Unsupervised Learning in a Framework of Information Compression by Multiple Alignment, Unification and Search

Details Unsupervised Learning in a Framework of Information Compression by Multiple Alignment, Unification and Search Unsupervised Learning in a Framework of Information Compression by Multiple Alignment, Unification and Search

2003-02-12

arxiv.org/abs/cs/0302015v1

Computer Science

Artificial Intelligence

39 pages, 1 JPEG figure

Scientific paper

This paper describes a novel approach to unsupervised learning that has been
developed within a framework of "information compression by multiple alignment,
unification and search" (ICMAUS), designed to integrate learning with other AI
functions such as parsing and production of language, fuzzy pattern
recognition, probabilistic and exact forms of reasoning, and others.

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