Statistical Reinforcement Learning :

Statistical Reinforcement Learning : modern machine learning approaches Sugiyama, Masashi Primary Author mixed material bibliography Boca Raton CRC Press 2015 en English xiii, 192 p. : Illust. ; 24 cm 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. Reinforcement learning Machine learning--Mathematical models 006.31 9781439856895 e-Library Universitas Pertamina Be Global Leader 006.31 SUG s 7119/PUP/2018 Perpustakaan Universitas Pertamina 006.31 SUG s c.1 Statistical_Reinforcement_Learning.jpg.jpg 3849 2018-11-30 12:55:02 2018-12-06 16:18:10 machine generated