Abstract
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.
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Rozinat, A., Zickler, S., Veloso, M., van der Aalst, W.M.P., McMillen, C. (2009). Analyzing Multi-agent Activity Logs Using Process Mining Techniques. In: Asama, H., Kurokawa, H., Ota, J., Sekiyama, K. (eds) Distributed Autonomous Robotic Systems 8. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00644-9_22
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DOI: https://doi.org/10.1007/978-3-642-00644-9_22
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