Thomas Riga
Papers
2
Total Citations
171
H-Index
2
About
Thomas Riga is a leading researcher in cognitive robotics and embodied cognition, with a primary focus on how artificial systems can acquire and ground linguistic symbols through sensorimotor interaction. His major contributions center on the development of computational models that bridge the gap between abstract symbols and physical actions, demonstrating how robots can learn language in a manner analogous to human development. Riga’s most influential work, "An Embodied Model for Sensorimotor Grounding and Grounding Transfer: Experiments With Epigenetic Robots" (2006), has garnered 161 citations, establishing a foundational framework for epigenetic robotics—a field that explores how robots can develop cognitive abilities through interaction with their environment. In this seminal paper, he shows how robots can ground symbols in action, enabling them to transfer this grounding to new contexts. Additionally, his earlier work, "The Acquisition of New Categories through Grounded Symbols: An Extended Connectionist Model" (2003), further advances connectionist approaches to category learning. Riga’s research has profound implications for creating more psychologically plausible AI, making him a pivotal figure in understanding the intersection of language, action, and robotic learning.
Research Focus
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Top Papers
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