public void FromIntList(IEnumerator <int> list)
{
subnetNeurons = list.Current;
list.MoveNext();
layers = list.Current;
list.MoveNext();
baseConnNum = list.Current;
list.MoveNext();
inputOutputConnNum = list.Current;
list.MoveNext();
EmotionState = list.Current;
list.MoveNext();
Init();
subNets = new NeuronCluster[list.Current];
list.MoveNext();
for (int i = 0; i < subNets.Length; i++)
{
subNets[i] = NeuronCluster.FromIntList(list);
}
connections = new NNConnection[list.Current];
list.MoveNext();
for (int i = 0; i < connections.Length; i++)
{
connections[i] = NNConnection.FromIntList(list);
}
}
public void DoTimestep()
{
if (EmotionState > 0)
{
EmotionState--;
}
else if (EmotionState < 0)
{
EmotionState++;
}
int finalEmotionState = (EmotionState > EMOTION_MAGNITUDE_THRESH ? 1 : (EmotionState < -EMOTION_MAGNITUDE_THRESH ? -1 : 0));
// First, copy inputs / connection values into all subnets
for (int i = 0; i < connections.Length; i++)
{
NNConnection conn = connections[i];
NeuronCluster srcNet = subNets[conn.srcNet];
// destNet can be -1, which means access the IO ports
if (conn.destNet >= 0)
{
NeuronCluster destNet = subNets[conn.destNet];
srcNet.SetExternalInput(conn.srcIdx, destNet.GetExternalOutput(conn.destIdx));
destNet.SetExternalInput(conn.destIdx, srcNet.GetExternalOutput(conn.srcIdx));
}
else
{
srcNet.SetExternalInput(conn.srcIdx, inputVector[conn.destIdx]);
// copy outputs after processing
// outputVector[conn.destIdx] = srcNet.GetExternalOutput(conn.srcIdx);
}
}
// Second, subnets process based on emotional state
for (int i = 0; i < subNets.Length; i++)
{
subNets[i].FullTimestep(finalEmotionState);
}
// Third, set outputs
for (int i = 0; i < connections.Length; i++)
{
NNConnection conn = connections[i];
// destNet must be -1
if (conn.destNet != -1)
{
continue;
}
NeuronCluster srcNet = subNets[conn.srcNet];
outputVector[conn.destIdx] = srcNet.GetExternalOutput(conn.srcIdx);
}
}
public static NeuronCluster FromIntList(IEnumerator <int> list)
{
int numNeurons = list.Current;
list.MoveNext();
int numExposed = list.Current;
list.MoveNext();
NeuronCluster result = new NeuronCluster(numNeurons, numExposed);
for (int i = 0; i < numExposed; i++)
{
result.externalInputs[i] = list.Current;
list.MoveNext();
}
for (int i = 0; i < numExposed; i++)
{
result.externalOutputs[i] = list.Current;
list.MoveNext();
}
for (int i = 0; i < numNeurons; i++)
{
result.activations[i] = list.Current;
list.MoveNext();
}
for (int i = 0; i < numNeurons; i++)
{
result.cooldowns[i] = list.Current;
list.MoveNext();
}
for (int i = 0; i < numNeurons; i++)
{
for (int j = 0; j < numNeurons; j++)
{
result.connections[i][j] = list.Current;
list.MoveNext();
}
}
return(result);
}
private void Init()
{
inputVector = new int[InputOutputConnTotal];
outputVector = new int[InputOutputConnTotal];
subNets = new NeuronCluster[(int)Mathf.Pow(2, layers) - 1];
List <NNConnection> listConnections = new List <NNConnection>();
for (int layer = 0; layer < layers; layer++)
{
int startIdx = (int)Mathf.Pow(2, layer) - 1;
int endIdx = (int)Mathf.Pow(2, layer + 1) - 1;
for (int i = startIdx; i < endIdx; i++)
{
int exposed = 3 * baseConnNum;
if (layer == layers - 1)
{
exposed = inputOutputConnNum + baseConnNum;
}
else if (layer == 0)
{
exposed = 2 * baseConnNum;
}
subNets[i] = new NeuronCluster(subnetNeurons, exposed);
// set up connections. Connect first 2 * base to the lower layer and last 1 * base to the higher layer
// top layer only has the 2 * base to the lower layer
// the index of the net in the next layer is the index of this one times two, and times two plus one
int idxInLayer = i - startIdx;
if (layer < layers - 1)
{
int destNetIdx = endIdx + 2 * idxInLayer;
int destConnStart = 2 * baseConnNum;
if (layer == layers - 2)
{
// the dest conns on the last layer hook up differently
destConnStart = inputOutputConnNum;
}
for (int c = 0; c < baseConnNum; c++)
{
listConnections.Add(new NNConnection()
{
srcNet = i,
destNet = destNetIdx,
srcIdx = c,
destIdx = destConnStart + c,
});
}
for (int c = 0; c < baseConnNum; c++)
{
listConnections.Add(new NNConnection()
{
srcNet = i,
destNet = destNetIdx + 1,
srcIdx = baseConnNum + c,
destIdx = destConnStart + c,
});
}
}
else
{
// connect to inputs
for (int c = 0; c < inputOutputConnNum; c++)
{
listConnections.Add(new NNConnection()
{
srcNet = i,
destNet = -1, // the IO connections
srcIdx = c,
destIdx = idxInLayer * inputOutputConnNum + c,
});
}
}
}
}
connections = listConnections.ToArray();
DebugBrainViewer.inst.SetupTexture(DebugTextureWidthPixels, DebugTextureHeightPixels);
}
