Lower learning rate of a3c test for robustness

        TestPolicy(),

        max_rollout_length=50,

        optimizer=dc.models.tensorgraph.TFWrapper(

            tf.train.AdamOptimizer, learning_rate=0.005))

            tf.train.AdamOptimizer, learning_rate=0.0001))

    a3c.fit(100000)

    # It should have learned that the expected value is very close to zero, and that the best

    new_a3c = dc.rl.A3C(env, TestPolicy(), model_dir=a3c._graph.model_dir)

    new_a3c.fit(0, restore=True)

    action_prob2, value2 = new_a3c.predict([[0]])

    print(value2, value)

    assert value2 == value