Making neural nets simple enough to succeed at universal relational generalization
Tuesday, November 17, 2020
16:00 UTC
Prof Kenneth Kurtz
Binghamton University
Recording
Open recording
Hosted by Analogical Minds60 minutes
Abstract
Traditional brain-style (connectionist) approaches basically hit a wall when it comes to relational cognition. As an alternative to the well-known approaches of structured connectionism and deep learning, I present an engine for relational pattern recognition based on minimalist reinterpretations of first principles of connectionism. Results of computational experiments will be discussed on problems testing relational learning and universal generalization.
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