Reinforcement Learning
Reference documents in Reinforcement Learning.
Documents in Reinforcement Learning
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Reinforcement Learning (RL), one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment.
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The purpose of the course is to give an overview of the Reinforcement Learning (RL) methodology, particularly as it relates to problems of optimal and suboptimal decision and control, as well as discrete optimization.
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This book provides a clear and simple account of the field's key ideas and algorithms of Reinforcement Learning (RL).
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The first comprehensive introduction to Multi-Agent Reinforcement Learning (MARL), covering MARL’s models, solution concepts, algorithmic ideas, technical challenges, and modern approaches.
