Papers
14
Total Citations
291
H-Index
9
About
Kevin Gold is a pioneer in developmental robotics, with his research bridging machine self-awareness, grounded language acquisition, and human-robot interaction. His most influential work tackles the fundamental problem of robotic self-recognition, where he developed probabilistic methods allowing humanoid robots to distinguish their own motion from that of other agents—a capability once thought to require social understanding. His seminal 2005 paper on motion-based self-recognition (61 citations) and his Bayesian model for mirror self-recognition (26 citations) established a computational foundation for machine self-other distinction. Gold also made significant contributions to robotic language learning, creating systems like TWIG that enable robots to infer word meanings from context and learn pronouns through grounded semantics. His work on learning "windows of contingency" (23 citations) advanced how robots reason about causal relationships in dynamic environments. With over 250 cumulative citations across his most-cited papers, Gold's research has influenced both robotics and cognitive science, demonstrating how robots can bootstrap complex social and linguistic capabilities from simple perceptual-motor experiences.
Research Focus
Key Achievements
Top Papers
- 1Motion-based robotic self-recognition61 citations · 2005
- 2Using probabilistic reasoning over time to self-recognize48 citations · 2008
- 3Robotic vocabulary building using extension inference and implicit contrast31 citations · 2008
- 4A Bayesian Robot That Distinguishes "Self" from "Other"26 citations · 2007
- 5Learning acceptable windows of contingency23 citations · 2006
- 6
- 7Learning grounded semantics with word trees: Prepositions and pronouns18 citations · 2007
- 8An information pipeline model of human-robot interaction17 citations · 2009
- 9Social development12 citations · 2006
- 10Using context and sensory data to learn first and second person pronouns8 citations · 2006