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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 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.
Availability
| 7119/PUP/2018 | 006.31 SUG s c.1 | Perpustakaan Universitas Pertamina | Available |
Detail Information
| Series Title |
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| Call Number |
006.31 SUG s
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| Publisher | CRC Press : Boca Raton., 2015 |
| Collation |
xiii, 192 p. : Illust. ; 24 cm
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| Language |
English
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| ISBN/ISSN |
9781439856895
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| Classification |
006.31
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| Statement of Responsibility |
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Other version/related
No other version available






