rcnfq.py 文件源码

def _init_MLP(self, mlp_layers):
        """Initialize the MLP that corresponds to the Q function.

        Parameters
        ----------
        state_dim : The state dimensionality
        nb_actions : The number of possible actions
        mlp_layers : A list consisting of an integer number of neurons for each
                     hidden layer. Default = [20, 20]
        """
        model = Sequential()
        for i in range(len(mlp_layers)):
            if i == 0:
                model.add(Dense(mlp_layers[i],
                          input_dim=self.state_dim + self.nb_actions))
            else:
                model.add(Dense(mlp_layers[i]))
            model.add(Activation('relu'))
        model.add(Dense(1))
        model.add(Activation('relu'))
        rmsprop = RMSprop()
        model.compile(loss='mean_squared_error', optimizer=rmsprop)
        return model