Information compression by multiple alignment, unification and search as a unifying principle in computing and cognition

被引:15
作者
Wolff, JG [1 ]
机构
[1] Univ Wales Bangor, Sch Informat, Bangor LL57 1UT, Gwynedd, Wales
关键词
artificial intelligence; cognitive science; computer science; concepts; epistemology; information; information compression; knowledge representation; learning; natural language; pattern recognition; perception; probabilistic reasoning; syntax;
D O I
10.1023/A:1022865729144
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This 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.
引用
收藏
页码:193 / 230
页数:38
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