Artificial Intelligence, Machine Learning, Data Science, Reinforcement Learning, Deep Learning.
and status',reward,state) state = state.reshape(3) replay.append((np.array(state),action,reward,np.array(next_state),done)) state = next_state if done: break if count>batch: count = 0 batch_ = random.sample(replay,batch) current_state = tf.convert_to_tensor([x[0] for x in batch_]) next_state =