Reinforcement Learning: State-of-the-Art (Adaptation, Learning, and Optimization, 12)

Looking to stay ahead of the game in the world of artificial intelligence and adaptive behavior? Look no further than Reinforcement Learning: State-of-the-Art. This book is not just your average read; it's a comprehensive guide to understanding the science of adaptive behavior and the computational methodology behind finding optimal behaviors for challenging problems in control, optimization, and intelligent agents. With contributions from young experts in seventeen different subfields, it truly represents the state-of-the-art of current reinforcement learning research.

Don't miss out on the latest advancements in reinforcement learning. This book covers a wide range of topics, including partially observable environments, hierarchical task decompositions, and predictive state representations. It also dives into transfer learning, evolutionary methods, and continuous spaces in reinforcement learning. Whether you're interested in robotics, games, or computational neuroscience, Reinforcement Learning: State-of-the-Art has got you covered.

Authored by Marco Wiering and Martijn van Otterlo, two esteemed professionals in the field, this book is a must-have for anyone involved in artificial intelligence research. Marco Wiering, from the University of Groningen in the Netherlands, brings a wealth of knowledge and experience to the table with his extensive research on various reinforcement learning topics. Martijn van Otterlo, from Radboud University Nijmegen, is a recognized expert in expressive knowledge representation in reinforcement learning settings. Together, their expertise ensures that Reinforcement Learning: State-of-the-Art is a truly comprehensive and up-to-date resource.

Stay at the forefront of the latest advancements in reinforcement learning. Order your copy of Reinforcement Learning: State-of-the-Art today and unlock the potential of adaptive behavior and intelligent agents!

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