Applications of Learning Classifier Systems

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Bull, Larry (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004.
• Έκδοση: 1st ed. 2004.
• Σειρά: Studies in Fuzziness and Soft Computing, 150
• Θέματα: Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Control engineering.; Robotics.; Mechatronics.; Artificial Intelligence.; Mathematical and Computational Engineering.; Applications of Mathematics.; Control, Robotics, Mechatronics.

  This carefully edited book brings together a fascinating selection of applications of Learning Classifier Systems (LCS). The book demonstrates the utility of this machine learning technique in recent real-world applications in such domains as data mining, modeling and optimization, and control. It shows how the LCS technique combines and exploits many Soft Computing approaches into a single coherent framework to produce an improved performance over other approaches. 

 Learning Classifier Systems: A Brief Introduction -- Section 1 - Data Mining -- Data Mining using Learning Classifier Systems -- NXCS Experts for Financial Time Series Forecasting -- Encouraging Compact Rulesets from XCS for Enhanced Data Mining -- Section 2 - Modelling and Optimization -- The Fighter Aircraft LCS: A Real-World, Machine Innovation Application -- Traffic Balance using Learning Classifier Systems in an Agent-based Simulation -- A Multi-Agent Model of the UK Market in Electricity Generation -- Exploring Organizational-Learning Oriented Classifier Systems in Real-World Problems -- Section 3 - Control -- Distributed Routing in Communication Networks using the Temporal Fuzzy Classifier System - a Study on Evolutionary Multi-Agent Control -- The Development of an Industrial Learning Classifier System for Data-Mining in a Steel Hop Strip Mill -- Application of Learning Classifier Systems to the On-Line Reconfiguration of Electric Power Distribution Networks -- Towards Distributed Adaptive Control for Road Traffic Junction Signals using Learning Classifier Systems -- Bibliography of Real-World Classifier Systems Applications.