awesome-rl

Reinforcement learning resources curated

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aikorea

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Aug 10, 2015

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This is a curated collection of reinforcement learning resources including papers, books, courses, and implementations. The repository serves as a comprehensive guide for researchers and practitioners looking to learn about or work with reinforcement learning algorithms and techniques. It organizes materials by categories such as theory, applications, and specific RL methods.

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Reinforcement LearningDeep Q-Networks (DQN)Policy Gradient MethodsActor-Critic AlgorithmsMulti-Agent Reinforcement LearningInverse Reinforcement LearningDeep Reinforcement LearningQ-LearningMonte Carlo MethodsTemporal Difference LearningModel-Based Reinforcement LearningHierarchical Reinforcement LearningCloud ComputingPortfolio ManagementRecommendation SystemsRoboticsMulti-Agent SystemsRobotic Control SystemsTime SeriesResource AllocationEdge ComputingSimulation EnvironmentsSensor DataAI SafetyHealthcarePath PlanningFoundation Models for RLGamingAgentic AIImageGame AI DevelopmentAutonomous NavigationTextTrading Strategy OptimizationFinanceResearch EnvironmentTabularAutonomous Vehicles

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Project created: Aug 10, 2015
Forked: Nov 4, 2025
Your last push: 2 years ago
Upstream last push: 2 years ago
Tracked since: May 25, 2023

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