基于python的强化学习算法Implementation of Reinforcement Learning Algorithms.zip （63个子文件） 
基于python的强化学习算法reinforcement-learning-master DP 
Gamblers Problem Solution.ipynb 36KB Value Iteration.ipynb 9KB Gamblers Problem.ipynb 4KB Value Iteration Solution.ipynb 6KB Policy Evaluation Solution.ipynb 5KB Policy Iteration Solution.ipynb 8KB Policy Evaluation.ipynb 7KB README.md 3KB Policy Iteration.ipynb 11KB PolicyGradient CliffWalk Actor Critic Solution.ipynb 98KB CliffWalk REINFORCE with Baseline Solution.ipynb 104KB README.md 5KB Continuous MountainCar Actor Critic Solution.ipynb 14KB a3c train.py 4KB estimator_test.py 4KB worker_test.py 3KB policy_monitor_test.py 1KB worker.py 7KB estimators.py 7KB README.md 741B policy_monitor.py 4KB MC Blackjack Playground.ipynb 7KB Off-Policy MC Control with Weighted Importance Sampling.ipynb 5KB Off-Policy MC Control with Weighted Importance Sampling Solution.ipynb 284KB MC Control with Epsilon-Greedy Policies Solution.ipynb 252KB MC Prediction.ipynb 3KB README.md 3KB MC Prediction Solution.ipynb 508KB MC Control with Epsilon-Greedy Policies.ipynb 5KB DQN Deep Q Learning Solution.ipynb 23KB Double DQN Solution.ipynb 21KB dqn.py 16KB Deep Q Learning.ipynb 20KB .gitignore 12B README.md 3KB Breakout Playground.ipynb 20KB LICENSE 1KB __init__.py 0B FA Q-Learning with Value Function Approximation.ipynb 129KB MountainCar Playground.ipynb 29KB Q-Learning with Value Function Approximation Solution.ipynb 187KB README.md 3KB MDP README.md 3KB TD Q-Learning Solution.ipynb 134KB Cliff Environment Playground.ipynb 3KB SARSA Solution.ipynb 91KB Windy Gridworld Playground.ipynb 4KB SARSA.ipynb 64KB Q-Learning.ipynb 66KB README.md 3KB .gitignore 1KB lib atari helpers.py 829B __init__.py 1B state_processor.py 1KB plotting.py 3KB __init__.py 0B envs gridworld.py 4KB windy_gridworld.py 3KB __init__.py 0B cliff_walking.py 3KB blackjack.py 4KB Introduction README.md 1KB README.md 6KB资源评论
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