Compendium of Machine Learning I: A Symbolic Learning

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A consolidation of the algorithms and methods of machine learning developed in a number of application areas for artificial intelligence, defining knowledge as new information acquired from external sources and also as skills acquisition. Briscoe and Caelli (computing, Curtin U. of Technology, Australia) cover topics in symbolic empirical learning, analytical learning, case based reasoning and analogy, integrated learning systems, and formal analysis. The sections introduce SEL and EBL, as well as the key related algorithms. The appendices contain electronic information sources, subscription lists, conferences. Includes illustrations. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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