Combining case-based reasoning, explanation-based learning, and learning from instruction
Proceedings of the sixth international workshop on Machine learning
A computer model of case-based reasoning in problem solving: an investigation in the domain of dispute mediation (analogy, machine learning, conceptual memory)
Self-organising hierarchical retrieval in a case-agent system
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
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A case-based reasoner can frequently benefit from using pieces of multiple previous cases in the course of solving a single problem. In our model, case pieces, called snippets, are organized around the pursuit of a goal, and there are links between the pieces that preserve the structure of reasoning. The advantages of our representational approach include: 1) The steps taken in a previous case can be followed as long as they are relevant, since the connections between steps are preserved. 2) There is easy access to all parts of previous cases, so they can be directly accessed when appropriate.