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optimizer = Adam(learning_rate=0.01)
state = enviroment.reset()
agent = Agent(enviroment, optimizer, state.shape)
batch_size = 32
num_of_episodes = 1000
timesteps_per_episode = 1000
agent.q_network.summary()
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