Kostenloser Versand
Bequem zahlen
Wir sind gerne für Sie daRule-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 cognitivesystems. Martin V.
Produkteigenschaften
- Artikelnummer: 9783540253792
- Medium: Buch
- ISBN: 978-3-540-25379-2
- Verlag: Springer Berlin Heidelberg
- Erscheinungstermin: 24.11.2005
- Sprache(n): Englisch
- Auflage: 2006
- Serie: Studies in Fuzziness and Soft Computing
- Produktform: Gebunden
- Gewicht: 1290 g
- Seiten: 259
- Format (B x H x T): 160 x 241 x 21 mm
- Ausgabetyp: Kein, Unbekannt
Themen
- Mathematik | Informatik
- Mathematik
- Numerik und Wissenschaftliches Rechnen
- Angewandte Mathematik, Mathematische Modelle
- Medizin | Veterinärmedizin
- Medizin | Public Health | Pharmazie | Zahnmedizin
- Klinische und Innere Medizin
- Neurologie, Klinische Neurowissenschaft
- Mathematik | Informatik
- EDV | Informatik
- Informatik
- Künstliche Intelligenz
- Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik
- Mathematik
- Numerik und Wissenschaftliches Rechnen
- Angewandte Mathematik, Mathematische Modelle