An indexing vocabulary for case-based explanation

• Authors: David B. Leake
• Venue: AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 1
• Year: 1991

The success of case-based reasoning depends on effective retrieval of relevant prior cases. If retrieval is expensive, or if the cases retrieved are inappropriate, retrieval and adaptation costs will nullify many of the advantages of reasoning from prior experience. We propose an indexing vocabulary to facilitate retrieval of explanations in a casebased explanation system. The explanations we consider are explanations of anomalies (conflicts between new situations and prior expectations or beliefs). Our vocabulary groups anomalies according to the type of information used to generate the expectations or beliefs that failed, and according to how the expectations failed. We argue that by using this vocabulary to characterize anomalies, and retrieving explanations that were built to account for similarly-characterized past anomalies, a case-based explanation system can restrict retrieval to explanations likely to be relevant. In addition, the vocabulary can be used to organize general explanation strategies that suggest paths for explanation in novel situations.