// Selection function to find most probable parents of the generation
NN_Data[] SelectParents()
{
NN_Data[] parents = new NN_Data[2];
// Get the fitness of all runners combined
int combinedFitness = 0;
foreach (var stats in deathList)
{
combinedFitness += stats.framesAlive;
}
// Get a random value between 0 and the combinedFitness. Use this to find a probable parent
for (int p_Index = 0; p_Index < 2; p_Index++)
{
int randFitness = Random.Range(0, combinedFitness) - deathList[0].framesAlive;
int locatedID = 0;
while (randFitness > 0)
{
locatedID++;
randFitness -= deathList[locatedID].framesAlive;
}
parents[p_Index] = deathList[locatedID].nn_data;
}
return(parents);
}
// Combine 2 parents' DNA using crossover & apply mutations
NN_Data CrossOver(NN_Data[] parents)
{
float[,] ih_w = new float[parents[0].ih_w.GetLength(0), parents[0].ih_w.GetLength(1)];
float[] ih_b = new float[parents[0].ih_b.Length];
float[,] ho_w = new float[parents[0].ho_w.GetLength(0), parents[0].ho_w.GetLength(1)];
float[] ho_b = new float[parents[0].ho_b.Length];
for (int row = 0; row < ih_w.GetLength(0); row++)
{
for (int col = 0; col < ih_w.GetLength(1); col++)
{
ih_w[row, col] = parents[Random.Range(0, 2)].ih_w[row, col];
if (mutationPercentage > Random.value)
{
ih_w[row, col] += (Random.value - .5f) * mutationScale;
}
}
}
for (int element = 0; element < ih_b.Length; element++)
{
ih_b[element] = parents[Random.Range(0, 2)].ih_b[element];
if (mutationPercentage > Random.value)
{
ih_b[element] += (Random.value - .5f) * mutationScale;
}
}
for (int row = 0; row < ho_w.GetLength(0); row++)
{
for (int col = 0; col < ho_w.GetLength(1); col++)
{
ho_w[row, col] = parents[Random.Range(0, 2)].ho_w[row, col];
if (mutationPercentage > Random.value)
{
ho_w[row, col] += (Random.value - .5f) * mutationScale;
}
}
}
for (int element = 0; element < ho_b.Length; element++)
{
ho_b[element] = parents[Random.Range(0, 2)].ho_b[element];
if (mutationPercentage > Random.value)
{
ho_b[element] += (Random.value - .5f) * mutationScale;
}
}
NN_Data childDNA = new NN_Data();
childDNA.UpdateData(ih_w, ih_b, ho_w, ho_b);
return(childDNA);
}
// Get saved NN data from a playerID
public static NN_Data ReadData(int playerID)
{
if (File.Exists(path + "Runner" + playerID.ToString() + ".txt"))
{
string[] lines = File.ReadAllLines(path + "Runner" + playerID.ToString() + ".txt");
string[] ih_w_rows = lines[0].Split(':');
float[,] ih_w = new float[ih_w_rows.Length, ih_w_rows[0].Split(',').Length];
for (int row = 0; row < ih_w.GetLength(0); row++)
{
string[] ih_w_cols = ih_w_rows[row].Split(',');
for (int col = 0; col < ih_w.GetLength(1); col++)
{
//File.WriteAllText(path + "Debug.txt", ih_w_cols[col]);
ih_w[row, col] = float.Parse(ih_w_cols[col]);
}
}
string[] ih_b_elements = lines[1].Split(',');
float[] ih_b = new float[ih_b_elements.Length];
for (int element = 0; element < ih_b_elements.Length; element++)
{
ih_b[element] = float.Parse(ih_b_elements[element]);
}
string[] ho_w_rows = lines[2].Split(':');
float[,] ho_w = new float[ho_w_rows.Length, ho_w_rows[0].Split(',').Length];
for (int row = 0; row < ho_w.GetLength(0); row++)
{
string[] ho_w_cols = ho_w_rows[row].Split(',');
for (int col = 0; col < ho_w.GetLength(1); col++)
{
ho_w[row, col] = float.Parse(ho_w_cols[col]);
}
}
string[] ho_b_elements = lines[3].Split(',');
float[] ho_b = new float[ho_b_elements.Length];
for (int element = 0; element < ho_b_elements.Length; element++)
{
ho_b[element] = float.Parse(ho_b_elements[element]);
}
NN_Data readData = new NN_Data();
readData.UpdateData(ih_w, ih_b, ho_w, ho_b);
return(readData);
}
else
{
return(null);
}
}
public void RunnerDies(int framesAlive, NN_Data nn_data)
{
deathCount++;
deathList.Add(new RunnerDeathStats((int)Mathf.Pow((float)framesAlive, fitnessInfluence), nn_data));
// When all runners are dead use their stats to reproduce
if (deathCount == numberOfRunners)
{
Reproduce();
}
}
// Save NN data to a playerID
public static void WriteData(int playerID, NN_Data data)
{
// Add all data values to List<string> and save to txt file
List <string> lines = new List <string>()
{
"", "", "", ""
};
for (int row = 0; row < data.ih_w.GetLength(0); row++)
{
for (int col = 0; col < data.ih_w.GetLength(1); col++)
{
lines[0] += data.ih_w[row, col].ToString() + ",";
}
lines[0] += ":";
}
for (int element = 0; element < data.ih_b.Length; element++)
{
lines[1] += data.ih_b[element].ToString() + ",";
}
for (int row = 0; row < data.ho_w.GetLength(0); row++)
{
for (int col = 0; col < data.ho_w.GetLength(1); col++)
{
lines[2] += data.ho_w[row, col].ToString() + ",";
}
lines[2] += ":";
}
for (int element = 0; element < data.ho_b.Length; element++)
{
lines[3] += data.ho_b[element].ToString() + ",";
}
// Clean up line endings
for (int line = 0; line < lines.Count; line++)
{
lines[line] = lines[line].Replace(",:", ":");
lines[line] = lines[line].TrimEnd(':');
lines[line] = lines[line].TrimEnd(',');
}
File.WriteAllLines(path + "Runner" + playerID.ToString() + ".txt", lines);
}
public NN(int playerID, int inputNodes, int hiddenNodes, int outputNodes)
{
NN_Data saveData = FileCtrl.ReadData(playerID);
// If file exists for this playerID, read file and set NN data
if (saveData != null)
{
nn_data.ih_w = saveData.ih_w;
nn_data.ih_b = saveData.ih_b;
nn_data.ho_w = saveData.ho_w;
nn_data.ho_b = saveData.ho_b;
}
// If file does not exist for this playerID, create new set of NN_Data
else
{
nn_data.ih_w = Math.RandomMatrix(inputNodes, hiddenNodes);
nn_data.ih_b = Math.RandomLst(hiddenNodes);
nn_data.ho_w = Math.RandomMatrix(hiddenNodes, outputNodes);
nn_data.ho_b = Math.RandomLst(outputNodes);
}
}
// Genetic algorithm to create new neural networks
void Reproduce()
{
// Breed and save children to file
for (int ID = 0; ID < numberOfRunners - 1; ID++)
{
// Selection
NN_Data[] parents = SelectParents();
// Cross Over to child DNA and mutate the child's DNA
NN_Data childDNA = CrossOver(parents);
// Save new genes
FileCtrl.WriteData(ID, childDNA);
}
// Save the fittest runner on his own
FileCtrl.WriteData(deathList.Count - 1, deathList[deathList.Count - 1].nn_data);
FileCtrl.SaveStats(generation + 1, deathList[deathList.Count - 1].framesAlive);
UnityEngine.SceneManagement.SceneManager.LoadScene(0);
}
public RunnerDeathStats(int framesAlive, NN_Data nn_data)
{
this.framesAlive = framesAlive;
this.nn_data = nn_data;
}
