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GitHub / Pegah-Ardehkhani / Reinforcement-Learning-Algorithms-from-Scratch

Explore key RL algorithms with detailed explanations and fully commented Python code implementations

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Pegah-Ardehkhani%2FReinforcement-Learning-Algorithms-from-Scratch

Stars: 4
Forks: 0
Open issues: 0

License: mit
Language: Jupyter Notebook
Size: 2.36 MB
Dependencies parsed at: Pending

Created at: 6 months ago
Updated at: 3 months ago
Pushed at: 5 months ago
Last synced at: 3 days ago

Topics: deep-q-learning, epsilon-greedy, iterative-policy-evaluation, monte-carlo, optimistic-inital-values, policy-iteration, q-learning, reinforcement-learning, reinforcement-learning-agent, reinforcement-learning-algorithms, reinforcement-learning-environments, rl, sarsa, td-0, td-lambda, thompson-sampling, ucb1, value-iteration

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