Python-强化学习方法和教程
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2019-08-11
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Python-强化学习方法和教程.zip （61个子文件） 
Reinforcement-learning-with-tensorflow-master experiments Robot_arm 
arm_env.py 8KB A3C.py 8KB DDPG.py 10KB DPPO.py 8KB 2D_car DDPG.py 10KB collision.py 2KB car_env.py 8KB Solve_BipedalWalker A3C.py 8KB DDPG.py 16KB log events.out.tfevents.1490801027.Morvan 1.07MB A3C_rnn.py 10KB Solve_LunarLander A3C.py 9KB run_LunarLander.py 2KB DuelingDQNPrioritizedReplay.py 13KB LICENCE 1KB README.md 7KB contents 9_Deep_Deterministic_Policy_Gradient_DDPG DDPG.py 10KB DDPG_update2.py 6KB DDPG_update.py 6KB 11_Dyna_Q maze_env.py 4KB RL_brain.py 3KB run_this.py 1KB 12_Proximal_Policy_Optimization simply_PPO.py 6KB discrete_DPPO.py 9KB DPPO.py 8KB 5.1_Double_DQN run_Pendulum.py 2KB RL_brain.py 7KB Curiosity_Model 
Curiosity.png 123KB Random_Network_Distillation.py 6KB Curiosity.py 6KB 6_OpenAI_gym run_CartPole.py 1KB run_MountainCar.py 1KB RL_brain.py 8KB 3_Sarsa_maze maze_env.py 4KB RL_brain.py 3KB run_this.py 1KB 8_Actor_Critic_Advantage AC_continue_Pendulum.py 6KB AC_CartPole.py 6KB 7_Policy_gradient_softmax run_CartPole.py 2KB run_MountainCar.py 2KB RL_brain.py 4KB 5.3_Dueling_DQN run_Pendulum.py 2KB RL_brain.py 7KB 10_A3C A3C_RNN.py 9KB A3C_continuous_action.py 8KB A3C_distributed_tf.py 9KB A3C_discrete_action.py 8KB 2_Q_Learning_maze maze_env.py 4KB RL_brain.py 2KB run_this.py 1KB 5_Deep_Q_Network DQN_modified.py 6KB maze_env.py 4KB RL_brain.py 8KB run_this.py 1KB 5.2_Prioritized_Replay_DQN run_MountainCar.py 2KB RL_brain.py 12KB 4_Sarsa_lambda_maze maze_env.py 4KB RL_brain.py 3KB run_this.py 2KB 1_command_line_reinforcement_learning treasure_on_right.py 3KB
RL_cover.jpg 68KB资源评论
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