public Trainer Clone()
{
Trainer New_Trainer = new Trainer(Setting.Instance().mapSize_Width, Setting.Instance().mapSize_Height, blocksize);
New_Trainer.train_setting();
New_Trainer._Genetic = _Genetic.Clone();
return(New_Trainer);
} // 사본생산
public void resetFrame()
{
warms = new Trainer(window_width, window_height, blocksize);
warms.train_setting();
Graphics g = CreateGraphics();
FrameUpdate();
g.DrawImage(GDIBuffer.Instance().GetImages, new Point(0, 0));
g.Dispose();
}
public MainForm()
{
MainForm.mf = this;
InitializeComponent();
this.SuspendLayout();
Setting.Instance();
warms = new Trainer(window_width, window_height, blocksize);
warms.train_setting();
Load += new EventHandler(MainForm_Load);
this.ResumeLayout(false);
}
public static List <Trainer> repList(List <Trainer> worm, int Evennum) // 두개의 뉴런값을 섞
{
List <Trainer> temp = new List <Trainer>(); // 우월한 유전자들 끼리 섞는 함수
Random r = MainForm.random;
int 교배수 = Setting.Instance().교배횟수;
for (int k = 0; k < Evennum / 2; k++)
{
Trainer child1 = new Trainer(Setting.Instance().mapSize_Width, Setting.Instance().mapSize_Height, Setting.Instance().블럭크기);
child1.train_setting();
Trainer child2 = new Trainer(Setting.Instance().mapSize_Width, Setting.Instance().mapSize_Height, Setting.Instance().블럭크기);
child2.train_setting();
child1._Genetic = worm[k % worm.Count]._Genetic.Clone(); // 부 유전자
child2._Genetic = worm[r.Next(0, worm.Count - 1)]._Genetic.Clone(); // 모 유전자
child1._Genetic.score = 1;
child2._Genetic.score = 1;
for (int i = 0; i < child1._Genetic.Middle_Neurons.Length; i++)
{
for (int j = 0; j < child1._Genetic.Middle_Neurons[i].Weighted_value.Length; j++)
{
if (r.Next(0, 100) < 40)
{
replaced(ref child1._Genetic.Middle_Neurons[i].Weighted_value[j], ref child2._Genetic.Middle_Neurons[i].Weighted_value[j], 교배수);
}
} // ref는 사용하기 전에 초기화
replaced(ref child1._Genetic.Middle_Neurons[i].Threshold_value, ref child2._Genetic.Middle_Neurons[i].Threshold_value, 교배수);
}
for (int i = 0; i < child1._Genetic.Output_Neurons.Length; i++)
{
for (int j = 0; j < child1._Genetic.Output_Neurons[i].Weighted_value.Length; j++)
{
if (r.Next(0, 100) < 40)
{
replaced(ref child1._Genetic.Output_Neurons[i].Weighted_value[j], ref child2._Genetic.Output_Neurons[i].Weighted_value[j], 교배수);
}
}
replaced(ref child1._Genetic.Output_Neurons[i].Threshold_value, ref child2._Genetic.Output_Neurons[i].Threshold_value, 교배수);
}
temp.Add(child1.Clone());
temp.Add(child2.Clone());
}
return(temp);
}
public void ReplayStart(Gen[] GData)
{
FrameCount = 0;
rotate = 0;
_Generation = 0;
trainers.Clear();
for (int i = 0; i < GData.Length; i++)
{
GData[i].score = 1;
warms = new Trainer(window_width, window_height, blocksize);
warms.train_setting();
}
frameTimer.Enabled = true;
}
public void TestStart()
{
FrameCount = 0;
rotate = 0;
_Generation = 0;
trainers.Clear();
GDIBuffer.Instance(window_width, window_height);
for (int i = 0; i < Setting.Instance().모집단; i++)
{
Trainer t = new Trainer(window_width, window_height, blocksize);
t.train_setting();
trainers.Add(t);
}
frameTimer.Enabled = true;
}
private void frameTimer_Tick(object sender, EventArgs e)
{
FrameCount++;
bool endcheck = false;
int start, end;
if (Setting.Instance().테스트단위 > Setting.Instance().모집단)
{
start = 0;
end = Setting.Instance().모집단;
}
else
{
if (rotate < Setting.Instance().모집단 / Setting.Instance().테스트단위)
{
start = rotate * Setting.Instance().테스트단위;
end = Setting.Instance().테스트단위 + Setting.Instance().테스트단위 *rotate;
}
else
{
start = rotate * Setting.Instance().테스트단위;
end = Setting.Instance().모집단 % Setting.Instance().테스트단위 + Setting.Instance().테스트단위 *rotate;
}
}
for (int i = start; i < end; i++)
{
trainers[i].FrameUpdate();
}
for (int i = start, k = 0; i < end; i++)
{
if (warms._Genetic.score <= trainers[i]._Genetic.score)
{
warms = trainers[i];
}
if (trainers[i].dead == 1) // 부딪히는 함수 추가필요
{
k++;
}
if (k == Setting.Instance().테스트단위 || k == Setting.Instance().모집단)
{
endcheck = true;
}
}
if (endcheck) // boolean = true -> 끝값이 수신되면
{
rotate = (rotate + 1);
FrameCount = 0;
warms = new Trainer(window_width, window_height, blocksize);
warms.train_setting();
}
if (rotate == (Setting.Instance().모집단 / Setting.Instance().테스트단위))
{
rotate = 0; // rotate 초기화
trainers.Sort((Trainer x, Trainer y) => y._Genetic.score.CompareTo(x._Genetic.score)); //내림차순 정렬
try
{
if (_Generation % Setting.Instance().저장간격 == 0)
{
IFormatter formatter = new BinaryFormatter();
Stream stream = new FileStream(Setting.Instance().저장위치 + @"\BestGeneration[" + _Generation + "].bin", FileMode.Create, FileAccess.Write, FileShare.None);
formatter.Serialize(stream, Setting.Instance());
for (int i = 0; i < Setting.Instance().저장개체수; i++)
{
formatter.Serialize(stream, trainers[i]._Genetic);
}
stream.Close();
}
using (StreamWriter w = File.AppendText(Setting.Instance().저장위치 + @"\BestGeneration.txt"))
{
//w.Write(log);
}
}
catch (Exception ee)
{
using (StreamWriter w = File.AppendText("BestGeneration.txt"))
{
// w.Write(log);
}
}
trainers = Generic.check(trainers, Setting.Instance().모집단); // 확률분포리스트를 뽑음
trainers = Generic.repList(trainers, Setting.Instance().모집단); // 교배 및 돌연변이
warms._Genetic.score = 1; // 점수 초기화
_Generation++; // 세대 +1
}
FrameUpdate();
FrameRender();
}
