Rule-Based Evolutionary Online Learning Systems A Principled Approach to LCS Analysis and Design /

• Κύριος συγγραφέας: Butz, Martin V. (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.
• Σειρά: Studies in Fuzziness and Soft Computing, 191
• Θέματα: Computer science.; Neurosciences.; Computers.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Computer Science.; Theory of Computation.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).; Applications of Mathematics.

This book offers a comprehensive introduction to learning classifier systems (LCS) – or more generally, rule-based evolutionary online learning systems. LCSs learn interactively – much like a neural network – but with an increased adaptivity and flexibility. This book provides the necessary backgrou...

Πίνακας περιεχομένων:

• Prerequisites
• Simple Learning Classifier Systems
• The XCS Classifier System
• How XCS Works: Ensuring Effective Evolutionary Pressures
• When XCS Works: Towards Computational Complexity
• Effective XCS Search: Building Block Processing
• XCS in Binary Classification Problems
• XCS in Multi-Valued Problems
• XCS in Reinforcement Learning Problems
• Facetwise LCS Design
• Towards Cognitive Learning Classifier Systems
• Summary and Conclusions.