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...
שמור ב:
| מחבר תאגידי: | |
|---|---|
| מחברים אחרים: | , , |
| פורמט: | Livre numérique |
| שפה: | Anglais |
| יצא לאור: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| סדרה: | Lecture notes in computer science. Lecture notes in artificial intelligence
1996 |
| נושאים: | |
| גישה מקוונת: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| הערה: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Advances in learning classifier systems, third international workshop, IWLCS 2000, Paris, France, September 15-16, 2000, revised papers, Pier Luca Lanzi, Wolfgang Stolzmann, Stewart W. Wilson (eds.), 2001, Berlin, Springer, 1 vol. (VIII-272 p.), Lecture notes in computer science, 3-540-42437-7 • Advances in Learning Classifier Systems, Texte imprimé, 9783662169148 |
תוכן הענינים:
- 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.