Publication Details

Sindhgatta, R., ter Hofstede, A. & Ghose, A. (2020). Resource-Based Adaptive Robotic Process Automation: Formal/Technical Paper. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12127 LNCS 451-466.


© Springer Nature Switzerland AG 2020. Robotic process automation is evolving from robots mimicking human workers in automating information acquisition tasks, to robots performing human decision tasks using machine learning algorithms. In either of these situations, robots or automation agents can have distinct characteristics in their performance, much like human agents. Hence, the execution of an automated task may require adaptations with human participants executing the task when robots fail, to taking a supervisory role or having no involvement. In this paper, we consider different levels of automation, and the corresponding coordination required by resources that include human participants and robots. We capture resource characteristics and define business process constraints that support process adaptations with human-automation coordination. We then use a real-world business process and incorporate automation agents, compute resource characteristics, and use resource-aware constraints to illustrate resource-based process adaptations for its automation.



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