Web: http://arxiv.org/abs/2205.02959

May 9, 2022, 1:11 a.m. | Sangwon Seo, Vaibhav V. Unhelkar

cs.LG updates on arXiv.org arxiv.org

We present Bayesian Team Imitation Learner (BTIL), an imitation learning
algorithm to model behavior of teams performing sequential tasks in Markovian
domains. In contrast to existing multi-agent imitation learning techniques,
BTIL explicitly models and infers the time-varying mental states of team
members, thereby enabling learning of decentralized team policies from
demonstrations of suboptimal teamwork. Further, to allow for sample- and
label-efficient policy learning from small datasets, BTIL employs a Bayesian
perspective and is capable of learning from semi-supervised demonstrations. We …

ai arxiv imitation learning learning semi-supervised

More from arxiv.org / cs.LG updates on arXiv.org

Data Analyst, Patagonia Action Works

@ Patagonia | Remote

Data & Insights Strategy & Innovation General Manager

@ Chevron Services Company, a division of Chevron U.S.A Inc. | Houston, TX

Faculty members in Research areas such as Bayesian and Spatial Statistics; Data Privacy and Security; AI/ML; NLP; Image and Video Data Analysis

@ Ahmedabad University | Ahmedabad, India

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC