Rule-based Evolutionary Online Learning Systems: a Principled Approach to Lcs Analysis and Design - Studies in Fuzziness and Soft Computing - Martin V. Butz - Grāmatas - Springer-Verlag Berlin and Heidelberg Gm - 9783642064777 - 2010. gada 12. februāris
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Martin V. Butz
Rule-based Evolutionary Online Learning Systems: a Principled Approach to Lcs Analysis and Design - Studies in Fuzziness and Soft Computing 1st Ed. Softcover of Orig. Ed. 2006 edition

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Rule-basedevolutionaryonlinelearningsystems,oftenreferredtoasMichig- style learning classi?er systems (LCSs), were proposed nearly thirty years ago (Holland, 1976; Holland, 1977) originally calling them cognitive systems. LCSs combine the strength of reinforcement learning with the generali- tion capabilities of genetic algorithms promising a ?exible, online general- ing, solely reinforcement dependent learning system. However, despite several initial successful applications of LCSs and their interesting relations with a- mal learning and cognition, understanding of the systems remained somewhat obscured. Questions concerning learning complexity or convergence remained unanswered. Performance in di?erent problem types, problem structures, c- ceptspaces,andhypothesisspacesstayednearlyunpredictable. Thisbookhas the following three major objectives: (1) to establish a facetwise theory - proachforLCSsthatpromotessystemanalysis,understanding,anddesign;(2) to analyze, evaluate, and enhance the XCS classi?er system (Wilson, 1995) by the means of the facetwise approach establishing a fundamental XCS learning theory; (3) to identify both the major advantages of an LCS-based learning approach as well as the most promising potential application areas. Achieving these three objectives leads to a rigorous understanding of LCS functioning that enables the successful application of LCSs to diverse problem types and problem domains. The quantitative analysis of XCS shows that the inter- tive, evolutionary-based online learning mechanism works machine learning competitively yielding a low-order polynomial learning complexity. Moreover, the facetwise analysis approach facilitates the successful design of more - vanced LCSs including Holland?s originally envisioned cognitive systems. Martin V.

280 pages, 16 black & white tables, biography

Mediji Grāmatas     Paperback Book   (Grāmata ar mīksto vāku un līmēto muguru)
Izlaists 2010. gada 12. februāris
ISBN13 9783642064777
Izdevēji Springer-Verlag Berlin and Heidelberg Gm
Lapas 280
Izmēri 156 × 234 × 15 mm   ·   408 g
Valoda Angļu  

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