Effective Human-Machine Teaming through Communicative Autonomous Agents that Explain, Coach, and Convince

Effective communication is essential for human-robot collaboration to improve task efficiency, fluency, and safety. Good communication between teammates provides shared situational awareness, allowing them to adapt and improvise successfully during uncertain situations, and helps identify and remedy any potential misunderstandings in the case of incongruous mental models. This doctoral proposal focuses on improving human-agent communication by leveraging explainable AI techniques to empower autonomous agents to 1) communicate insights into their capabilities and limitations to a human collaborator, 2) coach and influence human teammates' behavior during joint task execution, and 3) successfully convince and mediate trust in human-robot interactions.