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...
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| Format: | eBook |
| Language: | English |
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Boca Raton, FL
CRC Press
2015
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| Series: | Chapman & Hall/CRC machine learning & pattern recognition series
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| Subjects: | |
| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
| Summary: | 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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| Physical Description: | xiii, 189 pages illustrations |
| ISBN: | 1466549319 9781439856895 9781439856901 9780429105364 1439856893 9781466549319 1439856907 |