Entropy and information in models of learning behaviour

Belavkin, Roman V. ORCID logoORCID: https://orcid.org/0000-0002-2356-1447 (2005) Entropy and information in models of learning behaviour. AISB Quarterly, 119 . p. 5. ISSN 0268-4179 [Article]

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Abstract

Learning is an important process that allows us to reduce the uncertainty of the outcomes of our decisions or in other words the uncertainty about the utilities of decisions. Thus, through learning we can make decisions that are most beneficial to us (or at least that seem to be so). Information Theory has produced convenient apparatus to measure information transfer through a change of entropy (a measure of uncertainty). However, the notion of information cannot be easily applied to studies in experimental psychology, where learning is judged by external observations of subjects' performance in certain tasks. Modern cognitive modelling tools have allowed for bringing information theoretic concepts much closer to cognitive psychology.

Item Type: Article
Additional Information: Online quarterly newsletter
Research Areas: A. > School of Science and Technology > Computer Science
A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID: 7
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Depositing User: Repository team
Date Deposited: 08 Sep 2008 11:53
Last Modified: 30 May 2019 18:35
URI: https://eprints.mdx.ac.uk/id/eprint/7

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