深度强化学习入门：用TensorFlow构建你的第一个游戏AI

action = np.argmax(q[0])

# apply action, get rewards and new state

input_t, reward, game_over = env.act(action)

#If we managed to catch the fruit we add 1 to our win counter

if reward == 1:

win_cnt += 1

#Uncomment this to render the game here

#display_screen(action,3000,inputs[0])

"""

The experiences < s, a, r, s’ > we make during gameplay are our training data.

Here we first save the last experience, and then load a batch of experiences to train our model

"""

# store experience

exp_replay.remember([input_tm1, action, reward, input_t], game_over)

# Load batch of experiences

inputs, targets = exp_replay.get_batch(model, batch_size=batch_size)

# train model on experiences

batch_loss = model.train_on_batch(inputs, targets)

#sum up loss over all batches in an epoch

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