Human Decision Making and Social Behavior

Integrated Human Decision Making and Planning Model under Extended Belief-Desire-Intention Framework

PI: Young-Jun Son 


An integrated Belief-Desire-Intention (BDI) modeling framework is proposed for human decision making and planning for evacuation scenarios, whose submodules are based on a Bayesian belief network (BBN), Decision-Field-Theory (DFT), and a probabilistic depth first search (PDFS) technique. To mimic realistic human behaviors, attributes of the BDI framework are reverse-engineered from human-in-the-loop experiments conducted in the Cave Automatic Virtual Environment (CAVE). The proposed modeling framework has been used for various applications such as 1) evacuation behaviors under a terrorist bomb attack, 2) evacuation behaviors under fire in a factory, 3) virtual stock investment, 4) pedestrian and driver interaction, and 5) error detection and resolution by people in a complex manufacturing facility.

Link to MURI project.

Questions? Contact Young Jun Son, Ph.D. at


(NSF-SOD) A Testebed for Process-Driven and Simulation-based Knowledge Conglomeration in Enterprise Software Development

PIs: Young-Jun Son, Leon Zhao, Keith Provan and Brian McGough

Sponsor: National Science Foundation

The goal is to develop a testbed for process-driven and simulation-based knowledge conglomeration in enterprise software development, which will help software development teams to acquire, maintain, analyze, and formalize software requirements from multiple stakeholders that can have varying and possibly conflicting demands. The project is truly interdisciplinary as it consists of experts in simulation from systems engineering, social network theory experts from organizational management, knowledge workflow experts from management information systems, and a chief architect from a real world open source project.

Questions? Contact Young Jun Son, Ph.D. at

University of Arizona College of Engineering