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AAAI 2006

Strategy Variations in Analogical Problem Solving

Conference Paper Machine Learning Artificial Intelligence

Abstract

While it is commonly agreed that analogy is useful in human problem solving, exactly how analogy can and should be used remains an intriguing problem. VanLehn (1998) for instance argues that there are differences in how novices and experts use analogy, but the VanLehn and Jones (1993) Cascade model does not implement these differences. This paper analyzes several variations in strategies for using analogy to explore possible sources of novice/expert differences. We describe a series of ablation experiments on an expert model to examine the effects of strategy variations in using analogy in problem solving. We provide evidence that failing to use qualitative reasoning when encoding problems, being careless in validating analogical inferences, and not using multiple retrievals can degrade the efficiency of problem-solving.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
652057728752157739