/// <summary>
/// Show replay of the given agent.
/// </summary>
/// <param name="agentToShow"></param>
/// <param name="geneticSettings"></param>
public void ViewAgent(Agent agentToShow, GeneticSettings geneticSettings)
{
networkSettings = (geneticSettings.FitnessCalculator as SnakeFitnessCalculator).NetworkSettings;
snakeSettings = (geneticSettings.FitnessCalculator as SnakeFitnessCalculator).SnakeSettings;
SnakeFitnessCalculator fitnessCalculator = geneticSettings.FitnessCalculator as SnakeFitnessCalculator;
FitnessCalculatorRecording recording = fitnessCalculator.RecordCalculation(agentToShow);
MilisecondsForm milisecondsForm = new MilisecondsForm();
milisecondsForm.ShowDialog();
speedMS = milisecondsForm.speedMS;
ShowPlay(recording);
}
private void ShowPlay(FitnessCalculatorRecording recorder)
{
List <FitnessRoundInfo> fitnessRoundInfoList = recorder.FitnessRoundInfoList;
int score = recorder.InitialFitnessRoundInfo.Score;
bool isAlive = recorder.InitialFitnessRoundInfo.IsAlive;
UpdateCurrentGridInitial(recorder.InitialFitnessRoundInfo.ChangedFields);
SnakeGameGUI snakeGameGUI = new SnakeGameGUI(snakeSettings, currentGrid, score, isAlive);
// START GUI
snakeGameGUI.OpenGameWindow();
// Loop throug frames.
for (int i = 0; i < fitnessRoundInfoList.Count; i++)
{
UpdateCurrentGrid(fitnessRoundInfoList[i].ChangedFields);
snakeGameGUI.UpdateView(currentGrid, fitnessRoundInfoList[i].Score, fitnessRoundInfoList[i].IsAlive, fitnessRoundInfoList[i].SnakeHeadPoint);
Thread.Sleep(speedMS);
}
}
/// <summary>
/// Calculates the resulting fitness value by using the passed weights
/// and returns the value in a FitnessInfo class together with other relevant info about the calculation.
/// </summary>
public IFitnessInfo CalculateFitness(double[] weightsForNeuralNetwork)
{
int action = 0;
int currentScore = 0;
int movesSincePoint = 0;
int movesTotal = 0;
double fitness = 0;
double averageMovesPerFood = 0;
double[] input = new double[ProgramSettings.NUMBER_OF_INPUT_NEURONS];
EndGameInfo endGameInfo;
// Setup new snake game and neural network
neuralNetwork = new NeuralNetwork(NetworkSettings, weightsForNeuralNetwork);
snakeGame = new SnakeGame(SnakeSettings);
// Make recorder
if (record)
{
recorder = new FitnessCalculatorRecording(agentToRecord, NetworkSettings, SnakeSettings);
recorder.TakeSnapShotInitial(snakeGame, movesSincePoint, movesTotal, input, neuralNetwork);
}
// Simulation begins
do
{
input = ConvertGridToInput(snakeGame.Grid, snakeGame.Snake, snakeGame.Food);
action = neuralNetwork.CalculateOutput(input);
snakeGame.UpdateDirection(action);
// Check if got point
if (snakeGame.Score != currentScore)
{
movesSincePoint = 0;
currentScore = snakeGame.Score;
}
else
{
movesSincePoint++;
}
movesTotal++;
if (record) // Save round info.
{
recorder.TakeSnapShotRound(snakeGame, movesSincePoint, movesTotal, input, neuralNetwork);
}
FitnessRoundsCount++;
} while(snakeGame.Snake.IsAlive && movesSincePoint < GetMaxMoves(snakeGame.Snake.Lenght));
if (snakeGame.FoodEaten != 0)
{
averageMovesPerFood = movesTotal / (double)snakeGame.FoodEaten;
}
fitness = snakeGame.Score;
endGameInfo = new EndGameInfo(snakeGame, fitness, averageMovesPerFood, movesTotal);
if (record)
{
recorder.TakeSnapShotEndGame(endGameInfo);
}
return(endGameInfo);
}
