From Dyadic to Multi-Agent Teams: Combining Empirical and Computational Approaches to Model Trust in Human-Autonomy Interaction
Abstract: Trust has been identified as one central factor in effective human-autonomy interaction. In this talk, I will first present the results of several studies examining trust dynamics in human-autonomy interaction in both dyadic and multi-agent settings. In study 1, I will present a study that identifies three properties of trust dynamics, namely continuity, negativity bias, and stabilization. The three properties characterize a human agent's trust formation and evolution process de facto. In study 2, we propose a computational model of trust dynamics that adheres to the three properties and evaluate the computational model against existing trust inference models. In study 3, I will showcase our recent progress on trust molding in multi-human multi-robot settings.
Biography: Dr. X. Jessie Yang is an Associate Professor and a Richard Wilson faculty fellow in the Department of Industrial and Operations Engineering and the Department of Robotics, University of Michigan. Dr. Yang obtained her PhD in Mechanical & Aerospace Engineering (Human Factors) and her BEng in Electrical and Electronic Engineering, both from Nanyang Technological University, Singapore. Dr. Yang's research interests include human-autonomy/robot interaction, human factors in high-risk industries, and user experience design. Her research has been supported by grants from NSF, NIH, and DoD, including an NSF CAREER award, as well as from industrial collaborations, including Boeing and GM.