Compositional modeling: finding the right model for the job
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Analogy-making as perception: a computer model
Analogy-making as perception: a computer model
Derivational Analogy in PRODIGY: Automating Case Acquisition, Storage, and Utilization
Machine Learning - Special issue on case-based reasoning
Case-based reasoning
Flexible strategy learning: analogical replay of problem solving episodes
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
An integrated architecture for engineering problem-solving
An integrated architecture for engineering problem-solving
Case-Based Reasoning: Experiences, Lessons and Future Directions
Case-Based Reasoning: Experiences, Lessons and Future Directions
Analogy in Inductive Theorem Proving
Journal of Automated Reasoning
Dynamic Case Creation and Expansion for Analogical Reasoning
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
An analogy ontology for integrating analogical processing and first-principles reasoning
Eighteenth national conference on Artificial intelligence
Measuring the level of transfer learning by an AP physics problem-solver
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Analogical model formulation for transfer learning in AP Physics
Artificial Intelligence
Domain transfer via cross-domain analogy
Cognitive Systems Research
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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.