26 lines
658 B
Python
26 lines
658 B
Python
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import gym
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import numpy as np
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import CartPole_common
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env=gym.make("CartPole-v0")
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env._max_episode_steps=5000
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q_table=np.load("CartPole_qtable.npy")
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for epoch in range(1000):
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state = env.reset()
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score = 0
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while True:
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env.render()
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discrete_state=CartPole_common.discretise(state)
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action=np.argmax(q_table[discrete_state])
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#if not np.random.randint(5):
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# action=np.random.randint(2)
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state, reward, done, info=env.step(action)
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score+=reward
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if done:
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print('Essai {:05d} Score: {:04d}'.format(epoch, int(score)))
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break
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env.close()
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