Made neural net recurrent

1 files changed, 23 insertions, 8 deletions

diff --git a/src/brain/neural_network.cpp b/src/brain/neural_network.cpp
index 9061194..f3753f7 100644
--- a/src/brain/neural_network.cpp
+++ b/src/brain/neural_network.cpp
@@ -8,11 +8,11 @@ NeuralNetwork::NeuralNetwork(std::istream &&networkConfigFile, int numberOfSenso
     
     for (int i=0; i<numberOfSensors; ++i)
     {
-	_sensors[i] = std::make_shared<Sensor>(i);
+	_sensors[i] = std::make_shared<Sensor>();
     }
     for (int i=0; i<numberOfOutputs; ++i)
     {
-	auto output = std::make_shared<Neuron>(i);
+	auto output = std::make_shared<Neuron>();
 	_outputs.push_back(output);
 	_neurons[i] = output;
     }
@@ -26,13 +26,13 @@ NeuralNetwork::NeuralNetwork(std::istream &&networkConfigFile, std::vector<bool>
     
     for (unsigned int i=0; i<sensorInitialValues.size(); ++i)
     {
-	auto sensor = std::make_shared<Sensor>(i);
+	auto sensor = std::make_shared<Sensor>();
 	sensor->setActivation(sensorInitialValues[i] ? 1 : 0);
 	_sensors[i] = sensor;
     }
     for (int i=0; i<numberOfOutputs; ++i)
     {
-	auto output = std::make_shared<Neuron>(i);
+	auto output = std::make_shared<Neuron>();
 	_outputs.push_back(output);
 	_neurons[i] = output;
     }
@@ -86,7 +86,7 @@ std::shared_ptr<Sensor> NeuralNetwork::findOrAddSensor(int id)
     auto sensor = _sensors[id];
     if (!sensor)
     {
-	sensor = std::make_shared<Sensor>(id);
+	sensor = std::make_shared<Sensor>();
 	_sensors[id] = sensor;
     }
     return sensor;
@@ -97,7 +97,7 @@ std::shared_ptr<Neuron> NeuralNetwork::findOrAddNeuron(int id)
     auto neuron = _neurons[id];
     if (!neuron)
     {
-	neuron = std::make_shared<Neuron>(id);
+	neuron = std::make_shared<Neuron>();
 	_neurons[id] = neuron;
     }
     return neuron;
@@ -110,9 +110,24 @@ void NeuralNetwork::setInput(int inputIndex, double activation)
 
 int NeuralNetwork::findMaxOutputIndex() const
 {
-    double currentMaxActivation = 0;
+    bool anyNodeChanged = true;
+    for (unsigned int iteration=0; anyNodeChanged && iteration<_neurons.size()*10; ++iteration)
+    {
+	anyNodeChanged = false;
+	for (auto const& neuron : _neurons)
+	{
+	    neuron.second->calculateActivation();
+	    if (neuron.second->activationChanged())
+	    {
+		anyNodeChanged = true;
+	    }
+	}
+    }
+
     int currentMaxIndex = 0;
-    for (unsigned int i=0; i<_outputs.size(); ++i)
+    double currentMaxActivation = _outputs[0]->activation();
+
+    for (unsigned int i=1; i<_outputs.size(); ++i)
     {
 	double activation = _outputs[i]->activation();
 	if (activation >= currentMaxActivation)