Towards probabilistic decision making on human activities modeled with business process diagrams

Abstract

Agent-based technologies, originally proposed with the aim of assisting human activities, have been recently adopted in industry for automating business processes. Business Process Model and Notation (BPMN) is a standard notation for modeling business processes that provides a rich graphical representation that can be used for common understanding of processes but also for automation purposes. We propose a normal form of Business Process Diagrams (BPDs) based on Activity Theory that can be transformed into a Causal Bayesian Network, which in turn can be used to tackle with uncertainty introduced by human participants. We illustrate our approach on an Elderly health care scenario obtained from an actual contextual study.