Reinforcement learning : a special issue of machine learning on reinforcement learning
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| Autor principal: | |
|---|---|
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado em: |
Cham :
Springer International Publishing
[20..].
Cham : Springer Nature |
| Assuntos: | |
| Acesso em linha: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Contributeurs : Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Reinforcement learning, a special issue of machine learning on reinforcement learning, edited by Richard S. Sutton, 1992, Norwell (Mass.), Kluwer Academic Publishers, 1 vol. (p. 225-395), 0-7923-9234-5 |
Sumário:
- Introduction: The Challenge of Reinforcement Learning, R.S. Sutton
- Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning, R.J. Williams
- Practical Issues in Temporal Difference Learning, G. Tesauro
- Technical Note: (Q-Learning, C.J.C.H. Watkins and P. Dayan
- Self-Improving Reactive Agents Based on Reinforcement Learning, Planning and Teaching, L.-J. Lin
- Transfer of Learning by Composing Solutions of Elemental Sequential Tasks, S. P. Singh
- The Convergence of TD( ) for General , P. Dayan
- A Reinforcement Connectionist Approach to Robot Path Finding in Non-Maze-Like Environments, J. dei R. Millán and C. Torras.
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