ActorNetwork.py 文件源码

def create_actor_network(self, state_size,action_dim):
        print("Now we build the model")
        S = Input(shape=[state_size])   
        h0 = Dense(HIDDEN1_UNITS, activation='relu')(S)
        h1 = Dense(HIDDEN2_UNITS, activation='relu')(h0)
        # Steering = Dense(1,activation='tanh',init=lambda shape:VarianceScaling(scale=1e-4)(shape))(h1)  
        # Acceleration = Dense(1,activation='sigmoid',lambda shape:VarianceScaling(scale=1e-4)(shape))(h1)   
        # Brake = Dense(1,activation='sigmoid',lambda shape:VarianceScaling(scale=1e-4)(shape))(h1)
        Steering = Dense(1,activation='tanh')(h1)  
        Acceleration = Dense(1,activation='sigmoid')(h1)   
        Brake = Dense(1,activation='sigmoid')(h1)
        # V = merge([Steering,Acceleration,Brake],mode='concat')
        V = layers.concatenate([Steering,Acceleration,Brake])          
        model = Model(inputs=S,outputs=V)
        return model, model.trainable_weights, S