL-5600 MB Eindhoven, Netherlands

[2] Carnegie Mellon Univ, Dept Comp Sci, Pittsburgh, PA 15213 USA

来源：

DISTRIBUTED AUTONOMOUS ROBOTIC SYSTEMS 8 | 2009年

关键词：

D O I：

10.1007/978-3-642-00644-9_22

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Distributed autonomous robotic systems exhibit complex behavior that-although programmed, but due to the impact of the environment-only materializes as the process unfolds. Thus, the actual behavior of such a system cannot be known in advance but must be observed to be evaluated or verified. In this paper we propose to use process mining techniques to extract, compare, and enhance models of the actual behavior of a multi-agent robotic system through analyzing collected log data. We use the example of robot soccer as such a multi-agent robotic system, and we demonstrate which types of analysis are currently possible in the context of the process mining tool set ProM.

引用

页码：251 / +

页数：2

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