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This workshop, held in Rome from September 22-24, 2008, delves into the crucial relationship between action and language in understanding symbol grounding and effective communication. Key topics include the expressive power of natural language, the Church-Turing thesis, and the performance of human cognition. It investigates how language functions significantly beyond mere words, requiring grounding in sensorimotor experiences. Attendees explored challenges in designing systems capable of passing the Turing Test while integrating grounded meaning based on cognitive and linguistic principles.
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Symbol Grounding, Turing Testing and Robot Talking Harnad, S; Blondin-Massé; A, St-Louis, B; Chicoisne, G; Gargouri, Y; & Picard, O. RoadMap Workshop on Action and Language Integration Rome, 22-24 September 2008.
Associations vs. Propositions • The expressive power of natural language • The Church/Turing Thesis about the expressive power of computation • The performance power of human cognition • The Turing Test • Toy models and underdetermination
Pantomime vs. Propositions • Doing, Showing and Telling • Truth values (T & F) • Categories and category acquisition: Learning to do the right thing with the right kind of thing • Sensorimotor affordances • Naming and describing/defining/explaining
Symbol Grounding • Language has limitless expressive power, but it cannot be words all the way down • Words need to be grounded in sensorimotor categorization capacity • Wittgenstein’s “meaning is use” is empty: how to design a system that can use words as humans can? • Design a system that can pass the Turinf Test
Grounding Dictionary Meaning • (Switch to PDFs….) • Based on the MRC Psycholinguistic Database that the words in our grounding kernel are significantly more concrete and are acquired at a significantly earlier age than the words in the rest of the dictionary
ERPS During Sensorimotor Category Learning • (Switch to PDFs….) • Based on how prior ERP findings, these results suggest: (1) The positivity reflects the subject’s confidence in categorizing the stimuli, which depends on difficulty and improves (and accelerates) with practice. (2) The negative peak reflects improved detection of the category invariants with practice, with reduced efficiency on incorrect trials.