Advances in Learning Classifier Systems Third International Workshop, IWLCS 2000, Paris, France, September 15-16, 2000. Revised Papers /
Learning classi er systems are rule-based systems that exploit evolutionary c- putation and reinforcement learning to solve di cult problems. They were - troduced in 1978 by John H. Holland, the father of genetic algorithms, and since then they have been applied to domains as diverse as autonomous r...
| Συγγραφή απο Οργανισμό/Αρχή: | |
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| Άλλοι συγγραφείς: | , , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2001.
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| Έκδοση: | 1st ed. 2001. |
| Σειρά: | Lecture Notes in Artificial Intelligence ;
1996 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Theory
- An Artificial Economy of Post Production Systems
- Simple Markov Models of the Genetic Algorithm in Classifier Systems: Accuracy-Based Fitness
- Simple Markov Models of the Genetic Algorithm in Classifier Systems: Multi-step Tasks
- Probability-Enhanced Predictions in the Anticipatory Classifier System
- YACS: Combining Dynamic Programming with Generalization in Classifier Systems
- A Self-Adaptive Classifier System
- What Makes a Problem Hard for XCS?
- Applications
- Applying a Learning Classifier System to Mining Explanatory and Predictive Models from a Large Clinical Database
- Strength and Money: An LCS Approach to Increasing Returns
- Using Classifier Systems as Adaptive Expert Systems for Control
- Mining Oblique Data with XCS
- Advanced Architectures
- A Study on the Evolution of Learning Classifier Systems
- Learning Classifier Systems Meet Multiagent Environments
- The Bibliography
- A Bigger Learning Classifier Systems Bibliography
- An Algorithmic Description of XCS.
