Pii: S0364-0213(01)00035-0

نویسندگان

  • Ron Sun
  • Edward Merrill
  • Todd Peterson
چکیده

This paper presents a skill learning model CLARION. Different from existing models of mostly high-level skill learning that use a top-down approach (that is, turning declarative knowledge into procedural knowledge through practice), we adopt a bottom-up approach toward low-level skill learning, where procedural knowledge develops first and declarative knowledge develops later. Our model is formed by integrating connectionist, reinforcement, and symbolic learning methods to perform on-line reactive learning. It adopts a two-level dual-representation framework (Sun, 1995), with a combination of localist and distributed representation. We compare the model with human data in a minefield navigation task, demonstrating some match between the model and human data in several respects. © 2001 Cognitive Science Society, Inc. All rights reserved.

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تاریخ انتشار 1999