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Reinforcement learning and dynamic programming using function approximators /
From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dyn...
| Clasificación: | Libro Electrónico |
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| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
CRC Press,
[2010]
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| Colección: | Automation and control engineering.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- ch. 1. Introduction
- ch. 2. An introduction to dynamic programming and reinforcement learning
- ch. 3. Dynamic programming and reinforcement learning in large and continuous spaces
- ch. 4. Approximate value iteration with a fuzzy representation
- ch. 5. Approximate policy iteration for online learning and continuous-action control
- ch. 6. Approximate policy search with cross-entropy optimization of basis functions.