Skill transfer through goal-driven representation mapping

  • Authors:

  • Tolga Könik;Paul O'rorke;Dan Shapiro;Dongkyu Choi;Negin Nejati;Pat Langley

  • Affiliations:

  • Computational Learning Laboratory, Center for the Study of Language and Information, Stanford University, Stanford, CA 94305, USA;Computational Learning Laboratory, Center for the Study of Language and Information, Stanford University, Stanford, CA 94305, USA;Computational Learning Laboratory, Center for the Study of Language and Information, Stanford University, Stanford, CA 94305, USA;Computational Learning Laboratory, Center for the Study of Language and Information, Stanford University, Stanford, CA 94305, USA;Computational Learning Laboratory, Center for the Study of Language and Information, Stanford University, Stanford, CA 94305, USA;Computational Learning Laboratory, Center for the Study of Language and Information, Stanford University, Stanford, CA 94305, USA

  • Venue:
  • Cognitive Systems Research
  • Year:
  • 2009

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Abstract

In this paper, we present an approach to transfer that involves analogical mapping of symbols across different domains. We relate this mechanism to Icarus, a theory of the human cognitive architecture. Our system can transfer skills across domains hypothesizing maps between representations, improving performance in novel domains. Unlike previous approaches to analogical transfer, our method uses an explanatory analysis that compares how well a new domain theory explains previous solutions under different mapping hypotheses. We present experimental evidence that the new mechanism improves transfer over Icarus' basic learning processes. Moreover, we argue that the same features which distinguish Icarus from other architectures support representation mapping in a natural way and operate synergistically with it. These features enable our analogy system to translate a map among concepts into a map between skills, and to support transfer even if two domains are only partially analogous. We also discuss our system's relation to other work on analogy and outline directions for future research.