Simple Auto‐Associative Networks Succeed at Universal Generalization of the Identity Function and Reduplication Rule
Abstract
It has become widely accepted that standard connectionist models are unable to show identity-based relational reasoning that requires universal generalization. The purpose of this brief report is to show how one of the simplest forms of such models, feed-forward auto-associative networks, satisfies two of the most well-known challenges: universal generalization of the identity function and the reduplication rule. Given the simplicity of the modeling account provided, along with the clarity of the evidence, these demonstrations invite a shift in this high-profile debate over the nature of cognitive architecture and point to a way to bridge some of the presumed gulf between characteristically symbolic forms of reasoning and connectionist mechanisms.
Farah is a Middle Eastern-Canadian sociologist from Ottawa, examining the role of social structures in fostering personal growth. Her passion is highlighting stories of human adaptability, and promoting inclusive group strategies for realizing untapped potential.