private void AddSynapses()
{
Init();
ClearNeurons(false);
mv.GetNeuronAt(0, 0).Label = "Rd";
mv.GetNeuronAt(1, 0).Label = "Clr";
mv.GetNeuronAt(0, 0).AddSynapse(mv.GetNeuronAt(1, 0).id, 1);
for (int i = 1; i < mv.Height; i++)
{
Neuron n0 = mv.GetNeuronAt(0, i);
n0.Label = "I" + (i - 1).ToString();
Neuron n1 = mv.GetNeuronAt(1, i);
Neuron n2 = mv.GetNeuronAt(2, i);
n2.Label = "O" + (i - 1).ToString();
n2.Model = Neuron.modelType.LIF;
n2.LeakRate = 0.9f;
GetNeuron("Rd").AddSynapse(n1.id, 0.9f);
GetNeuron("Clr").AddSynapse(n1.id, -1);
GetNeuron("Clr").AddSynapse(n2.id, 0.5f);
n0.AddSynapse(n1.id, 0.9f);
n1.AddSynapse(n0.id, 1);
n1.AddSynapse(n2.id, 0.5f);
}
}
private void SetUpNeurons(int levelCount)
{
Neuron nIn = na.GetNeuronAt(1, 0);
nIn.Label = "In";
Neuron nRd = na.GetNeuronAt(0, 0);
nRd.Label = "Rd";
Neuron nClr = na.GetNeuronAt(2, 0);
nClr.Label = "Clr";
nRd.AddSynapse(nClr.id, 1);
Neuron nLast = na.GetNeuronAt(0, na.Height - 1);
for (int i = 0; i < levelCount; i++)
{
Neuron ni = na.GetNeuronAt(0, i + 1);
ni.Clear();
Neuron nm = na.GetNeuronAt(1, i + 1);
ni.Clear();
Neuron no = na.GetNeuronAt(2, i + 1);
no.Clear();
}
for (int i = 0; i < levelCount; i++)
{
Neuron ni = na.GetNeuronAt(0, i + 1);
ni.Model = Neuron.modelType.LIF;
ni.LeakRate = theLeakRate;
Neuron nm = na.GetNeuronAt(1, i + 1);
Neuron no = na.GetNeuronAt(2, i + 1);
no.Label = "O" + i;
ni.AddSynapse(nm.id, 1);
nm.AddSynapse(no.id, 0.9f);
no.AddSynapse(nm.id, 1);
nClr.AddSynapse(no.id, -1f);
nRd.AddSynapse(no.id, 0.9f);
nLast.AddSynapse(no.id, -1f);
float weight = GetWeight(4 + i);
weight += .001f; //differentiates between < and =
nIn.AddSynapse(ni.id, weight);
for (int j = i + 1; j < levelCount; j++)
{
ni.AddSynapse(na.GetNeuronAt(1, j + 1).id, -1f);
}
for (int j = 0; j < levelCount; j++)
{
if (j != i)
{
ni.AddSynapse(na.GetNeuronAt(0, j + 1).id, -1f);
}
}
}
}
public override void Initialize()
{
pending.Clear();
na.GetNeuronAt(0, 0).Label = "Stop";
na.GetNeuronAt(1, 0).Label = "Done";
na.GetNeuronAt(2, 0).Label = "TurnTo";
na.GetNeuronAt(3, 0).Model = Neuron.modelType.FloatValue;
na.GetNeuronAt(3, 0).Label = "Theta";
na.GetNeuronAt(4, 0).Label = "MoveTo";
na.GetNeuronAt(5, 0).Model = Neuron.modelType.FloatValue;
na.GetNeuronAt(5, 0).Label = "R";
na.GetNeuronAt(6, 0).Label = "Scan";
na.GetNeuronAt(9, 0).Label = "Coll";
na.GetNeuronAt(10, 0).Label = "CollAngle";
na.GetNeuronAt(10, 0).Model = Neuron.modelType.FloatValue;
//Connect Neurons to the UKS
Neuron nUKSDone = GetNeuron("Module2DUKS", "Done");
if (nUKSDone != null)
{
na.GetNeuronAt("Done").AddSynapse(nUKSDone.Id, 1);
}
Neuron nUKSStop = GetNeuron("UKSOut", "Stop");
if (nUKSStop != null)
{
nUKSStop.AddSynapse(na.GetNeuronAt("Stop").Id, 1);
}
}
public void Neuron_RemoveSynapse_AllConnectionsRemoved_ValuesCorrect()
{
var inputNeuron = new Neuron(null, 1);
var outputNeuron = new Neuron(ActivationFunctions.LineairTruncated, 0);
inputNeuron.AddSynapse(outputNeuron, 1);
Assert.IsEmpty(inputNeuron.InputSynapses);
Assert.AreEqual(1, inputNeuron.OutputSynapses.Count());
Assert.AreEqual(1, outputNeuron.InputSynapses.Count());
Assert.IsEmpty(outputNeuron.OutputSynapses);
inputNeuron.SetValue(1);
Assert.AreEqual(new Scalar(1), outputNeuron.GetValue());
inputNeuron.RemoveSynapse(outputNeuron);
Assert.IsEmpty(inputNeuron.InputSynapses);
Assert.IsEmpty(inputNeuron.OutputSynapses);
Assert.IsEmpty(outputNeuron.InputSynapses);
Assert.IsEmpty(outputNeuron.OutputSynapses);
Assert.AreEqual(new Scalar(0), outputNeuron.GetValue());
Assert.AreEqual(new Scalar(1), inputNeuron.GetValue());
}
//fill this method in with code which will execute once
//when the module is added, when "initialize" is selected from the context menu,
//or when the engine restart button is pressed
public override void Initialize()
{
na.BeginEnum();
for (Neuron n = na.GetNextNeuron(); n != null; n = na.GetNextNeuron())
{
n.Label = "";
n.DeleteAllSynapes();
}
Neuron n1 = na.GetNeuronAt(0);
n1.Label = "good";
Neuron n1Target = GetNeuron("Module2DUKS", "Positive");
if (n1Target != null)
{
n1.AddSynapse(n1Target.Id, 1);
}
Neuron n2 = na.GetNeuronAt(1);
n2.Label = "no";
Neuron n2Target = GetNeuron("Module2DUKS", "Negative");
if (n2Target != null)
{
n2.AddSynapse(n2Target.Id, 1);
}
}
private void AddSynapse(string word, string nextWord)
{
word = TrimPunctuation(word);
nextWord = TrimPunctuation(nextWord);
wordDictionary.TryGetValue(word, out int wordNeuronID);
if (wordNeuronID == 0) // if there is no neuron for the word, add one
{
wordDictionary.Add(word, nextFreeNeuron);
wordNeuronID = nextFreeNeuron++;
na.GetNeuronAt(wordNeuronID).Label = word; //useful someday
}
wordDictionary.TryGetValue(nextWord, out int nextWordNeuronID);
if (nextWordNeuronID == 0) // if there is no neuron for the word, add one
{
wordDictionary.Add(nextWord, nextFreeNeuron);
nextWordNeuronID = nextFreeNeuron++;
na.GetNeuronAt(nextWordNeuronID).Label = nextWord; //useful someday
}
Neuron n = na.GetNeuronAt(wordNeuronID);
Neuron nNext = na.GetNeuronAt(nextWordNeuronID);
Synapse s = n.FindSynapse(nNext.id);
float weight = .1f;
if (s != null)
{
weight += .1f;
}
n.AddSynapse(nNext.id, weight);
}
//fill this method in with code which will execute once
//when the module is added, when "initialize" is selected from the context menu,
//or when the engine restart button is pressed
public override void Initialize()
{
foreach (Neuron n in mv.Neurons)
{
n.Label = "";
n.DeleteAllSynapes();
}
Neuron n1 = mv.GetNeuronAt(0);
n1.Label = "good";
Neuron n1Target = GetNeuron("Module2DUKS", "Positive");
if (n1Target != null)
{
n1.AddSynapse(n1Target.Id, 1);
}
Neuron n2 = mv.GetNeuronAt(1);
n2.Label = "no";
Neuron n2Target = GetNeuron("Module2DUKS", "Negative");
if (n2Target != null)
{
n2.AddSynapse(n2Target.Id, 1);
}
}
//fill this method in with code which will execute once
//when the module is added, when "initialize" is selected from the context menu,
//or when the engine restart button is pressed
public override void Initialize()
{
AddLabel("Enable");
Neuron n = AddLabel("Patterns");
n.AddSynapse(n.id, 1);
AddLabel("Output");
}
void AddSynapse(Neuron source, Neuron dest, float weight)
{
if (source == null || dest == null)
{
return;
}
source.AddSynapse(dest.id, weight);
}
//Fill this method in with code which will execute once
//when the module is added, when "initialize" is selected from the context menu,
//or when the engine restart button is pressed
public override void Initialize()
{
Neuron n = na.GetNeuronAt(0, 0);
n.Label = "FirstNeuron";
Neuron n1 = na.GetNeuronAt(0, 1);
n.AddSynapse(n1.Id, 0.5f);
}
private void _createNode()
{
var newNode = new Neuron <TFunc>();
_network.OutputLayer.Nodes.Add(newNode);
foreach (INode inputNode in _network.InputLayer.Nodes)
{
newNode.AddSynapse(new Synapse(inputNode, inputNode.Output()));
}
}
public void Neuron_SetValue_GetValueWithNextNeuron(double value)
{
var inputNeuron = new Neuron(null, 1);
var outputNeuron = new Neuron(ActivationFunctions.LineairTruncated, 0);
inputNeuron.AddSynapse(outputNeuron, 1);
inputNeuron.SetValue(value);
Assert.AreEqual(new Scalar(value), outputNeuron.GetValue());
}
void AddSynapse(string source, int sourceRow, string dest, int destRow, float weight)
{
Neuron n1 = na.GetNeuronAt(Array.IndexOf(cols, source), sourceRow);
Neuron n2 = na.GetNeuronAt(Array.IndexOf(cols, dest), destRow);
if (n1 != null && n2 != null)
{
n1.AddSynapse(n2.Id, weight);
}
}
public double Neuron_SetValue_GetValueWithNextNeuron_WithPositiveBias(double value)
{
const double BIAS = 0.5;
var inputNeuron = new Neuron(null, 1);
var outputNeuron = new Neuron(ActivationFunctions.LineairTruncated, BIAS);
inputNeuron.AddSynapse(outputNeuron, 1);
inputNeuron.SetValue(value);
return(outputNeuron.GetValue());
}
public void Neuron_SetValue_GetValueWithNextNeuron_WithWeightedSynapse(double value)
{
const double SYNAPSE_WEIGHT = 0.5;
var inputNeuron = new Neuron(null, 1);
var outputNeuron = new Neuron(ActivationFunctions.LineairTruncated, 0);
inputNeuron.AddSynapse(outputNeuron, SYNAPSE_WEIGHT);
inputNeuron.SetValue(value);
Assert.AreEqual(new Scalar(value * SYNAPSE_WEIGHT), outputNeuron.GetValue());
}
public override void Fire()
{
Init(); //be sure to leave this here
if (words.Count > 0)
{
string word = words[0];
na.BeginEnum();
for (Neuron n = na.GetNextNeuron(); n != null; n = na.GetNextNeuron())
{
if (n.Label == word)
{
n.SetValue(1);
// n.CurrentCharge = 1;
break;
}
else if (n.Label == "")
{
//the word has not been heard before, add it
n.Label = word;
n.CurrentCharge = 1;
//connection to UKS
ModuleUKSN nmUKS = (ModuleUKSN)FindModuleByType(typeof(ModuleUKSN));
if (nmUKS != null)
{
List <Thing> words = nmUKS.Labeled("Word").Children;
Thing w = nmUKS.Valued(word, words);
if (w == null)
{
string label = "w" + char.ToUpper(word[0]) + word.Substring(1);
w = nmUKS.AddThing(label, new Thing[] { nmUKS.Labeled("Word") }, word);
}
Neuron n1 = nmUKS.GetNeuron(w);
if (n1 != null)
{
n.AddSynapse(n1.Id, 1);
}
//TODO: add a synapse to the speakwords module as well
}
break;
}
}
words.RemoveAt(0);
}
}
//fill this method in with code which will execute once
//when the module is added, when "initialize" is selected from the context menu,
//or when the engine restart button is pressed
public override void Initialize()
{
if (mv == null)
{
return;
}
for (int i = 1; i < mv.Height; i++)
{
for (int j = 0; j < mv.Width; j++)
{
mv.GetNeuronAt(j, i).Model = Neuron.modelType.Color;
}
}
Neuron n1 = mv.GetNeuronAt(0, 0);
n1.Model = Neuron.modelType.IF;
n1.Label = "Enable";
n1.AddSynapse(n1.id, 1);
n1.SetValue(1);
n1 = mv.GetNeuronAt(1, 0);
n1.Model = Neuron.modelType.FloatValue;
n1.Label = "X";
n1.SetValue(0);
n1 = mv.GetNeuronAt(2, 0);
n1.Model = Neuron.modelType.FloatValue;
n1.Label = "Y";
n1.SetValue(0);
n1 = mv.GetNeuronAt(3, 0);
n1.Model = Neuron.modelType.FloatValue;
n1.Label = "Scale";
n1.SetValue(0);
n1 = mv.GetNeuronAt(4, 0);
n1.Model = Neuron.modelType.FloatValue;
n1.Label = "Rot";
n1.SetValue(0);
}
private void SetUpNeurons(int levelCount)
{
Neuron nRd = mv.GetNeuronAt(0, 0);
nRd.Label = "Rd";
Neuron nIn = mv.GetNeuronAt(1, 0);
nIn.Label = "In";
Neuron nIn1 = mv.GetNeuronAt(2, 0);
nIn1.Label = "In1";
Neuron nClr = mv.GetNeuronAt(3, 0);
nClr.Label = "Clr";
nRd.AddSynapse(nClr.id, 1);
nIn.AddSynapse(nIn1.id, 1);
for (int i = 0; i < levelCount; i++)
{
Neuron ni = mv.GetNeuronAt(0, i + 1);
ni.Clear();
Neuron ni1 = mv.GetNeuronAt(1, i + 1);
ni1.Clear();
Neuron nm = mv.GetNeuronAt(2, i + 1);
ni.Clear();
Neuron no = mv.GetNeuronAt(3, i + 1);
no.Clear();
no.model = Neuron.modelType.LIF;
no.LeakRate = 0.13f;
Neuron noP = mv.GetNeuronAt(4, i + 1);
noP.Clear();
Neuron noN = mv.GetNeuronAt(5, i + 1);
noN.Clear();
}
Neuron nLast = mv.GetNeuronAt(0, mv.Height - 1);
Neuron nLast1 = mv.GetNeuronAt(1, mv.Height - 1);
nLast.AddSynapse(nIn1.id, 0.5f);
nLast1.AddSynapse(nIn1.id, 0.5f);
for (int i = 0; i < levelCount; i++)
{
Neuron ni = mv.GetNeuronAt(0, i + 1);
ni.Model = Neuron.modelType.LIF;
ni.LeakRate = theLeakRate;
Neuron ni1 = mv.GetNeuronAt(1, i + 1);
ni1.Model = Neuron.modelType.LIF;
ni1.LeakRate = theLeakRate;
Neuron nm = mv.GetNeuronAt(2, i + 1);
Neuron no = mv.GetNeuronAt(3, i + 1);
Neuron noP = mv.GetNeuronAt(4, i + 1);
Neuron noN = mv.GetNeuronAt(5, i + 1);
noP.Label = "O" + i;
noN.Label = "O-" + i;
ni.AddSynapse(nm.id, 1);
ni1.AddSynapse(nm.id, 1);
nm.AddSynapse(no.id, 0.1f);
no.AddSynapse(nm.id, 1);
nClr.AddSynapse(noN.id, 1f);
no.AddSynapse(noN.id, -1f);
no.AddSynapse(noP.id, 1f);
nClr.AddSynapse(no.id, -1f);
nRd.AddSynapse(no.id, 0.99f);
float weight = GetWeight(4 + i);
weight += .001f; //differentiates between < and =
nIn.AddSynapse(ni.id, weight);
nIn1.AddSynapse(ni1.id, weight);
for (int j = 0; j < levelCount; j++)
{
if (j != i)
{
ni.AddSynapse(mv.GetNeuronAt(0, j + 1).id, -1f);
ni1.AddSynapse(mv.GetNeuronAt(1, j + 1).id, -1f);
}
}
}
}
//fill this method in with code which will execute once
//when the module is added, when "initialize" is selected from the context menu,
//or when the engine restart button is pressed
public override void Initialize()
{
ClearNeurons();
for (int x = 0; x < mv.Width; x += 2)
{
for (int y = 0; y < mv.Height; y += 2)
{
//three internal neurons
Neuron valueNeuron = mv.GetNeuronAt(x + 1, y);
if (valueNeuron == null)
{
continue;
}
valueNeuron.Label = "#";
Neuron liveNeuron = mv.GetNeuronAt(x, y);
if (liveNeuron == null)
{
continue;
}
liveNeuron.Label = "+";
Neuron dieNeuron = mv.GetNeuronAt(x, y + 1);
if (dieNeuron == null)
{
continue;
}
dieNeuron.Label = "-";
liveNeuron.Model = Neuron.modelType.LIF;
dieNeuron.Model = Neuron.modelType.LIF;
liveNeuron.LeakRate = 1;
dieNeuron.LeakRate = 1;
//three internal synapses
try { liveNeuron.AddSynapse(valueNeuron.Id, 1); } catch { }
try
{
dieNeuron.AddSynapse(valueNeuron.Id, -1);
}
catch { }
try
{
valueNeuron.AddSynapse(liveNeuron.Id, .4f);
}
catch { }
// add live & die synapses to the 8 surrounding neurons
// may be better to rewrite this without relying on try catch blocks.
// bottom row
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x + 2, y).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x + 2, y + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x + 2, y + 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x + 2, y + 2 + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x + 2, y - 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x + 2, y - 2 + 1).Id, .3f); } catch { }
// middle row
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x, y + 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x, y + 2 + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x, y - 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x, y - 2 + 1).Id, .3f); } catch { }
// top row
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x - 2, y).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x - 2, y + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x - 2, y + 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x - 2, y + 2 + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x - 2, y - 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(mv.GetNeuronAt(x - 2, y - 2 + 1).Id, .3f); } catch { }
}
}
}
public override void Fire()
{
Init(); //be sure to leave this here
if (synth == null)
{
return;
}
bool paused = true;
for (int i = 1; i < na.NeuronCount; i++)
{
Neuron n = na.GetNeuronAt(i);
if (n.Fired())
{
if (n.Label.Length == 1)
{
phraseToSpeak += n.Label;
paused = false;
}
if (n.Synapses.Count == 0)
{
//if a neuron fired and it has no connection, connect it to the knowledge store
//connection to KB
ModuleUKSN nmKB = (ModuleUKSN)FindModuleByType(typeof(ModuleUKSN));
if (nmKB != null)
{
string label = "pn" + n.Label;
List <Thing> phonemes = nmKB.Labeled("Phoneme").Children;
Thing pn = nmKB.Labeled(label, phonemes);
if (pn == null) //this should always be null
{
pn = nmKB.AddThing(label, new Thing[] { nmKB.Labeled("Phoneme") }, pn);
}
Neuron n1 = nmKB.GetNeuron(pn);
if (n1 != null)
{
n.AddSynapse(n1.Id, 1);
n1.SetValue(1);
}
}
}
}
}
if (phonemesToFire != "")
{
char c = phonemesToFire[0];
bool fired = false;
for (int i = 0; i < na.NeuronCount; i++)
{
Neuron n = na.GetNeuronAt(i);
if (n.Label == c.ToString())
{
n.SetValue(1);
fired = true;
break;
}
}
if (!fired)
{
Utils.Noop();
}
phonemesToFire = phonemesToFire.Substring(1);
}
if (paused && phraseToSpeak != "")
{
if (dlg != null)
{
((ModuleSpeakPhonemesDlg)dlg).SetLabel(phraseToSpeak);
}
if (na.GetNeuronAt("Enable").Fired())
{
ModuleSpeechIn msi = (ModuleSpeechIn)FindModuleByType(typeof(ModuleSpeechIn));
if (msi != null)
{
msi.PauseRecognition(); //if there is a recognizer active
}
//synth.SpeakAsync(phraseToSpeak + ".");
//phraseToSpeak = "";
PromptBuilder pb1 = new PromptBuilder();
if (typedIn)
{
pb1.StartVoice("Microsoft David Desktop");
pb1.StartStyle(new PromptStyle(PromptRate.Medium));
}
else
{
pb1.StartVoice("Microsoft Zira Desktop");
pb1.StartStyle(new PromptStyle(PromptRate.ExtraSlow));
}
pb1.AppendTextWithPronunciation("not used", phraseToSpeak);
pb1.EndStyle();
pb1.EndVoice();
string x = pb1.ToXml();
Debug.WriteLine(debugString(phraseToSpeak));
//synth.Speak(pb1);
synth.SpeakAsync(pb1);
}
//string heard = GetPronunciationFromText("", phraseToSpeak); //it would be nice to hear what was said but it doesn't work with this engine
phraseToSpeak = "";
typedIn = false;
}
}
//fill this method in with code which will execute once
//when the module is added, when "initialize" is selected from the context menu,
//or when the engine restart button is pressed
public override void Initialize()
{
ClearNeurons();
for (int x = 0; x < na.Width; x += 2)
{
for (int y = 0; y < na.Height; y += 2)
{
//three internal neurons
Neuron valueNeuron = na.GetNeuronAt(x + 1, y);
if (valueNeuron == null)
{
continue;
}
valueNeuron.Label = "#";
Neuron liveNeuron = na.GetNeuronAt(x, y);
if (liveNeuron == null)
{
continue;
}
liveNeuron.Label = "+";
Neuron dieNeuron = na.GetNeuronAt(x, y + 1);
if (dieNeuron == null)
{
continue;
}
dieNeuron.Label = "-";
liveNeuron.Model = Neuron.modelType.LIF;
dieNeuron.Model = Neuron.modelType.LIF;
liveNeuron.LeakRate = 1;
dieNeuron.LeakRate = 1;
//three internal synapses
try { liveNeuron.AddSynapse(valueNeuron.Id, 1); } catch { }
try
{
dieNeuron.AddSynapse(valueNeuron.Id, -1);
}
catch { }
try
{
valueNeuron.AddSynapse(liveNeuron.Id, .4f);
}
catch { }
//add live & die synapses to the 8 surrounding neurons
try { valueNeuron.AddSynapse(na.GetNeuronAt(x + 2, y).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x + 2, y + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x + 2, y + 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x + 2, y + 2 + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x + 2, y - 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x + 2, y - 2 + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x, y + 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x, y + 2 + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x, y - 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x, y - 2 + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x - 2, y).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x - 2, y + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x - 2, y + 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x - 2, y + 2 + 1).Id, .3f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x - 2, y - 2).Id, .4f); } catch { }
try { valueNeuron.AddSynapse(na.GetNeuronAt(x - 2, y - 2 + 1).Id, .3f); } catch { }
}
}
}
public override void Initialize()
{
ClearNeurons();
Neuron n0 = na.GetNeuronAt(1, 1);
n0.Label = "'1'";
n0.AddSynapse(n0.Id, 1, Synapse.modelType.Fixed);
n0.SetValue(1);
na.GetNeuronAt(0, 1).Label = "clr";
for (int i = 0; i < cols.Length; i++)
{
Neuron n = na.GetNeuronAt(i, 0);
n.Label = cols[i];
}
//put in the vertical synapses for the columns which need them
for (int i = 0; i < cols.Length; i++)
{
if (cols[i] == "this" || cols[i] == "this" ||
cols[i] == "attrib" || cols[i] == "parent" ||
cols[i] == "child" || cols[i] == "next" || cols[i] == "nMtch" || cols[i] == "head" ||
cols[i] == "anyAttr" || cols[i] == "allAttr" ||
cols[i] == "recur" || cols[i] == "head" ||
cols[i] == "match" ||
cols[i] == "say")
{
Neuron n = na.GetNeuronAt(i, 0);
Neuron n1 = na.GetNeuronAt(i, 1);
n.AddSynapse(n1.Id, -1, Synapse.modelType.Fixed);
n0.AddSynapse(n1.Id, 1, Synapse.modelType.Fixed);
for (int j = 2; j < na.Height; j++)
{
n1.AddSynapse(na.GetNeuronAt(i, j).Id, -1, Synapse.modelType.Fixed);
}
}
}
//make the clr neuron clear all the input neurons
Neuron nClr = na.GetNeuronAt("clr");
for (int j = 2; j < na.Height; j++)
{
nClr.AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "in"), j).Id, -1, Synapse.modelType.Fixed);
}
na.GetNeuronAt("recur").AddSynapse(nClr.Id, 1, Synapse.modelType.Fixed);
//put in all the horizontal synapses
for (int j = 2; j < na.Height; j++)
{
na.GetNeuronAt(Array.IndexOf(cols, "in"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "in"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "in"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "thing"), j).Id, 10, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "thing"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "theNeuronArray"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "thing"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "attrib"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "thing"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "anyAttr"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "thing"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "allAttr"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "thing"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "parent"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "thing"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "child"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "thing"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "next"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "theNeuronArray"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "out"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "alt"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "out"), j).Id, 1, Synapse.modelType.Fixed);
//na.GetNeuronAt(Array.IndexOf(cols, "out"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "in"), j).Id, -1, false);
na.GetNeuronAt(Array.IndexOf(cols, "out"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "recur"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "recur"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "in"), j).Id, 2, Synapse.modelType.Fixed); //2 because the out is suppressing
na.GetNeuronAt(Array.IndexOf(cols, "match"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "thing"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "out"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "say"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "out"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "0"), j).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "0"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "say"), j).Id, -1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "next"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "in"), j).Id, -1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "next"), j).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "thing"), j).Id, -30, Synapse.modelType.Fixed);
}
//make som coluimns into an always-fire
na.GetNeuronAt(Array.IndexOf(cols, "next"), 0).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "next"), 0).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "say"), 0).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "say"), 0).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "attrib"), 0).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "attrib"), 0).Id, 1, Synapse.modelType.Fixed);
na.GetNeuronAt(Array.IndexOf(cols, "match"), 0).AddSynapse(na.GetNeuronAt(Array.IndexOf(cols, "match"), 0).Id, 1, Synapse.modelType.Fixed);
//na.GetNeuronAt(0, 2).Label = "Attribute";
//na.GetNeuronAt(0, 3).Label = "Thing";
//na.GetNeuronAt(0, 4).Label = "Sequence";
//na.GetNeuronAt("say").SetValue(1);
//if (naOut != null)
//{
// na.GetNeuronAt(Array.IndexOf(cols, "say"), 2).AddSynapse(GetSpokenWord("Attribute").Id, 1, false);
// na.GetNeuronAt(Array.IndexOf(cols, "say"), 3).AddSynapse(GetSpokenWord("Thing").Id, 1, false);
// na.GetNeuronAt(Array.IndexOf(cols, "say"), 4).AddSynapse(GetSpokenWord("Sequence").Id, 1, false);
//}
Test();
}
public override void Fire()
{
Init(); //be sure to leave this here
//Do any hebbian synapse adjustment
if (GetNeuron("Learning") is Neuron nlearing && nlearing.Fired())
{
for (int i = 0; i < mv.Height; i++)
{
if (mv.GetNeuronAt(0, i) is Neuron n)
{
if (n.LastFired > MainWindow.theNeuronArray.Generation - 4)
{
waitingForInput = 0;
//adjust the incoming synapse weights
int firedCount = 0;
for (int j = 0; j < n.synapsesFrom.Count; j++)
{
Synapse s = n.synapsesFrom[j];
if (s.model != Synapse.modelType.Fixed)
{
Neuron nSource = MainWindow.theNeuronArray.GetNeuron(s.TargetNeuron);
if (nSource.LastFired > MainWindow.theNeuronArray.Generation - 4)
{
firedCount++;
}
}
}
//if no inputs fired, things might not work so skip for now
if (firedCount == 0)
{
continue;
}
for (int j = 0; j < n.synapsesFrom.Count; j++)
{
Synapse s = n.synapsesFrom[j];
if (s.model != Synapse.modelType.Fixed)
{
Neuron nSource = MainWindow.theNeuronArray.GetNeuron(s.TargetNeuron);
if (nSource.LastFired > MainWindow.theNeuronArray.Generation - 4)
{
nSource.AddSynapse(n.id, (s.weight + targetWeightPos) / 2, s.model);
}
else
{
nSource.AddSynapse(n.id, (s.weight + targetWeightNeg) / 2, s.model);
}
}
}
//clear partial charges from others
for (int k = 0; k < mv.Height; k++)
{
if (mv.GetNeuronAt(0, k) is Neuron n5)
{
n5.currentCharge = 0;
n5.Update();
}
}
break;
}
}
}
Neuron nRdOut = GetNeuron("RdOut");
if ((MainWindow.theNeuronArray.Generation % 36) == 0)
{
waitingForInput = maxTries; //countdown tries to read
//fire rdOut
nRdOut.currentCharge = 1;
nRdOut.Update();
}
if (waitingForInput > 1 && (MainWindow.theNeuronArray.Generation % 6) == 0)
{
waitingForInput--;
nRdOut.currentCharge = 1;
nRdOut.Update();
}
//if we get here, no neuron has fired yet
if (waitingForInput == 1 && (MainWindow.theNeuronArray.Generation % 6) == 0)
{
waitingForInput--;
//if we've tried enough, learn a new pattern
//1) select the neuron to use 2) fire it
long oldestFired = long.MaxValue;
Neuron oldestNeuron = null;
for (int i = 0; i < mv.Height; i++)
{
if (mv.GetNeuronAt(0, i) is Neuron n2)
{
if (n2.LastFired < oldestFired)
{
oldestFired = n2.LastFired;
oldestNeuron = n2;
}
}
}
if (oldestNeuron != null)
{
oldestNeuron.CurrentCharge = 1;
oldestNeuron.Update();
//zero out the old synapses
List <Synapse> prevSynapses = new List <Synapse>();
for (int j = 0; j < oldestNeuron.synapsesFrom.Count; j++)
{
prevSynapses.Add(oldestNeuron.synapsesFrom[j]);
}
oldestNeuron.DeleteAllSynapes(false);
for (int j = 0; j < prevSynapses.Count; j++)
{
float theWeight = prevSynapses[j].weight;
if (prevSynapses[j].model != Synapse.modelType.Fixed)
{
theWeight = 0;
}
theNeuronArray.GetNeuron(prevSynapses[j].targetNeuron).AddSynapse(
oldestNeuron.id, theWeight, prevSynapses[j].model);
}
}
}
}
public override void Initialize()
{
Neuron nEnable = na.GetNeuronAt(0);
nEnable.Label = "Enable";
Neuron nDisable = na.GetNeuronAt(1);
nDisable.Label = "Disable";
nEnable.AddSynapse(nDisable.Id, -1);
nDisable.AddSynapse(nDisable.Id, 1);
//nDisable.CurrentCharge = 1;
for (int i = 2; i < na.NeuronCount; i++)
{
Neuron n = na.GetNeuronAt(i);
nDisable.AddSynapse(n.Id, -1);
}
Neuron nStop = na.GetNeuronAt(2);
nStop.Label = "Stop";
Neuron nGo = na.GetNeuronAt(3);
nGo.Label = "Go";
Neuron nLeft = na.GetNeuronAt(4);
nLeft.Label = "Left";
Neuron nRight = na.GetNeuronAt(5);
nRight.Label = "Right";
nStop.AddSynapse(nGo.Id, -1);
nGo.AddSynapse(nGo.Id, 1);
Neuron nFwd = GetNeuron("ModuleMove", "^");
if (nFwd != null)
{
nGo.AddSynapse(nFwd.Id, 1);
}
Neuron nKBGo = GetNeuron("KBOut", "Go");
if (nKBGo != null)
{
nKBGo.AddSynapse(nGo.Id, 1);
}
Neuron nKBStop = GetNeuron("KBOut", "Stop");
if (nKBStop != null)
{
nKBStop.AddSynapse(nStop.Id, 1);
}
Neuron nL = GetNeuron("ModuleTurn", "<");
Neuron nR = GetNeuron("ModuleTurn", ">");
if (nL != null)
{
nLeft.AddSynapse(nL.Id, 1);
}
if (nR != null)
{
nRight.AddSynapse(nR.Id, 1);
}
Neuron nLTurn = GetNeuron("KBOut", "LTurn");
if (nLTurn != null)
{
nLTurn.AddSynapse(nLeft.Id, 1);
}
Neuron nRTurn = GetNeuron("KBOut", "RTurn");
if (nRTurn != null)
{
nRTurn.AddSynapse(nRight.Id, 1);
}
nStop.AddSynapse(nLeft.Id, -1);
nStop.AddSynapse(nRight.Id, -1);
nLeft.AddSynapse(nLeft.Id, 1);
nRight.AddSynapse(nRight.Id, 1);
}
public override void Fire()
{
Init(); //be sure to leave this here
if (synth == null)
{
return;
}
if (GetNeuronValue("Cancel") == 1)
{
synth.SpeakAsyncCancelAll();
}
if (GetNeuronValue("Validate") == 1)
{
if (!validating)
{
hitWords.Clear();
missWords.Clear();
missPhrase.Clear();
hit = 0;
miss = 0;
}
validating = true;
}
else
{
if (validating)
{
if (hit + miss == 0)
{
Debug.WriteLine("No Validation Data");
}
else
{
Debug.WriteLine("Validation: " + hit + " / " + miss + " = " + 100 * hit / (hit + miss));
Debug.WriteLine("Validation: " + hitWords.Count + " / " + missWords.Count + " = " + 100 * hitWords.Count / (hitWords.Count + missWords.Count));
}
}
validating = false;
}
bool paused = true;
for (int i = 3; i < na.NeuronCount; i++)
{
Neuron n = na.GetNeuronAt(i);
if (n.Fired())
{
if (n.Label.Length == 1)
{
phraseToSpeak += n.Label;
paused = false;
}
if (n.Synapses.Count == 0)
{
//connect it to the knowledge store
//connection to KB
//ModuleUKS2 nmKB = (ModuleUKS2)FindModuleByName("AudibleUKS");
if (FindModuleByName("AudibleUKS") is ModuleUKS2 UKS)
{
string label = "pn" + n.Label;
List <Thing> phonemes = UKS.Labeled("Phoneme").Children;
Thing pn = UKS.Labeled(label, phonemes);
if (pn == null) //this should always be null
{
pn = UKS.AddThing(label, new Thing[] { UKS.Labeled("Phoneme") }, pn);
}
Neuron n1 = UKS.GetNeuron(pn);
Neuron n2 = UKS.GetNeuron(pn, false);
if (n1 != null)
{
n.AddSynapse(n1.Id, 1);
n1.SetValue(1);
n2.AddSynapse(n.Id, 1);
}
}
}
}
}
if (phonemesToFire != "")
{
char c = phonemesToFire[0];
bool fired = false;
if (c != ' ')
{
for (int i = 0; i < na.NeuronCount; i++)
{
Neuron n = na.GetNeuronAt(i);
if (n.Label == c.ToString())
{
n.SetValue(1);
fired = true;
break;
}
}
if (!fired)
{
Neuron n = AddLabel(c.ToString());
//connect it to the knowledge store
//connection to KB
//ModuleUKS2 nmKB = (ModuleUKS2)FindModuleByName("AudibleUKS");
if (FindModuleByName("AudibleUKS") is ModuleUKS2 UKS)
{
string label = "pn" + n.Label;
List <Thing> phonemes = UKS.Labeled("Phoneme").Children;
Thing pn = UKS.Labeled(label, phonemes);
if (pn == null) //this should always be null
{
pn = UKS.AddThing(label, new Thing[] { UKS.Labeled("Phoneme") }, pn);
}
Neuron n1 = UKS.GetNeuron(pn);
Neuron n2 = UKS.GetNeuron(pn, false);
if (n1 != null)
{
n.AddSynapse(n1.Id, 1);
n2.AddSynapse(n.Id, 1);
n.SetValue(1);
}
}
}
}
phonemesToFire = phonemesToFire.Substring(1);
}
if (paused && phraseToSpeak != "")
{
if (dlg != null)
{
((ModuleSpeakPhonemes2Dlg)dlg).SetLabel(phraseToSpeak);
}
if (na.GetNeuronAt("Enable").Fired())
{
ModuleSpeechIn msi = (ModuleSpeechIn)FindModuleByType(typeof(ModuleSpeechIn));
if (msi != null)
{
msi.PauseRecognition(); //if there is a recognizer active
}
//synth.SpeakAsync(phraseToSpeak + ".");
//phraseToSpeak = "";
PromptBuilder pb1 = new PromptBuilder();
if (typedIn)
{
pb1.StartVoice("Microsoft David Desktop");
pb1.StartStyle(new PromptStyle(PromptRate.Medium));
}
else
{
pb1.StartVoice("Microsoft Zira Desktop");
pb1.StartStyle(new PromptStyle(PromptRate.Slow));
}
pb1.AppendTextWithPronunciation("not used", phraseToSpeak.Trim());
pb1.EndStyle();
pb1.EndVoice();
string x = pb1.ToXml();
Debug.WriteLine(debugString(phraseToSpeak));
//synth.Speak(pb1);
synth.SpeakAsync(pb1);
}
//string heard = GetPronunciationFromText("", phraseToSpeak); //it would be nice to hear what was said but it doesn't work with this engine
phraseToSpeak = "";
typedIn = false;
}
}
private void AddSynapses()
{
Init();
ClearNeurons(false);
mv.GetNeuronAt(0, 0).Label = "In";
int chainWidth = 0;
int chainHeight = 0;
int theCount = 0;
if (mv.Height > mv.Width)
{
chainWidth = mv.Width - 2;
chainHeight = mv.Height;
//add the count neuron labels
theCount = mv.Height;
for (int j = 0; j < theCount; j++)
{
mv.GetNeuronAt(mv.Width - 1, j).Label = (j + 1).ToString();
mv.GetNeuronAt(mv.Width - 2, j).Label = "i" + (j + 1).ToString();
mv.GetNeuronAt(mv.Width - 2, j).Model = Neuron.modelType.LIF;
mv.GetNeuronAt(mv.Width - 2, j).LeakRate = 1f;
}
}
else
{
chainHeight = mv.Height - 2;
chainWidth = mv.Width;
//add the count neuron labels
theCount = mv.Width;
for (int j = 0; j < theCount; j++)
{
mv.GetNeuronAt(j, mv.Height - 1).Label = (j + 1).ToString();
mv.GetNeuronAt(j, mv.Height - 2).Label = "i" + (j + 1).ToString();
mv.GetNeuronAt(j, mv.Height - 2).Model = Neuron.modelType.LIF;
mv.GetNeuronAt(j, mv.Height - 2).LeakRate = 1f;
}
}
//add the synapses for the chain
for (int i = 0; i < chainHeight; i++)
{
for (int j = 0; j < chainWidth - 1; j++)
{
mv.GetNeuronAt(j, i).AddSynapse(mv.GetNeuronAt(j + 1, i).id, 1);
}
if (i < chainHeight - 1)
{
mv.GetNeuronAt(chainWidth - 1, i).AddSynapse(mv.GetNeuronAt(0, i + 1).id, 1);
}
}
//add the synapses to the count neurons
for (int k = 0; k < theCount; k++)
{
float theWeight = 1 / (float)(k + 1);
Neuron target = GetNeuron("i" + (k + 1).ToString());
for (int i = 0; i < chainHeight; i++)
{
for (int j = 0; j < chainWidth; j++)
{
mv.GetNeuronAt(j, i).AddSynapse(target.id, theWeight);
}
}
}
for (int k = 0; k < theCount; k++)
{
Neuron source = GetNeuron("i" + (k + 1).ToString());
Neuron target = GetNeuron((k + 1).ToString());
source.AddSynapse(target.id, 1);
for (int j = k - 1; j >= 0; j--)
{
target = GetNeuron((j + 1).ToString());
source.AddSynapse(target.id, -1);
}
}
}
//fill this method in with code which will execute once
//when the module is added, when "initialize" is selected from the context menu,
//or when the engine restart button is pressed
public override void Initialize()
{
base.Initialize();
foreach (Neuron n in na.Neurons())
{
n.DeleteAllSynapes();
}
ModuleView na1 = theNeuronArray.FindAreaByLabel("KBOut");
if (na1 != null)
{
foreach (Neuron n in na1.Neurons())
{
n.DeleteAllSynapes();
}
}
//since we are inserting at 0, these are in reverse order
UKS.Insert(0, new Thing {
Label = "Sleep"
});
UKS.Insert(0, new Thing {
Label = "Max"
});
UKS.Insert(0, new Thing {
Label = "Ref"
});
UKS.Insert(0, new Thing {
Label = "Parent"
});
firstThing = 4;
EventCount = 0;
phraseCount = 0;
//add connections from speakPhonemes to this module
ModuleView naPhonemes = theNeuronArray.FindAreaByLabel("ModuleSpeakPhonemes");
if (naPhonemes != null)
{
Neuron n2 = GetNeuron(Labeled("SayRnd"));
Neuron n3 = naPhonemes.GetNeuronAt("BabyTalk");
if (n2 != null && n3 != null)
{
n3.AddSynapse(n2.Id, 1);
}
Thing parent = Labeled("Vowel");
foreach (Neuron n in naPhonemes.Neurons())
{
if (n.Label == "Conson.")
{
parent = Labeled("Consonant");
}
if (n.Label.Length == 1)
{
string label = "spk" + n.Label;
Thing pn = AddThing(label, new Thing[] { parent });
Neuron n1 = GetNeuron(pn, false);
if (n1 != null)
{
n1.AddSynapse(n.Id, 1);
}
}
}
}
UpdateNeuronLabels();
}
