FareedKhan-dev/all-rl-algorithms
all-rl-algorithms
Implementation of all RL algorithms in a simpler way
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FareedKhan-dev
FareedKhan-dev • individual
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Mar 30, 2025
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README Summary
This repository provides simplified implementations of all major reinforcement learning algorithms in Jupyter Notebooks. It serves as an educational resource for understanding RL concepts through clean, accessible code examples. The implementations cover various RL paradigms including value-based, policy-based, and actor-critic methods.
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Reinforcement LearningQ-LearningPolicy Gradient MethodsDeep Q-NetworksActor-Critic MethodsMonte Carlo MethodsTemporal Difference LearningMulti-Armed BanditsMarkov Decision Processes
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Reinforcement LearningQ-LearningPolicy Gradient MethodsDeep Q-NetworksActor-Critic MethodsMonte Carlo MethodsTemporal Difference LearningMulti-Armed BanditsMarkov Decision ProcessesNumericalLocal DevelopmentJupyter EnvironmentRL Algorithm EducationEducational AI ResourcesRoboticsGamingLearning RL FundamentalsEducationTabularAlgorithm ComparisonFinanceResearch PrototypingJupyter Notebook
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Updated 7 months ago
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research- Quality
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Learning ResourcesPrimaryData Science & AnalyticsFinance & LegalSearch & KnowledgeOther AI / MLModel TrainingRobotics
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Jupyter Notebook100.0%
Timeline
- Project created
- Mar 30, 2025
- Forked
- Nov 4, 2025
- Your last push
- 7 months ago
- Upstream last push
- 7 months ago
- Tracked since
- Aug 29, 2025
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