Overview of proposed approach.

Proud of Manisha Natarajan and Chunyue Xue and happy to share the acceptance of our work entitled “Mixed-Initiative Human-Robot Teaming under Suboptimality with Online Bayesian Adaptation” at AAMAS 2024!

Full reference details: Natarajan, M., Xue, C., van Waveren, S., Feigh, K., & Gombolay, M. “Mixed-Initiative Human-Robot Teaming under Suboptimality with Online Bayesian Adaptation,” in International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2024.

Summary: In this work, we develop computational modeling and optimization techniques for enhancing the performance of suboptimal human-agent teams, where both the human and the agent act suboptimally due to incomplete environmental knowledge. We adopt an online Bayesian approach that enables a robot to infer people’s willingness to comply with its assistance in a sequential decision-making game. Our user studies show that 1) user preferences and team performance indeed vary with robot intervention styles and 2) our proposed technical approach for mixed-initiative collaborations enhances objective team performance and subjective measures, such as user’s trust and perceived likeability of the robot.