rnn.py 文件源码

def create_rnn():
    """Create a recurrent neural network to compute a control policy.

    Reference:
    Koutnik, Jan, Jurgen Schmidhuber, and Faustino Gomez. "Evolving deep
    unsupervised convolutional networks for vision-based reinforcement
    learning." Proceedings of the 2014 conference on Genetic and
    evolutionary computation. ACM, 2014.
    """
    model = Sequential()

    model.add(SimpleRNN(output_dim=3, stateful=True, batch_input_shape=(1, 1, 3)))
    model.add(Dense(input_dim=3, output_dim=3))

    model.compile(loss='mse', optimizer='rmsprop')

    return model