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 Case-Based Reasoning


Artificial Intelligence and Legal Reasoning: A Discussion of the Field and Gardner's Book

AI Magazine

In this article, I discuss the emerging field of artificial intelligence and legal reasoning and review the new book by Anne v.d.L. Gardner, An Artificial Intelligence Approach to Legal Reasoning, published by Bradford/MIT Press (1987, 225 pp., $22.50) as the first book in its new series on the subject.


Derivational analogy: A theory of reconstructive problem solving and expertise acquisition

Classics

CMU-CS-85-115, Carnegie Mellon University. Reprinted in Michalski, R. S., Carbonell, J. G., and Mitchell, T. M., (Eds.), Machine Learning: An Artificial Intelligence Approach, volume 2, chapter 14, pages 371-392. Morgan Kaufmann Publishers. Derivational analogy, a method of solving problems based on the transfer of past experience to new probiem situations, is discussed in the context of other general approaches to problem solving. The experience transfer process consists of recreating lines of reasoning, including decision sequences and accompanying justifications, that proved effective in solving particular problems requiring similar initial analysis. The role of derivational analogy in case-based reasoning and in automated expertise acquisition is discussed.


Nearest Neighbor Pattern Classification

Classics

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