Nikolos Gurney

University of Southern California, Creative Technologies (United States)

Papers

Total Citations

H-Index

About

Nikolos Gurney is a leading researcher at the intersection of artificial intelligence, cognitive robotics, and human-robot interaction. His primary focus lies in equipping autonomous systems with advanced social cognition, most notably **Theory of Mind (ToM)**—the ability to infer the mental states, beliefs, and intentions of human partners. In his highly cited 2022 survey, “Robots with Theory of Mind for Humans,” Gurney systematically reviewed the state-of-the-art in modeling ToM for AI, establishing a foundational roadmap for creating more intuitive and socially aware robots. This work has garnered 14 citations and is widely considered essential reading in the field. Beyond theory, Gurney tackles the critical challenge of **explainable AI** in human-robot teams. His influential paper on “Explainable Reinforcement Learning in Human-Robot Teams” (8 citations) demonstrates how decision-tree explanations can dramatically improve system transparency, allowing humans to understand and trust the rationale behind a robot’s actions. This research directly addresses the “black-box” problem of deep reinforcement learning, bridging the gap between complex algorithms and practical, collaborative teamwork. Gurney’s work is shaping a future where robots are not just functional, but genuinely understandable partners.