Information Compression by Multiple Alignment, Unification and Search as a Unifying Principle in Computing and Cognition

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dc.creatorWolff, J Gerard
dc.date2003-07-10
dc.date.accessioned2026-07-07T03:20:01Z
dc.date.available2026-07-07T03:20:01Z
dc.descriptionThis article presents an overview of the idea that "information compression by multiple alignment, unification and search" (ICMAUS) may serve as a unifying principle in computing (including mathematics and logic) and in such aspects of human cognition as the analysis and production of natural language, fuzzy pattern recognition and best-match information retrieval, concept hierarchies with inheritance of attributes, probabilistic reasoning, and unsupervised inductive learning. The ICMAUS concepts are described together with an outline of the SP61 software model in which the ICMAUS concepts are currently realised. A range of examples is presented, illustrated with output from the SP61 model.
dc.identifierhttps://arxiv.org/abs/cs/0307025
dc.identifierhttp://arxiv.org/abs/cs/0307025
dc.identifierArtificial Intelligence Review 19(3), 193-230, 2003
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/31692
dc.subjectArtificial Intelligence
dc.subjectI.2.0
dc.titleInformation Compression by Multiple Alignment, Unification and Search as a Unifying Principle in Computing and Cognition
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