// Use this for initialization
void Start()
{
Instance = this;
for (int i = 0; i < PopulationSize; i++)
{
GameObject curRocket = (GameObject)GameObject.Instantiate(RocketPrefab, new Vector3(0, 0, -1000), Quaternion.identity);
RocketGameObjects.Add(curRocket);
DNA curDNA = (DNA)gameObject.AddComponent <DNA>();
Population.Add(curDNA);
curDNA.RandomSeed(DNASize);
curRocket.GetComponent <Rocket>().cDNA = curDNA;
curDNA.MyRocket = curRocket;
}
foreach (GameObject curRocketgo in RocketGameObjects)
{
foreach (GameObject otherRocketGO in RocketGameObjects)
{
if (curRocketgo != otherRocketGO)
{
Physics2D.IgnoreCollision(curRocketgo.GetComponent <Collider2D>(), otherRocketGO.GetComponent <Collider2D>());
}
}
}
foreach (GameObject RocketGO in RocketGameObjects)
{
RocketGO.transform.position = new Vector3(0, 0, 0);
}
}
public Model(int childCount, int iterationCount, float mutationRate)
{
_mutationRate = mutationRate;
_childCount = childCount;
_iterationCount = iterationCount;
_rulesets = new RuleSet[_childCount];
_meshes = new Mesh[_childCount];
//InitialiseDB.Initialise(); //can be used to populate a new set of initial L systems in the DB (specified in LSystemDB.cs)
var ldb = new LSystemDB();
var systemsJSON = ldb.ReadFromFile();
_sampleRules = new string[_childCount][];
_sampleAxioms = new string[_childCount][];
_encode = new Encoder("Ff-+|!£\"GHI^&$");
//get the L systems from database and assign them to as meshes to GOs
for (int i = 0; i < _childCount; i++)
{
RuleSet tempRS = new RuleSet(systemsJSON[(i % systemsJSON.Count).ToString()]);
_rulesets[i] = tempRS;
_meshes[i] = MeshFromRuleset(i);
EncodeSamples(i);
}
//one GA for the rules and axioms so they don't get jumbled up
_gaRules = CreateGA(_sampleRules);
_gaAxioms = CreateGA(_sampleAxioms);
}
public void Init()
{
// Initialize the genes
// 0 = Forward
// 1 = Angled Turn
GA = new GeneticAlgo(geneLength, 360);
startPos = this.transform.position;
}
public void setup(CustomTerrain ct, GeneticAlgo ga)
{
terrain = ct;
genetic_algo = ga;
updateSetup();
zone = new VegetationConstraint[livesIn.Length];
for (int i = 0; i < livesIn.Length; i++)
{
zone[i] = terrain.getVegetationFromZone(livesIn[i]);//Added
}
}
public void Init()
{
// Initialize our genes
// 0 = Forward
// 1 = Left
// 2 = Right
GA = new GeneticAlgo(geneLength, 3);
timeAlive = 0.0f;
alive = true;
ethan = Instantiate(ethanPrefab, this.transform.position, this.transform.rotation);
ethan.GetComponent <UnityStandardAssets.Characters.ThirdPerson.AICharacterControl> ().target = this.transform;
}
private void StartButton_Click(object sender, RoutedEventArgs e)
{
generation = 1;
generationString = "Generaciones : \n";
if (!String.IsNullOrEmpty(PopulationTextBox.Text))
{
this.population = int.Parse(PopulationTextBox.Text);
geneticAlgo = new GeneticAlgo(this.population);
this.ejecutarAlgoritmo();
}
}
public void Init()
{
// Init GeneticAlgo
// 0 = Forward
// 1 = Back
// 2 = Left
// 3 = Right
// 4 = Jump
// 5 = Crouch
GA = new GeneticAlgo(geneLength, 6);
m_Character = GetComponent <ThirdPersonCharacter> ();
startingPos = this.transform.position;
timeAlive = 0;
alive = true;
}
// Start is called before the first frame update
void Awake()
{
gameController = FindObjectOfType <GameController>();
geneticAlgo = FindObjectOfType <GeneticAlgo>();
bird = GetComponent <Bird>();
weights1 = new float[inputLayerSize, hidenLayerSize];
weights2 = new float[hidenLayerSize];
bias1 = new float[hidenLayerSize];
//for observation in editor
hidenNode = new float[hidenLayerSize];
SetRandomParameters();
//SetTestParameters();
}
public void Combine(GeneticAlgo GA1, GeneticAlgo GA2)
{
for (int i = 0; i < geneLength; i++)
{
if (i < geneLength / 2)
{
int c = GA1.genes [i];
genes [i] = c;
}
else
{
int c = GA2.genes [i];
genes [i] = c;
}
}
}
private void btnStart_Click(object sender, EventArgs e)
{
GeneticAlgo geneticAlgo = new GeneticAlgo();
List<Cromosoma> initPopulation = obtenerPoblacionInicial(tamanioPoblacion);
geneticAlgo.generarRistras(ref initPopulation, generaciones, probabilidadDeCruza, probabilidadDeMutacion);
dgResults.Rows.Clear();
for (int i = 0; i < initPopulation.Count - 1; i++)
{
String sol = "| ";
for (int j = 0; j < 8; j++)
{
sol = sol + initPopulation[i].genes[j] + " | ";
}
dgResults.Rows.Add(new Object[] { sol, initPopulation[i].conveniencia });
}
board1.Genes = initPopulation[0].genes;
}
private List<Cromosoma> obtenerPoblacionInicial(int population)
{
List<Cromosoma> initPop = new List<Cromosoma>();
GeneticAlgo RandomGen = new GeneticAlgo();
for (int i = 0; i < population; i++)
{
List<int> genes = new List<int>(new int[] {0, 1, 2, 3, 4, 5, 6, 7});
Cromosoma chromosome = new Cromosoma();
chromosome.genes = new int[8];
for (int j = 0; j < 8; j++)
{
int geneIndex = (int)(RandomGen.obtenerAleatorio(0,genes.Count-1)+0.5);
chromosome.genes[j] = genes[geneIndex];
genes.RemoveAt(geneIndex);
}
initPop.Add(chromosome);
}
return initPop;
}
public void StartTest()
{
MatchAlgo matchAlgo = new MatchAlgo();
GeneticAlgo geneticAlgo = new GeneticAlgo();
System.Random rand = new System.Random();
List <WeightsForBoardEval> weights = new List <WeightsForBoardEval>();
for (int i = 0; i < 50; i++)
{
WeightsForBoardEval w = new WeightsForBoardEval(rand);
weights.Add(w);
Console.WriteLine("pesInizRand = " + w);
}
SortedList <WeightScore, int> scoreMap = new SortedList <WeightScore, int>();
//per ogni peso = giocatore, fa giocare 3 match come oca e 3 match come volpe al giocatore contro un giocatore casuale
for (int i = 0; i < weights.Count; i++)
{
int score = 0;
WeightsForBoardEval weight = weights[i];
AlphaBeta playerAsFox = new AlphaBeta(PawnType.Fox, 3, weight, false);
AlphaBeta playerAsGoose = new AlphaBeta(PawnType.Goose, 3, weight, false);
score = matchAlgo.MatchTwoAi(playerAsFox, null, 3, -1, -1).first;
score += matchAlgo.MatchTwoAi(playerAsGoose, null, 3, -1, -1).first;
WeightScore ws = new WeightScore(weight, score);
scoreMap.Add(ws, score);
}
Console.WriteLine("aiTester prima di evoluzione");
// evolve 50 volte la popolazione
for (int i = 0; i < 50; i++)
{
Console.WriteLine("\n \n \n \n inizio evoluzione generazione " + i);
scoreMap = geneticAlgo.Evolve(scoreMap, 0.3, 0.1, 0.01);
}
Console.WriteLine("best weights " + scoreMap.Keys[0]);
Console.WriteLine("finito completamente aiTester ore: " + DateTime.Now.ToString("h:mm:ss tt"));
Console.ReadKey();
}
public void CreateGA()
{
System.Random r = new System.Random(Time.frameCount);
string selectType = "god mode";
string mutateType = "randomChoice";
string crossType = "OnePt";
Encoder encoder = new Encoder();
string target = encoder.Encode(TextureNoise.CreateNoise(width, height, r));
Fitness fitness = new Fitness(target);
Population population = new Population(20, fitness._targetString)
{
_name = "images"
};
Selection selection = new Selection(selectType);
CrossOver crossover = new CrossOver(crossType);
Mutation mutation = new Mutation(mutateType);
geneticAlgo = new GeneticAlgo(encoder, fitness, population, selection, crossover, mutation);
}
// Update is called once per frame
void FixedUpdate()
{
if (transform.position.y > 1.5 | transform.position.y < -1.5)
{
alife = false;
}
if (alife)
{
GeneticAlgo ga = FindObjectOfType <GeneticAlgo>();
if (ga != null & ga.regularisationWeight != 0 & nn)
{
//if (ga.regularisationWeight!=0 & nn)
//{
// score += Time.deltaTime - nn.RegularisationTerm();
//}
}
else
{
score += Time.deltaTime;
}
}
}
// Update is called once per frame
void Update()
{
//Debug.Log(transform.forward);
float[] values;
float fitness;
string id;
KeyControl();
duration -= Time.deltaTime;
GameObject.FindGameObjectWithTag("text duration").GetComponent <Text>().text = "Elapsed Duration : " + duration.ToString() + "\n" +
"Camera Movement Status : " + isMoveCamera.ToString() + "\n" +
"Camera Follow Status : " + isFollowCamera.ToString() + "\n" +
"Press 'L' to hide camera information" + "\n" +
"Press 'I' to display camera information" + "\n";
if (duration <= 0)
{
System.Diagnostics.Stopwatch stopWatch = new System.Diagnostics.Stopwatch();
stopWatch.Start();
GeneticAlgo GA = new GeneticAlgo(counterId);
GA.Generations = generations;
GA.MutationRate = mutationRate;
GA.CrossoverRate = crossoverRate;
GA.FitnessFile = @fitnessFile;
GA.Elitism = elitism;
GA.PopulationSize = populationSize;
GA.Compute();
GA.GetBest(out values, out fitness, out id, out duration);
isMoveCamera = (Random.value > 0.5f) ? true : false;
isFollowCamera = (Random.value > 0.5f) ? true : false;
if (!isFollowCamera)
{
isMoveCamera = false;
}
while (fitness != 1.0f)
{
GA.Compute();
GA.GetBest(out values, out fitness, out id, out duration);
}
hasilPosGenerated = new Vector3(values[0], values[1], values[2]);
hasilRotGenerated = new Vector3(values[3], values[4], values[5]);
initialId = id;
stopWatch.Stop();
System.TimeSpan ts = stopWatch.Elapsed;
executionTime = System.String.Format("{0:00}:{1:00}:{2:00}.{3:00}",
ts.Hours, ts.Minutes, ts.Seconds,
ts.Milliseconds / 10);
GameObject.FindGameObjectWithTag("text pose").GetComponent <Text>().text = "Id Pose : " + initialId + "\n"
+ "Duration : " + duration + "\n"
+ "Execution Time : " + executionTime + "\n"
+ "Fitness : " + fitness.ToString();
counterId = initialId;
if (ts.Milliseconds >= 50)
{
GameObject.FindGameObjectWithTag("text pose").GetComponent <Text>().color = new Color(255, 0, 0);
}
else
{
GameObject.FindGameObjectWithTag("text pose").GetComponent <Text>().color = new Color(0, 253, 243);
}
smartCam.transform.rotation = Quaternion.Euler(hasilRotGenerated + transform.rotation.eulerAngles);
smartCam.transform.position = transform.position + (transform.rotation * hasilPosGenerated);
if (isFollowCamera)
{
smartCam.transform.parent = transform;
}
else
{
smartCam.transform.parent = null;
}
temp = Regex.Replace(counterId, @"[\d-]", string.Empty);
if (temp == "MSF")
{
isZoom = Random.value > 0.5f ? true : false;
}
}
if (isMoveCamera)
{
CameraMovementPose();
}
var screenPoint = Vector3.Distance(smartCam.transform.position, transform.position);
if (screenPoint > CameraDistance)
{
if (!isFollowCamera)
{
if (duration > 1f)
{
smartCam.transform.LookAt(transform);
duration = duration - Time.deltaTime * 1f;
}
}
}
}
