/// <summary>
/// Gets the average score a brain gets over a number of boards
/// </summary>
/// <returns></returns>
private double AverageScore(Brain brain, int runs)
{
double minScore = 999999999;
double avgTime = 0;
double prevScore = 0;
double avgTurns = 0;
for (int i = 0; i < runs; i++)
{
NewBoard(i);
while (Board1.Progress1Tick())
{
RunBrain(Board1, brain);
}
prevScore += CalculateScore(Board1);
minScore = Math.Min(CalculateScore(Board1), minScore);
avgTime += Board1.Tick;
avgTurns += Board1.Turns;
}
avgTime /= runs;
avgTurns /= runs;
Console.WriteLine(minScore);
Console.WriteLine(avgTime);
Console.WriteLine(avgTurns);
return(prevScore / runs);
}
/**
* <summary>Generates new brains, the size of the brain is determined by height * width</summary>
* <param name="hlHeight">determines thd width of the hidden layer</param>
* <param name="hlWidth">determines the height of the hidden layers</param>
*/
private void ModeGenerateNewBrains(int hlWidth, int hlHeight)
{
NewBoard();
DrawFieldRectangles();
NewBrain(hlWidth, hlHeight);
while (savedFilesCount < savedFilesMax)
{
RedrawField();
bool gameOver = true;
for (int i = 0; i < 1000; i++)
{
if (Board1.Progress1Tick())
{
RunBrain();
gameOver = false;
}
else
{
gameOver = true;
break;
}
}
if (!gameOver)
{
continue;
}
Board1.GameOver = true;
//gameover
double score = CalculateScore();
if (score > ScoreTreshold)
{
try
{
string filename = "SnakeBrainFile" + Math.Floor(score).ToString() + "-" + DateTime.Now.Ticks.ToString() + ".dat";
FileStream SnakeBrainFile =
new FileStream(filename, FileMode.OpenOrCreate, FileAccess.Write);
Formatter.Serialize(SnakeBrainFile, SnakeBrain);
SnakeBrainFile.Close();
savedFilesCount++;
//MessageBox.Show("Saved snakebrain as " + filename);
}
catch (Exception err)
{
MessageBox.Show("Error saving snake brain.");
MessageBox.Show(err.Message);
}
//MessageBox.Show("You crashed into your own tail and died or you ran out of time, your final score was " + string.Format("{0:N2}", score) + "\n\nGrow more quickly and grow larger to gain a larger score");
}
NewBoard();
NewBrain(hlWidth, hlHeight);
}
MessageBox.Show("End of program, " + savedFilesCount.ToString() + " brain files generated.\nReview the executables' folder to see the brain files");
Restart();
}
private void DemoAICycle()
{
RedrawField();
if (Board1.Progress1Tick())
{
RunBrain();
}
else
{//gameOver
NewBoard();
}
}
private void DemoAICycle()
{
RedrawField();
if (Board1.Progress1Tick())
{
RunBrain(Board1, SnakeBrain);
}
else
{//gameOver
Counter++;
NewBoard(Counter);
}
}
/// <summary>
/// runs the main brain a few times after mutating it and returns its average score
/// </summary>
/// <param name="mutateMagnitude">The magnitude by which mutations can happen</param>
/// <param name="iterations">The number of times the snake plays the game before returning the average score.</param>
/// <param name="mutateNRR">Determines how much mutation magnitude distrubution conforms to a normal distribution.</param>
/// <returns>the average score</returns>
private double ModeTrainAI(double mutateMagnitude = .1, int mutateNRR = 4, int iterations = 100, int mutationChance = 5)
{
SnakeBrain.Mutate(mutateMagnitude, mutateNRR, mutationChance);
double averageScore = 0;
for (int i = 0; i < iterations; i++)
{
NewBoard(i);
while (Board1.Progress1Tick())
{
RunBrain();
}
averageScore += CalculateScore();
}
return(averageScore / iterations);
}
/// <summary>
/// runs the main brain a few times after mutating it and returns its average score
/// </summary>
/// <param name="mutateMagnitude">The magnitude by which mutations can happen</param>
/// <param name="iterations">The number of times the snake plays the game before returning the average score.</param>
/// <param name="mutateNRR">Determines how much mutation magnitude distrubution conforms to a normal distribution.</param>
/// <param name="randomly">Whether or not to use deterministic brain changes</param>
/// <param name="incrementor">if non-random then this must should increment by 1 each call</param>
/// <returns>the average score</returns>
private double ModeTrainAI(double mutateMagnitude = .1, int mutateNRR = 4, int iterations = 100, int nrOfMutations = 2, bool randomly = false, int incrementor = 0)
{
if (randomly)
{
SnakeBrain.Mutate(mutateMagnitude, mutateNRR, nrOfMutations);
}
double averageScore = 0;
for (int i = 0; i < iterations; i++)
{
NewBoard(i);
while (Board1.Progress1Tick())
{
RunBrain(Board1, SnakeBrain);
}
averageScore += CalculateScore(Board1);
}
return(averageScore / iterations);
}
private void ModeTrainAIButton_Click(object sender, RoutedEventArgs e)
{
if (!double.TryParse(ModeTrainAIDegreeBox.Text, out double degree))
{
MessageBox.Show("Invalid interval value, please input a double (aka. decimal) value");
return;
}
if (!int.TryParse(ModeTrainAIIterationsBox.Text, out int iterations))
{
MessageBox.Show("Invalid iterations value, please input an integer");
return;
}
if (!int.TryParse(ModeTrainAIMutationChanceBox.Text, out int mutationChance))
{
MessageBox.Show("Invalid mutation chance value, please input an integer");
return;
}
mutationChance = 100 / mutationChance;
if (!int.TryParse(ModeTrainAINRRBox.Text, out int nrr))
{
MessageBox.Show("Invalid NRR value, please input an integer");
return;
}
if (!double.TryParse(ModeTrainAITresholdBox.Text, out double treshold))
{
MessageBox.Show("Invalid treshold value, please input a double");
return;
}
OpenFileDialog dlg = new OpenFileDialog
{
DefaultExt = ".dat",
Filter = "Data Files (*.dat)|*.dat"
};
bool?result = dlg.ShowDialog();
if (result != true)
{
MessageBox.Show("Couldn't recover file path");
return;
}
if (!File.Exists(dlg.FileName))
{
MessageBox.Show("Couldn't find that file");
return;
}
try
{
FileStream SnakeBrainInstanceFromFile = new FileStream(dlg.FileName, FileMode.Open, FileAccess.Read);
SnakeBrain = (Brain)Formatter.Deserialize(SnakeBrainInstanceFromFile);
SnakeBrainInstanceFromFile.Close();
}
catch (Exception err)
{
MessageBox.Show("Could not load selected snake brain file for this demo");
MessageBox.Show(err.Message);
return;
}
int len = MainGrid.Children.Count;
for (int i = 0; i < len; i++)
{
MainGrid.Children.RemoveAt(0);
}
NewBoard();
DrawFieldRectangles();
Brain prevBrain = DeepCopy(SnakeBrain);
double prevScore = 0;
for (int i = 0; i < iterations; i++)
{
NewBoard();
while (Board1.Progress1Tick())
{
RunBrain();
}
prevScore += CalculateScore();
}
prevScore /= iterations;
MinScore = prevScore * 0.75;
int count = 1000000000;
while (--count > 0)
{
double score = ModeTrainAI(degree, nrr, iterations, mutationChance);
if (score / treshold > prevScore && score > MinScore)
{
if (score * .75 > MinScore)
{
MinScore = score * .75;
try
{
string filename = "TrainedSnakeBrainFile" + Math.Floor(score).ToString() + "-" + SnakeBrain.HiddenLayerWidth + "-" + SnakeBrain.HiddenLayerHeight + "-" + iterations.ToString() + "-" + DateTime.Now.Ticks.ToString() + ".dat";
FileStream SnakeBrainFile =
new FileStream(filename, FileMode.OpenOrCreate, FileAccess.Write);
Formatter.Serialize(SnakeBrainFile, SnakeBrain);
SnakeBrainFile.Close();
savedFilesCount++;
}
catch (Exception err)
{
MessageBox.Show("Error saving snake brain.");
MessageBox.Show(err.Message);
}
}
prevScore = score;
prevBrain = DeepCopy(SnakeBrain);
}
else
{
SnakeBrain = DeepCopy(prevBrain);
}
if (savedFilesCount > savedFilesMax)
{
break;
}
}
}
