John Robert Hoare

Lockheed Martin (United States), University of Tennessee at Knoxville

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About

John Robert Hoare is a pioneer in human-robot interaction, with a career dedicated to making autonomous systems transparent, trustworthy, and truly collaborative. His foundational work centers on two critical challenges: enabling robots to explain their own decision-making, and allowing them to infer human intent for seamless teamwork. In his landmark 2012 paper, *Explaining robot actions* (74 citations), Hoare developed a system that allows robots to answer natural-language questions about their behavior—for instance, explaining a turn by stating, “I detected a person at the end of the hallway.” This work directly addresses the “black box” problem in AI, building essential trust between humans and machines. Earlier, in his 2010 study *Using on-line Conditional Random Fields to determine human intent for peer-to-peer human robot teaming* (12 citations), Hoare introduced a novel framework for implicit coordination, enabling robots to predict a human partner’s goals in real-time without explicit commands. By pioneering these explainability and intent-recognition techniques, Hoare has laid the groundwork for safer, more intuitive human-robot teams, making him a key figure in shaping how robots and people work side by side.