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AI and Similarity
May/June 2006 (vol. 21 no. 3)
pp. 39-49
Edwina L. Rissland, University of Massachusetts
For AI to become truly robust, we must further our understanding of similarity-driven reasoning, analogy, learning, and explanation. Here are some suggested research directions.This article is part of a special issue on the Future of AI.
Index Terms:
similarity, explanation, examples, concepts, concept change, case-based reasoning, hypotheticals, open-texture, AI and law
Citation:
Edwina L. Rissland, "AI and Similarity," IEEE Intelligent Systems, vol. 21, no. 3, pp. 39-49, May-June 2006, doi:10.1109/MIS.2006.38
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