reinforcement-learning-an-introduction-solutions and rl-sandbox

Both tools are independent implementations of solutions and algorithms from the same foundational textbook, making them competitors where a user would choose one or the other for studying and practicing reinforcement learning concepts.

reinforcement-learning-an-introduction-solutions
41
Emerging
rl-sandbox
34
Emerging
Maintenance 0/25
Adoption 7/25
Maturity 16/25
Community 18/25
Maintenance 0/25
Adoption 4/25
Maturity 16/25
Community 14/25
Stars: 34
Forks: 13
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stars: 6
Forks: 3
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About reinforcement-learning-an-introduction-solutions

matteocasolari/reinforcement-learning-an-introduction-solutions

Implementations for solutions to programming exercises of Reinforcement Learning: An Introduction, Second Edition (Sutton & Barto)

This project provides executable code solutions for the programming exercises found in the textbook "Reinforcement Learning: An Introduction, Second Edition" by Sutton & Barto. It takes theoretical problem descriptions from the textbook as input and produces working code implementations with corresponding result visualizations. This resource is ideal for students, researchers, or practitioners learning about reinforcement learning algorithms.

reinforcement-learning machine-learning-education algorithm-implementation AI-research computational-learning

About rl-sandbox

ocraft/rl-sandbox

Selected algorithms and exercises from the book Sutton, R. S. & Barton, A.: Reinforcement Learning: An Introduction. 2nd Edition, MIT Press, Cambridge, 2018.

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reinforcement-learning-an-introduction-solutions and rlai-exercises reinforcement-learning-an-introduction-solutions and rl_sutton_barto reinforcement-learning-an-introduction-solutions and rlai-exercises reinforcement-learning-an-introduction-solutions and rl_sutton_barto

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