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Learning Appropriate Contexts

By Bruce Edmonds

Abstract

Genetic Programming is extended so that the solutions being evolved do so in the context of local domains within the total problem domain. This produces a situation where different “species” of solution develop to exploit different “niches” of the problem – indicating exploitable solutions. It is argued that for context to be fully learnable a further step of abstraction is necessary. Such contexts abstracted from clusters of solution/model domains make sense of the problem of how to identify when it is the content of a model is wrong and when it is the context. Some principles of learning to identify useful contexts are proposed

Topics: Cognitive Psychology, Artificial Intelligence, Machine Learning
Publisher: Springer-verlag
Year: 2001
OAI identifier: oai:cogprints.org:1772

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Citations

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