Invited talk: Melanie Mitchell, "Active Symbols and Analogy-Making: Reflections on Hofstadter & Mitchell's Copycat project"
in
Workshop: Retrospectives: A Venue for Self-Reflection in ML Research
Abstract
In our 1995 paper “The Copycat Project: A Model of Mental Fluidity and Analogy-Making”, Douglas Hofstadter and I described Copycat, a computer program that makes analogies in an idealized domain of letter strings. The goal of the project was to model the general-purpose ability of humans to fluidly perceive abstract similarities between situations. Copycat's active symbol architecture, inspired by human perception, was a unique combination of symbolic and subsymbolic components. Now, 25 years later, AI is refocusing on abstraction and analogy as core aspects of robust intelligence, and the ideas underlying Copycat have new relevance. In this talk I will reflect on these ideas, on the limitations of Copycat and its idealized domain, and on possible novel contributions of this decades-old work to current open problems in AI.