Deep Reinforcement Learning
Author | : Mohit Sewak |
Publisher | : Springer |
Total Pages | : 215 |
Release | : 2019-06-27 |
ISBN-10 | : 9789811382857 |
ISBN-13 | : 9811382859 |
Rating | : 4/5 (57 Downloads) |
Download or read book Deep Reinforcement Learning written by Mohit Sewak and published by Springer. This book was released on 2019-06-27 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand examples and applications, and then introduces the cutting-edge research advances that make reinforcement learning capable of out-performing most state-of-art systems, and even humans in a number of applications. The book not only equips readers with an understanding of multiple advanced and innovative algorithms, but also prepares them to implement systems such as those created by Google Deep Mind in actual code. This book is intended for readers who want to both understand and apply advanced concepts in a field that combines the best of two worlds – deep learning and reinforcement learning – to tap the potential of ‘advanced artificial intelligence’ for creating real-world applications and game-winning algorithms.