Proceedings of the Annual Meeting of the Cognitive Science Society

We discuss the problem of transferring learned knowledge across domains, and characterize two possible approaches. Transfer through reoperationalization involves learning concepts in a domain-specific form and transferring them to other domains by recharacterizing them in each domain as necessary. Abstraction-based transfer involves learning concepts at a high level of abstraction to facilitate transferring them to other domains without recharacterization. W e discuss these approaches and present an example of the abstraction-based transfer of a method of projection, or selective lookahead, from the game of chess to the game of checkers, as implemented in our test-bed system for failure-driven learning in i)lanning domains. We then discuss a continuum of abstraction to characterize learned concepts, and propose a corresponding continuum characterizing the time at which the computation necessary for cross-domain transfer is accomplished.