Towards integrating process mining with agent-based modeling and simulation: State of the art and outlook

Agent-based modeling and simulation (ABMS) is a valuable tool for assessing complex socio-technical systems and is becoming increasingly advanced through the integration with data-driven capabilities. Process mining is an emerging data-driven discipline that combines elements from data mining and process modeling to gain insights into process execution through tasks such as process discovery, conformance checking, and process enhancement using event data. This study explores the role of process mining and its impact on the ABMS paradigm, identifying the current state of the art, gaps in the literature, and future directions for integrating process mining with ABMS. A systematic literature review is conducted to examine how ABMS and process mining techniques are jointly employed to address challenges reported in the literature. From an initial pool of 189 publications, a final set of 20 papers was synthesized, their primary contributions were discussed, and open issues and challenges for future research were identified. Although the integrated field of process mining and ABMS shows an upward trend in publications, it remains modest and requires further efforts to achieve synergistic improvements in socio-technical systems. The findings offer initial guidance for promising research directions.