000			01366 a2200181 4500
005			20250912103745.0
020			_a9789390394852
082			_a006.31 GRA
100			_aGraesser, Laura
245			_aFoundations of Deep Reinforcement Learning : Theory and Practice in Python
260			_bPearson India Education Services Pvt. Ltd. _aNoida _c2022
300			_a379
520			_aDeep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games-such as Go, Atari games, and DotA 2-to robotics. Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM Lab, and finishes with the practical details of getting deep RL to work. This guide is ideal for both computer science students and software engineers who are familiar with basic machine learning concepts and have a working understanding of Python.
650			_aArtificial intelligence
650			_aDeep learning
700			_aKeng, Wah Loon
942			_cBK _2ddc
999			_c51474 _d51474