Automated Enactment Tracking for Dynamic Workflows

Abstract

The notion of workflows is an established concept to coordinate the activities within an organization. However, human workflow participants typically have to explicitly report the steps taken, limiting acceptance and effectiveness of workflow technology. In the presented PhD thesis, the novel approach of automated enactment tracking is introduced to overcome this problem. Using a Multi-Agent System, the data produced during everyday activities is evaluated in a robust and flexible manner. The system applies Case-Base Reasoning to identify the tasks performed, following the principle that similar tasks produce similar data. Agents further collaborate with each other to identify processes enacted in parallel, and to compensate for missing or inaccurate information.