// Constructor
public AgentGenome(int index)
{
this.index = index;
bodyGenome = new BodyGenome(); // empty constructors:
brainGenome = new BrainGenome();
}
private void AgentCrossover(int playerIndex)
{
List <BrainGenome> newGenBrainGenomeList = new List <BrainGenome>(); // new population!
FitnessManager fitnessManager = teamsConfig.playersList[playerIndex].fitnessManager;
TrainingSettingsManager trainingSettingsManager = teamsConfig.playersList[playerIndex].trainingSettingsManager;
// Keep top-half peformers + mutations:
for (int x = 0; x < teamsConfig.playersList[playerIndex].agentGenomeList.Count; x++)
{
if (x == 0)
{
BrainGenome parentGenome = teamsConfig.playersList[playerIndex].agentGenomeList[fitnessManager.rankedIndicesList[x]].brainGenome;
//parentGenome.index = 0;
newGenBrainGenomeList.Add(parentGenome);
}
else
{
BrainGenome newBrainGenome = new BrainGenome();
int parentIndex = fitnessManager.GetAgentIndexByLottery();
BrainGenome parentGenome = teamsConfig.playersList[playerIndex].agentGenomeList[parentIndex].brainGenome;
newBrainGenome.SetToMutatedCopyOfParentGenome(parentGenome, trainingSettingsManager);
newGenBrainGenomeList.Add(newBrainGenome);
}
}
for (int i = 0; i < teamsConfig.playersList[playerIndex].agentGenomeList.Count; i++)
{
teamsConfig.playersList[playerIndex].agentGenomeList[i].brainGenome = newGenBrainGenomeList[i];
}
}
public AgentGenome Mutate(AgentGenome parentGenome, bool bodySettings, bool brainSettings)
{
//AgentGenome parentGenome = leaderboardGenomesList[selectedIndex].candidateGenome;
//***EAC Creature NAME mutation here???
string parentName = parentGenome.name;
int randIndex = Random.Range(0, parentName.Length - 1);
string frontHalf = parentName.Substring(0, randIndex);
string middleChar = parentName.Substring(randIndex, 1);
string backHalf = parentName.Substring(randIndex + 1);
if (RandomStatics.CoinToss(.05f)) {
middleChar = RandomStatics.GetRandomLetter();
}
frontHalf += middleChar;
string newName = RandomStatics.CoinToss(.025f) ? backHalf + frontHalf : frontHalf + backHalf;
//--------------------------------------------------------------------------------------------------------------------
tempMutationSettings = bodySettings ? mutationSettings : cachedNoneMutationSettings;
BodyGenome newBodyGenome = new BodyGenome(parentGenome.bodyGenome, tempMutationSettings);
tempMutationSettings = brainSettings ? mutationSettings : cachedNoneMutationSettings;
BrainGenome newBrainGenome = new BrainGenome(parentGenome.brainGenome, newBodyGenome, tempMutationSettings);
return new AgentGenome(newBodyGenome, newBrainGenome, parentGenome.generationCount + 1, newName);
}
public AgentGenome(BodyGenome bodyGenome, BrainGenome brainGenome, int generationCount, string name)
{
this.bodyGenome = bodyGenome;
this.brainGenome = brainGenome;
this.generationCount = generationCount;
this.name = name;
//Debug.Log("Constructing AgentGenome via mutation");
}
public void Refresh()
{
genome = cand.candidateGenome;
brain = genome.brainGenome;
core = genome.bodyGenome.coreGenome;
float lifespan = cand.performanceData.totalTicksAlive;
textGeneration.text = "Gen: " + genome.generationCount;
textBodySize.text = "Size: " + (100f * core.creatureBaseLength).ToString("F0") + ", Aspect 1:" + (1f / core.creatureAspectRatio).ToString("F0");
textBrainSize.text = "Brain Size: " + brain.inOutNeurons.Count + "--" + brain.links.Count;
}
public void RebuildBrain(BrainGenome genome, Agent agent)
{
// Create Neurons:
neuronList = new List <Neuron>();
IDs = new Dictionary <NID, int>();
// I need access to all of the Modules in order to link the neuron values to the module values!!!!
for (int i = 0; i < genome.bodyNeuronList.Count; i++)
{
Neuron neuron = new Neuron();
agent.MapNeuronToModule(genome.bodyNeuronList[i].nid, neuron);
IDs.Add(genome.bodyNeuronList[i].nid, i);
neuronList.Add(neuron);
}
for (int i = 0; i < genome.hiddenNeuronList.Count; i++) // REVISIT
{
Neuron neuron = new Neuron();
agent.MapNeuronToModule(genome.hiddenNeuronList[i].nid, neuron);
IDs.Add(genome.hiddenNeuronList[i].nid, i);
neuronList.Add(neuron);
}
//Debug.Log("RebuildBrain " + genome.bodyNeuronList.Count + ", " + neuronList.Count.ToString());
// Create Axons:
axonList = new List <Axon>();
for (int i = 0; i < genome.linkList.Count; i++)
{
// find out neuronIDs:
int fromID = -1;
if (IDs.TryGetValue(new NID(genome.linkList[i].fromModuleID, genome.linkList[i].fromNeuronID), out fromID))
{
}
else
{
Debug.LogError("fromNID NOT FOUND " + genome.linkList[i].fromModuleID.ToString() + ", " + genome.linkList[i].fromNeuronID.ToString());
}
int toID = -1;
if (IDs.TryGetValue(new NID(genome.linkList[i].toModuleID, genome.linkList[i].toNeuronID), out toID))
{
}
else
{
Debug.LogError("toNID NOT FOUND " + genome.linkList[i].fromModuleID.ToString() + ", " + genome.linkList[i].fromNeuronID.ToString());
}
//Debug.Log(fromID.ToString() + " --> " + toID.ToString() + ", " + genome.linkList[i].weight.ToString());
//int fromID = IDs < new NID(genome.linkList[i].fromModuleID, genome.linkList[i].fromNeuronID) >;
Axon axon = new Axon(fromID, toID, genome.linkList[i].weight);
axonList.Add(axon);
}
//PrintBrain();
}
/// Create Neurons and Axons
public void RebuildBrain(BrainGenome genome, Agent agent)
{
//Debug.Log($"Rebuilding brain with {genome.inOutNeurons.Count} neurons in genome, " +
// $"and {genome.linkCount} links in genome");
neurons = new List <Neuron>();
RebuildNeurons(genome.inOutNeurons, agent);
RebuildNeurons(genome.hiddenNeurons, agent);
RebuildAxons(genome);
//PrintBrain();
}
public void SetToMutatedCopyOfParentGenome(BrainGenome parentGenome, BodyGenome bodyGenome, MutationSettingsInstance settings)
{
/*
* //this.bodyNeuronList = parentGenome.bodyNeuronList; // UNSUSTAINABLE!!! might work now since all neuronLists are identical ******
*
* // Copy from parent brain or rebuild neurons from scratch based on the new mutated bodyGenome???? --- ******
* for(int i = 0; i < parentGenome.bodyNeuronList.Count; i++) {
* NeuronGenome newBodyNeuronGenome = new NeuronGenome(parentGenome.bodyNeuronList[i]);
* this.bodyNeuronList.Add(newBodyNeuronGenome);
* }
* // Alternate: SetBodyNeuronsFromTemplate(BodyGenome templateBody);
*/
// Rebuild BodyNeuronGenomeList from scratch based on bodyGenome
InitializeBodyNeuronList();
InitializeIONeurons(bodyGenome);
hiddenNeurons = MutateHiddenNeurons(parentGenome.hiddenNeurons);
links = MutateLinks(parentGenome.links, settings);
if (RandomStatics.CoinToss(settings.brainCreateNewLinkChance))
{
AddNewLink(settings);
}
if (RandomStatics.CoinToss(settings.brainCreateNewHiddenNodeChance))
{
AddNewHiddenNeuron();
}
var newNeurons = GetNewlyUnlockedNeurons(bodyGenome);
//Debug.Log($"Initializing axons with {newNeurons.Count} new neurons from " +
// $"{bodyGenome.newlyUnlockedNeuronInfo.Count} new tech.");
foreach (var neuron in newNeurons)
{
SortIONeuron(neuron);
LinkNeuronToLayer(neuron);
}
//RemoveVestigialLinks();
}
// * WPP: expose values in editor
public void SetTexture(BrainGenome brain)
{
int width = Mathf.Min(WIDTH, brain.linkCount);
texture.Resize(width, 1);
for (int x = 0; x < width; x++)
{
Color testColor;
if (brain.linkCount > x)
{
float weightVal = brain.links[x].weight;
testColor = new Color(weightVal * 0.5f + 0.5f, weightVal * 0.5f + 0.5f, weightVal * 0.5f + 0.5f);
if (weightVal < -0.25f)
{
testColor = Color.Lerp(testColor, Color.black, 0.15f);
}
else if (weightVal > 0.25f)
{
testColor = Color.Lerp(testColor, Color.white, 0.15f);
}
else
{
testColor = Color.Lerp(testColor, Color.gray, 0.15f);
}
}
else
{
testColor = Color.black; // CLEAR
}
texture.SetPixel(x, 0, testColor);
}
texture.Apply();
}
void RebuildAxons(BrainGenome genome)
{
axons = new List <Axon>();
if (genome.linkCount <= 0)
{
Debug.LogError("Cannot rebuild axons because genome has zero links");
return;
}
foreach (var link in genome.links)
{
var from = GetMatchingNeuron(neurons, link.from);
var to = GetMatchingNeuron(neurons, link.to);
if (from == null || to == null)
{
continue;
}
Axon axon = new Axon(from, to, link.weight);
axons.Add(axon);
}
}
public BrainGenome(BrainGenome parentGenome, BodyGenome bodyGenome, MutationSettingsInstance mutationSettings)
{
SetToMutatedCopyOfParentGenome(parentGenome, bodyGenome, mutationSettings);
}
void ConstructRandom(float initialConnectionDensity, int hiddenNeuronCount)
{
bodyGenome = new BodyGenome();
brainGenome = new BrainGenome(bodyGenome, initialConnectionDensity, hiddenNeuronCount);
}
public Brain(BrainGenome genome, Agent agent)
{
RebuildBrain(genome, agent);
}
//CritterModuleFoodSensorsGenome foodGenome;
// * WPP: break code sections into methods, call from here
private void UpdateUI()
{
if (!agent)
{
return;
}
agentIndex = agent.index;
candidate = agent.candidateRef;
coreModule = agent.coreModule;
brain = agent.brain;
candidateGenome = candidate.candidateGenome;
brainGenome = candidateGenome.brainGenome;
bodyGenome = candidateGenome.bodyGenome;
coreGenome = bodyGenome.coreGenome;
foodModule = agent.foodModule;
movementModule = agent.movementModule;
//foodGenome = bodyGenome.foodGenome;
if (!agent.isInert)
{
// DebugTxt1 : use this for selected creature stats:
int curCount = 0;
int maxCount = 1;
if (agent.isEgg)
{
curCount = agent.lifeStageTransitionTimeStepCounter;
maxCount = agent.gestationDurationTimeSteps;
}
if (agent.isMature)
{
curCount = agent.ageCounter;
maxCount = agent.maxAgeTimeSteps;
}
if (agent.isDead)
{
curCount = agent.lifeStageTransitionTimeStepCounter;
maxCount = curCount; // agentRef._DecayDurationTimeSteps;
}
int progressPercent = Mathf.RoundToInt((float)curCount / (float)maxCount * 100f);
string lifeStageProgressTxt = " " + agent.curLifeStage + " " + curCount + "/" + maxCount + " " + progressPercent + "% ";
// &&&& INDIVIDUAL AGENT: &&&&
string debugTxtAgent = "";
debugTxtAgent += "CRITTER# [" + agentIndex + "] SPECIES# [" + agent.speciesIndex + "]\n\n";
// Init Attributes:
// Body:
debugTxtAgent += "Base Size: " + coreGenome.creatureBaseLength.ToString("F2") + ", Aspect: " + coreGenome.creatureAspectRatio.ToString("F2") + "\n";
debugTxtAgent += "Fullsize Dimensions: ( " + agent.fullSizeBoundingBox.x.ToString("F2") + ", " + agent.fullSizeBoundingBox.y.ToString("F2") + ", " + agent.fullSizeBoundingBox.z.ToString("F2") + " )\n";
debugTxtAgent += "BONUS - Damage: " + coreModule.damageBonus.ToString("F2") + ", Speed: " + coreModule.speedBonus.ToString("F2") + ", Health: " + coreModule.healthBonus.ToString("F2") + ", Energy: " + coreModule.energyBonus.ToString("F2") + "\n";
debugTxtAgent += "DIET - Decay: " + coreModule.digestEfficiencyDecay.ToString("F2") + ", Plant: " + coreModule.digestEfficiencyPlant.ToString("F2") + ", Meat: " + coreModule.digestEfficiencyMeat.ToString("F2") + "\n";
//string mouthType = "Active";
//if (agentRef.mouthRef.isPassive) { mouthType = "Passive"; }
//debugTxtAgent += "Mouth: [" + mouthType + "]\n";
debugTxtAgent += "# Neurons: " + brain.neurons.Count + ", # Axons: " + brain.axons.Count + "\n";
debugTxtAgent += "# In/Out Nodes: " + brainGenome.inOutNeurons.Count + ", # Hidden Nodes: " + brainGenome.hiddenNeurons.Count + ", # Links: " + brainGenome.links.Count + "\n";
debugTxtAgent += "\nSENSORS:\n";
debugTxtAgent += "Comms= " + bodyGenome.data.hasComms + "\n";
debugTxtAgent += "Enviro: WaterStats: " + bodyGenome.data.useWaterStats + ", Cardinals= " + bodyGenome.data.useCardinals + ", Diagonals= " + bodyGenome.data.useDiagonals + "\n";
//debugTxtAgent += "Food: Nutrients= " + foodGenome.useNutrients + ", Pos= " + foodGenome.usePos + ", Dir= " + foodGenome.useDir + ", Stats= " + foodGenome.useStats + ", useEggs: " + foodGenome.useEggs + ", useCorpse: " + foodGenome.useCorpse + "\n";
//debugTxtAgent += "Friend: Pos= " + bodyGenome.friendGenome.usePos + ", Dir= " + bodyGenome.friendGenome.useDir + ", Vel= " + bodyGenome.friendGenome.useVel + "\n";
//debugTxtAgent += "Threat: Pos= " + bodyGenome.threatGenome.usePos + ", Dir= " + bodyGenome.threatGenome.useDir + ", Vel= " + bodyGenome.threatGenome.useVel + ", Stats= " + bodyGenome.threatGenome.useStats + "\n";
// Realtime Values:
debugTxtAgent += "\nREALTIME DATA:";
//debugTxtAgent += "\nExp: " + agentRef.totalExperience.ToString("F2") + ", fitnessScore: " + agentRef.masterFitnessScore.ToString("F2") + ", LVL: " + agentRef.curLevel.ToString();
debugTxtAgent += "\n(" + lifeStageProgressTxt + ") Growth: " + (agent.sizePercentage * 100f).ToString("F0") + "%, Age: " + agent.ageCounter + " Frames\n\n";
debugTxtAgent += "Nearest Food: [" + foodModule.nearestFoodParticleIndex +
"] Amount: " + foodModule.nearestFoodParticleAmount.ToString("F4") +
"\nPos: ( " + foodModule.nearestFoodParticlePos.x.ToString("F2") +
", " + foodModule.nearestFoodParticlePos.y.ToString("F2") +
" ), Dir: ( " + foodModule.foodPlantDirX[0].ToString("F2") +
", " + foodModule.foodPlantDirY[0].ToString("F2") + " )" +
"\n";
debugTxtAgent += "\nNutrients: " + foodModule.nutrientDensity[0].ToString("F4") + ", Stamina: " + coreModule.stamina[0].ToString("F3") + "\n";
debugTxtAgent += "Gradient Dir: (" + foodModule.nutrientGradX[0].ToString("F2") + ", " + foodModule.nutrientGradY[0].ToString("F2") + ")\n";
//debugTxtAgent += "Total Food Eaten -- Decay: n/a, Plant: " + agentRef.totalFoodEatenPlant.ToString("F2") + ", Meat: " + agentRef.totalFoodEatenZoop.ToString("F2") + "\nFood Stored: " + agentRef.coreModule.foodStored[0].ToString() + ", Corpse Food Amount: " + agentRef.currentBiomass.ToString("F3") + "\n";
//debugTxtAgent += "\nFullSize: " + agentRef.fullSizeBoundingBox.ToString() + ", Volume: " + agentRef.fullSizeBodyVolume.ToString() + "\n";
//debugTxtAgent += "( " + (agentRef.sizePercentage * 100f).ToString("F0") + "% )\n";
debugTxtAgent += "\nCurVel: " + agent.curVel.ToString("F3") + ", CurAccel: " + agent.curAccel.ToString("F3") + ", AvgVel: " + agent.avgVel.ToString("F3") + "\n";
debugTxtAgent += "\nWater Depth: " + agent.waterDepth.ToString("F3") + ", Vel: " + (agent.avgFluidVel * 10f).ToString("F3") + "\n";
debugTxtAgent += "Throttle: [ " + movementModule.throttleX[0].ToString("F3") + ", " + movementModule.throttleY[0].ToString("F3") + " ]\n";
debugTxtAgent += "FeedEffector: " + coreModule.mouthFeedEffector[0].ToString("F2") + "\n";
debugTxtAgent += "AttackEffector: " + coreModule.mouthAttackEffector[0].ToString("F2") + "\n";
debugTxtAgent += "DefendEffector: " + coreModule.defendEffector[0].ToString("F2") + "\n";
debugTxtAgent += "DashEffector: " + coreModule.dashEffector[0].ToString("F2") + "\n";
debugTxtAgent += "HealEffector: " + coreModule.healEffector[0].ToString("F2") + "\n";
//+++++++++++++++++++++++++++++++++++++ CRITTER: ++++++++++++++++++++++++++++++++++++++++++++
string debugTxtGlobalSim = "";
debugTxtGlobalSim += "\n\nNumChildrenBorn: " + simulation.numAgentsBorn + ", numDied: " + simulation.numAgentsDied + ", ~Gen: " + ((float)simulation.numAgentsBorn / (float)simulation.numAgents);
debugTxtGlobalSim += "\nSimulation Age: " + simulation.simAgeTimeSteps;
debugTxtGlobalSim += "\nYear " + simulation.curSimYear + "\n\n";
int numActiveSpecies = masterGenomePool.currentlyActiveSpeciesIDList.Count;
debugTxtGlobalSim += numActiveSpecies + " Active Species:\n";
for (int s = 0; s < numActiveSpecies; s++)
{
int speciesID = masterGenomePool.currentlyActiveSpeciesIDList[s];
//int parentSpeciesID = simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].parentSpeciesID;
int numCandidates = masterGenomePool.completeSpeciesPoolsList[speciesID].candidateGenomesList.Count;
int numLeaders = masterGenomePool.completeSpeciesPoolsList[speciesID].leaderboardGenomesList.Count;
//int numBorn = simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].numAgentsEvaluated;
int speciesPopSize = 0;
//float avgFitness = simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgPerformanceData.totalTicksAlive;
for (int a = 0; a < simulation.numAgents; a++)
{
if (simulation.agents[a].speciesIndex == speciesID)
{
speciesPopSize++;
}
}
if (masterGenomePool.completeSpeciesPoolsList[speciesID].isFlaggedForExtinction)
{
debugTxtGlobalSim += "xxx ";
}
/*debugTxtGlobalSim += "Species[" + speciesID.ToString() + "] p(" + parentSpeciesID.ToString() + "), size: " + speciesPopSize.ToString() + ", #cands: " + numCandidates.ToString() + ", numEvals: " + numBorn.ToString() +
* ", avgFitness: " + avgFitness.ToString("F2") +
* ", avgConsumption: (" + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgFoodEatenCorpse.ToString("F4") + ", " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgFoodEatenPlant.ToString("F4") + ", " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgFoodEatenZoop.ToString("F4") + ", " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgFoodEatenEgg.ToString("F4") + ", " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgFoodEatenCreature.ToString("F4") +
* "), avgBodySize: " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgBodySize.ToString("F3") +
* ", avgTalentSpec: (" + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgSpecAttack.ToString("F2") + ", " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgSpecDefend.ToString("F2") + ", " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgSpecSpeed.ToString("F2") + ", " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgSpecUtility.ToString("F2") +
* "), avgDiet: (" + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgFoodSpecDecay.ToString("F2") + ", " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgFoodSpecPlant.ToString("F2") + ", " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgFoodSpecMeat.ToString("F2") +
* "), avgNumNeurons: " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgNumNeurons.ToString("F1") +
* ", avgNumAxons: " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgNumAxons.ToString("F1") +
* ", total: " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgFitnessScore.ToString("F2") +
* ", avgExp: " + simManager.masterGenomePool.completeSpeciesPoolsList[speciesID].avgExperience.ToString() + "\n\n";*/
}
/*debugTxtGlobalSim += "\n\nAll-Time Species List:\n";
* for (int p = 0; p < simManager.masterGenomePool.completeSpeciesPoolsList.Count; p++) {
* string extString = "Active!";
* if (simManager.masterGenomePool.completeSpeciesPoolsList[p].isExtinct) {
* extString = "Extinct!";
* }
* debugTxtGlobalSim += "Species[" + p.ToString() + "] p(" + simManager.masterGenomePool.completeSpeciesPoolsList[p].parentSpeciesID.ToString() + ") " + extString + "\n";
* }*/
textDebugTrainingInfo1.text = debugTxtAgent;
textDebugTrainingInfo3.text = debugTxtGlobalSim;
}
string debugTxtResources = "";
debugTxtResources += "GLOBAL RESOURCES:\n";
debugTxtResources += "\nSunlight: " + environmentSettings._BaseSolarEnergy;
debugTxtResources += "\nOxygen: " + simResourceManager.curGlobalOxygen;
debugTxtResources += "\n + " + simResourceManager.oxygenProducedByAlgaeReservoirLastFrame + " ( algae reservoir )";
debugTxtResources += "\n + " + simResourceManager.oxygenProducedByPlantParticlesLastFrame + " ( algae particles )";
debugTxtResources += "\n - " + simResourceManager.oxygenUsedByDecomposersLastFrame + " ( decomposers )";
debugTxtResources += "\n - " + simResourceManager.oxygenUsedByAnimalParticlesLastFrame + " ( zooplankton )";
debugTxtResources += "\n - " + simResourceManager.oxygenUsedByAgentsLastFrame + " ( agents )";
debugTxtResources += "\nNutrients: " + simResourceManager.curGlobalNutrients;
debugTxtResources += "\n + " + simResourceManager.nutrientsProducedByDecomposersLastFrame + " ( decomposers )";
debugTxtResources += "\n - " + simResourceManager.nutrientsUsedByAlgaeReservoirLastFrame + " ( algae reservoir )";
debugTxtResources += "\n - " + simResourceManager.nutrientsUsedByPlantParticlesLastFrame + " ( algae particles )";
debugTxtResources += "\nDetritus: " + simResourceManager.curGlobalDetritus;
debugTxtResources += "\n + " + simResourceManager.wasteProducedByAlgaeReservoirLastFrame + " ( algae reservoir )";
debugTxtResources += "\n + " + simResourceManager.wasteProducedByPlantParticlesLastFrame + " ( algae particles )";
debugTxtResources += "\n + " + simResourceManager.wasteProducedByAnimalParticlesLastFrame + " ( zooplankton )";
debugTxtResources += "\n + " + simResourceManager.wasteProducedByAgentsLastFrame + " ( agents )";
debugTxtResources += "\n - " + simResourceManager.detritusRemovedByDecomposersLastFrame + " ( decomposers )";
debugTxtResources += "\nDecomposers: " + simResourceManager.curGlobalDecomposers;
debugTxtResources += "\nAlgae (Reservoir): " + simResourceManager.curGlobalAlgaeReservoir;
debugTxtResources += "\nAlgae (Particles): " + simResourceManager.curGlobalPlantParticles;
debugTxtResources += "\nZooplankton: " + simResourceManager.curGlobalAnimalParticles;
debugTxtResources += "\nLive Agents: " + simResourceManager.curGlobalAgentBiomass;
debugTxtResources += "\nDead Agents: " + simResourceManager.curGlobalCarrionVolume;
debugTxtResources += "\nEggSacks: " + simResourceManager.curGlobalEggSackVolume;
debugTxtResources += "\nGlobal Mass: " + simResourceManager.curTotalMass;
Vector4 resourceGridSample = simulation.SampleTexture(vegetationManager.resourceGridRT1, theCursorCzar.curMousePositionOnWaterPlane / SimulationManager._MapSize);
Vector4 simTansferSample = simulation.SampleTexture(vegetationManager.resourceSimTransferRT, theCursorCzar.curMousePositionOnWaterPlane / SimulationManager._MapSize) * 100f;
//Debug.Log("curMousePositionOnWaterPlane: " + curMousePositionOnWaterPlane.ToString());
debugTxtResources += "\nresourceGridSample: (" + resourceGridSample.x.ToString("F4") + ", " + resourceGridSample.y.ToString("F4") + ", " + resourceGridSample.z.ToString("F4") + ", " + resourceGridSample.w.ToString("F4") + ")";
debugTxtResources += "\nsimTansferSample: (" + simTansferSample.x.ToString("F4") + ", " + simTansferSample.y.ToString("F4") + ", " + simTansferSample.z.ToString("F4") + ", " + simTansferSample.w.ToString("F4") + ")";
textDebugTrainingInfo2.text = debugTxtResources;
if (debugTextureViewerArray == null)
{
CreateDebugRenderViewerArray();
}
debugTextureViewerMat.SetPass(0);
debugTextureViewerMat.SetVector("_Zoom", _Zoom);
debugTextureViewerMat.SetFloat("_Amplitude", _Amplitude);
debugTextureViewerMat.SetVector("_ChannelMask", _ChannelMask);
debugTextureViewerMat.SetInt("_ChannelSoloIndex", _ChannelSoloIndex);
debugTextureViewerMat.SetFloat("_IsChannelSolo", _IsChannelSolo);
debugTextureViewerMat.SetFloat("_Gamma", _Gamma);
//debugTextureViewerMat.
if (debugTextureViewerArray[_DebugTextureIndex])
{
debugTextureViewerMat.SetTexture("_MainTex", debugTextureViewerArray[_DebugTextureIndex]);
int channelID = 4;
string[] channelLabelTxt = new string[5];
channelLabelTxt[0] = " (X Solo)";
channelLabelTxt[1] = " (Y Solo)";
channelLabelTxt[2] = " (Z Solo)";
channelLabelTxt[3] = " (W Solo)";
channelLabelTxt[4] = " (Color)";
if (_IsChannelSolo > 0.5f)
{
channelID = _ChannelSoloIndex;
}
textDebugTextureName.text = debugTextureViewerArray[_DebugTextureIndex].name + channelLabelTxt[channelID];
}
textDebugTextureZoomX.text = _Zoom.x.ToString();
textDebugTextureZoomY.text = _Zoom.y.ToString();
textDebugTextureAmplitude.text = _Amplitude.ToString();
textDebugTextureSoloChannelIndex.text = _ChannelSoloIndex.ToString();
textDebugTextureGamma.text = _Gamma.ToString();
}
public Brain(BrainGenome genome, Agent agent)
{
//Debug.Log("Brain() genome: " + genome.bodyNeuronList.Count.ToString());
RebuildBrain(genome, agent);
}
private void NextGeneration()
{
string fitTxt = "Fitness Scores:\n";
float totalFitness = 0f;
float minScore = float.PositiveInfinity;
float maxScore = float.NegativeInfinity;
for (int f = 0; f < trainingPopulationSize; f++)
{
fitTxt += f.ToString() + ": " + rawFitnessScoresArray[f].ToString() + "\n";
totalFitness += rawFitnessScoresArray[f];
minScore = Mathf.Min(minScore, rawFitnessScoresArray[f]);
maxScore = Mathf.Max(maxScore, rawFitnessScoresArray[f]);
}
Debug.Log(fitTxt);
avgFitnessLastGen = totalFitness / (float)trainingPopulationSize;
// Process Fitness (bigger is better so lottery works)
float scoreRange = maxScore - minScore;
if (scoreRange == 0f)
{
scoreRange = 1f; // avoid divide by zero
}
for (int f = 0; f < trainingPopulationSize; f++)
{
rawFitnessScoresArray[f] = 1f - ((rawFitnessScoresArray[f] - minScore) / scoreRange); // normalize and invert scores for fitness lottery
}
// Sort Fitness Scores
int[] rankedIndicesList = new int[rawFitnessScoresArray.Length];
float[] rankedFitnessList = new float[rawFitnessScoresArray.Length];
// populate arrays:
for (int i = 0; i < rawFitnessScoresArray.Length; i++)
{
rankedIndicesList[i] = i;
rankedFitnessList[i] = rawFitnessScoresArray[i];
}
for (int i = 0; i < rawFitnessScoresArray.Length - 1; i++)
{
for (int j = 0; j < rawFitnessScoresArray.Length - 1; j++)
{
float swapFitA = rankedFitnessList[j];
float swapFitB = rankedFitnessList[j + 1];
int swapIdA = rankedIndicesList[j];
int swapIdB = rankedIndicesList[j + 1];
if (swapFitA < swapFitB) // bigger is better now after inversion
{
rankedFitnessList[j] = swapFitB;
rankedFitnessList[j + 1] = swapFitA;
rankedIndicesList[j] = swapIdB;
rankedIndicesList[j + 1] = swapIdA;
}
}
}
string fitnessRankText = "";
for (int i = 0; i < rawFitnessScoresArray.Length; i++)
{
fitnessRankText += "[" + rankedIndicesList[i].ToString() + "]: " + rankedFitnessList[i].ToString() + "\n";
}
// CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER CROSSOVER
List <BrainGenome> newGenBrainGenomeList = new List <BrainGenome>(); // new population!
//FitnessManager fitnessManager = teamsConfig.playersList[playerIndex].fitnessManager;
//TrainingSettingsManager trainingSettingsManager = teamsConfig.playersList[playerIndex].trainingSettingsManager;
// Keep top-half peformers + mutations:
for (int x = 0; x < agentGenomeList.Count; x++)
{
if (x == 0)
{
BrainGenome parentGenome = agentGenomeList[rankedIndicesList[x]].brainGenome; // keep top performer as-is
newGenBrainGenomeList.Add(parentGenome);
}
else
{
BrainGenome newBrainGenome = new BrainGenome();
int parentIndex = GetAgentIndexByLottery(rankedFitnessList, rankedIndicesList);
BrainGenome parentGenome = agentGenomeList[parentIndex].brainGenome;
newBrainGenome.SetToMutatedCopyOfParentGenome(parentGenome, trainingSettingsManager);
newGenBrainGenomeList.Add(newBrainGenome);
}
}
for (int i = 0; i < agentGenomeList.Count; i++)
{
agentGenomeList[i].brainGenome = newGenBrainGenomeList[i];
}
// Reset
ResetTrainingForNewGen();
trainingSettingsManager.mutationChance *= 0.996f;
trainingSettingsManager.mutationStepSize *= 0.998f;
curTrainingGen++;
}
public void SetToMutatedCopyOfParentGenome(BrainGenome parentGenome, TrainingSettingsManager settings)
{
this.bodyNeuronList = parentGenome.bodyNeuronList; // UNSUSTAINABLE!!! might work now since all neuronLists are identical
// Alternate: SetBodyNeuronsFromTemplate(BodyGenome templateBody);
// Existing Hidden Neurons!!
hiddenNeuronList = new List <NeuronGenome>();
for (int i = 0; i < parentGenome.hiddenNeuronList.Count; i++)
{
NeuronGenome newHiddenNeuronGenome = new NeuronGenome(parentGenome.hiddenNeuronList[i]); // create new neuron as a copy of parent neuron
// Might be able to simply copy hiddenNeuronList or individual hiddenNeuronGenomes from parent if they are functionally identical...
// for now going with the thorough approach of a reference-less copy
hiddenNeuronList.Add(newHiddenNeuronGenome);
}
// Existing Links!!
linkList = new List <LinkGenome>();
for (int i = 0; i < parentGenome.linkList.Count; i++)
{
LinkGenome newLinkGenome = new LinkGenome(parentGenome.linkList[i].fromModuleID, parentGenome.linkList[i].fromNeuronID, parentGenome.linkList[i].toModuleID, parentGenome.linkList[i].toNeuronID, parentGenome.linkList[i].weight, true);
float randChance = UnityEngine.Random.Range(0f, 1f);
if (randChance < settings.mutationChance)
{
float randomWeight = Gaussian.GetRandomGaussian();
newLinkGenome.weight = Mathf.Lerp(newLinkGenome.weight, randomWeight, settings.mutationStepSize);
}
linkList.Add(newLinkGenome);
}
// Add Brand New Link:
//
float randLink = UnityEngine.Random.Range(0f, 1f);
if (randLink < settings.newLinkChance)
{
List <NeuronGenome> inputNeuronList = new List <NeuronGenome>();
//List<NeuronGenome> hiddenNeuronList = new List<NeuronGenome>();
List <NeuronGenome> outputNeuronList = new List <NeuronGenome>();
for (int j = 0; j < bodyNeuronList.Count; j++)
{
if (bodyNeuronList[j].neuronType == NeuronGenome.NeuronType.In)
{
inputNeuronList.Add(bodyNeuronList[j]);
}
if (bodyNeuronList[j].neuronType == NeuronGenome.NeuronType.Out)
{
outputNeuronList.Add(bodyNeuronList[j]);
}
}
for (int j = 0; j < hiddenNeuronList.Count; j++)
{
inputNeuronList.Add(hiddenNeuronList[j]);
outputNeuronList.Add(hiddenNeuronList[j]);
}
// Try x times to find new connection -- random scattershot approach at first:
// other methods:
// -- make sure all bodyNeurons are fully-connected when modifying body
int maxChecks = 8;
for (int k = 0; k < maxChecks; k++)
{
int randID = UnityEngine.Random.Range(0, inputNeuronList.Count);
NID fromNID = inputNeuronList[randID].nid;
randID = UnityEngine.Random.Range(0, outputNeuronList.Count);
NID toNID = outputNeuronList[randID].nid;
// check if it exists:
bool linkExists = false;
for (int l = 0; l < linkList.Count; l++)
{
if (linkList[l].fromModuleID == fromNID.moduleID && linkList[l].fromNeuronID == fromNID.neuronID && linkList[l].toModuleID == toNID.moduleID && linkList[l].toNeuronID == toNID.neuronID)
{
linkExists = true;
break;
}
}
if (linkExists)
{
}
else
{
float randomWeight = Gaussian.GetRandomGaussian() * 0f;
LinkGenome linkGenome = new LinkGenome(fromNID.moduleID, fromNID.neuronID, toNID.moduleID, toNID.neuronID, randomWeight, true);
//Debug.Log("New Link! from: [" + fromNID.moduleID.ToString() + ", " + fromNID.neuronID.ToString() + "], to: [" + toNID.moduleID.ToString() + ", " + toNID.neuronID.ToString() + "]");
linkList.Add(linkGenome);
break;
}
}
}
// Add Brand New Hidden Neuron:
float randNeuronChance = UnityEngine.Random.Range(0f, 1f);
if (randNeuronChance < settings.newHiddenNodeChance)
{
// find a link and expand it:
int randLinkID = UnityEngine.Random.Range(0, linkList.Count);
// create new neuron
NeuronGenome newNeuronGenome = new NeuronGenome(NeuronGenome.NeuronType.Hid, -1, hiddenNeuronList.Count);
hiddenNeuronList.Add(newNeuronGenome);
// create 2 new links
LinkGenome linkGenome1 = new LinkGenome(linkList[randLinkID].fromModuleID, linkList[randLinkID].fromNeuronID, newNeuronGenome.nid.moduleID, newNeuronGenome.nid.neuronID, 1f, true);
LinkGenome linkGenome2 = new LinkGenome(newNeuronGenome.nid.moduleID, newNeuronGenome.nid.neuronID, linkList[randLinkID].toModuleID, linkList[randLinkID].toNeuronID, linkList[randLinkID].weight, true);
// delete old link
linkList.RemoveAt(randLinkID);
// add new links
linkList.Add(linkGenome1);
linkList.Add(linkGenome2);
//Debug.Log("New Neuron! " + newNeuronGenome.nid.neuronID.ToString() + " - from: [" + linkGenome1.fromModuleID.ToString() + ", " + linkGenome1.fromNeuronID.ToString() + "], to: [" + linkGenome2.toModuleID.ToString() + ", " + linkGenome2.toNeuronID.ToString() + "]");
}
}
public Brain(BrainGenome genome, Agent agent)
{
// Debug.Log("Brain constructed with " + genome.inOutNeurons.Count + " neurons.");
RebuildBrain(genome, agent);
}
