问如何在神经网络中动态设置输入/输出的数量和行为？

EN

void LearningSystem::process(int const last_frame_time) {
    std::set<unsigned int> const& learning_list = eManager->getAllEntitiesPossessingComponent(ComponentType::intelligence);

    vector<double> outputs, inputs;
    for (auto entity : learning_list) {
        Intelligence& intel = eManager->getComponent<Intelligence>(entity, ComponentType::intelligence);
        Sensors& sensor = eManager->getComponent<Sensors>(entity, ComponentType::sensors);
        Behavior& behavior = eManager->getComponent<Behavior>(entity, ComponentType::behavior);

        // calculate each input value
        for (unsigned int i = 0; i < sensor.sensor_list.size(); ++i) {
            sensor.triggers[i](sensor.sensor_list[i]);
        }

        // retrieve the inputs from the sensors...
        inputs = sensor.sensor_list;
        // ...and add the bias
        inputs.push_back(bias);

        // for each layer
        for (auto i : intel.vecLayers) {
            // clear the internal outputs
            outputs.clear();

            // for each neuron
            for (auto j : i.vecNeurons) {
                // reset the neuron value
                double neuronValue = 0.0;

                // for each weight/input pair, sum the weights * inputs
                for (auto k = j.vecWeights.begin(), in = inputs.begin(); k != j.vecWeights.end(); ++k, ++in) {
                    neuronValue += (*k) * (*in);
                }

                // store the internal outputs for use by the next layer
                outputs.push_back(sigmoid(neuronValue));
            }

            // assign the inputs for the next layer...
            inputs = outputs;
            // ...and add the bias
            inputs.push_back(bias);
        }

        behavior.values = outputs;

        // calculate actions based on output values
        for (unsigned int i = 0; i < behavior.values.size(); ++i) {
            behavior.actions[i](behavior.values[i]);
        }
    }
}