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Statistical reinforcement learning : modern machine learning approaches /
Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic reward signals with its past actions. With numerous successful applications in business intelligence, plant control, and gaming, the RL framework is ideal for deci...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
CRC Press,
[2015]
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| Colección: | Chapman & Hall/CRC machine learning & pattern recognition series.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic reward signals with its past actions. With numerous successful applications in business intelligence, plant control, and gaming, the RL framework is ideal for decision making in unknown environments with large amounts of data. Supplying an up-to-date and accessible introduction to the field, Statistical Reinforcement Learning: Modern Machine Learning Approaches presents fundamental concepts and practical algorithms of statistical reinforcement learning from th. |
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| Descripción Física: | 1 online resource (xiii, 189 pages) : illustrations |
| Bibliografía: | Includes bibliographical references (pages 183-189). |
| ISBN: | 9781439856901 1439856907 9781466549319 1466549319 1439856893 9781439856895 9780429105364 0429105363 |