20 lines
552 B
Python
20 lines
552 B
Python
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import gym
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import numpy as np
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import MountainCar_common
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env=gym.make("MountainCar-v0")
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q_table=np.load("MountainCar_qtable.npy")
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for epoch in range(1000):
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state = env.reset()
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while True:
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env.render()
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discrete_state=MountainCar_common.discretise(state)
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action=np.argmax(q_table[discrete_state])
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state, reward, done, info=env.step(action)
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if done:
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print("Essai {:05d}: {}".format(epoch, "OK" if state[0]>=env.goal_position else "raté ..."))
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break
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env.close()
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