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Learning Appropriate Contexts

Edmonds, Bruce (2001) Learning Appropriate Contexts. [Conference Paper]

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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.

Item Type:Conference Paper
Keywords:learning, conditions of application, context, evolutionary computing, error
Subjects:Psychology > Cognitive Psychology
Computer Science > Artificial Intelligence
Computer Science > Machine Learning
ID Code:1772
Deposited By: Edmonds, Dr Bruce
Deposited On:30 Aug 2001
Last Modified:11 Mar 2011 08:54

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