/// <summary>
/// This is where RLM is being configured and trained. Call this method and pass the needed parameters to start the training.
/// </summary>
/// <param name="maze">Contains all the details of the maze that encog will be going to solve.</param>
/// <param name="gameTimeout">The given time for solving the maze per session.</param>
public static void MazeTrain(MazeInfo maze, int gameTimeout)
{
Console.WriteLine("RLM network settings:");
int sessions = Util.GetInput("Number of sessions [default 50]: ", 50); //Gets user input for the number of sessions
int startRandomness = Util.GetInput("Start randomness [default 100]: ", 100); //Gets user input for the start randomness
int endRandomness = Util.GetInput("End randomness [default 0]: ", 0); //Gets user input for the end randomness
int randomnessThrough = Util.GetInput("Number of sessions to enforce randomness [default 1]: ", 1);
Console.WriteLine();
try
{
RLMMazeTraveler traveler = new RLMMazeTraveler(maze, true, randomnessThrough, startRandomness, endRandomness); //Instantiate RlmMazeTraveler game lib to configure the network.
traveler.SessionComplete += SesionComplete;
System.Diagnostics.Stopwatch watch = new System.Diagnostics.Stopwatch();
watch.Start();
//Start the training (Play the game)
for (int i = 0; i < randomnessThrough; i++)
{
traveler.Travel(gameTimeout);
}
// set to predict instead of learn for the remaining sessions
traveler.Learn = false;
for (int i = 0; i < sessions - randomnessThrough; i++)
{
traveler.Travel(gameTimeout);
}
watch.Stop();
Console.WriteLine($"Elapsed: {watch.Elapsed}");
traveler.TrainingDone();
Console.ReadLine();
}
catch (Exception e)
{
if (e.InnerException != null && e.InnerException is RlmDefaultConnectionStringException)
{
Console.WriteLine($"Error: {e.InnerException.Message}");
}
else
{
Console.WriteLine($"ERROR: {e.Message}");
}
}
}
private async Task StartGame(RLMMazeTraveler traveler)
{
int currentSession = 0;
while (currentSession < TotalIterations)
{
currentSession++;
lblCurrentSession.Content = currentSession;
//var outcome = await traveler.Travel(currentSession);
var outcome = traveler.Travel(currentSession);
//var data = traveler.BumpedIntoWallPercentage;
//lblBumpedIntoWall.Content = $"{data.ToString("#0.##")}%";
lblMoveCount.Content = outcome.Moves;
lblSessionsCompleted.Content = outcome.FinalScore;
}
}
private async void windowLessTraining_Loaded_1(object sender, RoutedEventArgs e)
{
if (isEncog)
{
//EncogMaze encogMaze = new EncogMaze(maze);
//encogMaze.MazeCycleComplete += Traveler_MazeCycleComplete;
////encogMaze.EncogCycleComplete += EncogMaze_EncogCycleComplete;
//encogMaze.TrainingIterationComplete += EncogMaze_TrainingIterationComplete;
//await StartGame(encogMaze);
}
else
{
// reset session count
//RNNMazeTraveler.ResestStaticSessionData();
traveler = new RLMMazeTraveler(maze, Learn, Temp_num_sessions, StartRandomness, EndRandomness);
traveler.MazeCycleComplete += Traveler_MazeCycleComplete;
traveler.SessionStarted += Traveler_SessionStarted;
await StartGame(traveler);
}
}
async void Init(MazeInfo mazeInfo)
{
if (!Learn)
{
CurrentIteration = 1;
Temp_num_sessions = 1;
StartRandomness = 0;
EndRandomness = 0;
}
replayMemory = new object[Temp_num_sessions];
StatusText.Content = "Initializing RLM engine...";
await Task.Run(() => {
RLMMazeTraveler traveler = new RLMMazeTraveler(mazeInfo, Learn, Temp_num_sessions, StartRandomness, EndRandomness); //Instantiate RlmMazeTraveler game lib to configure the network.
traveler.SessionComplete += Traveler_SessionComplete;
traveler.MazeCycleComplete += Traveler_MazeCycleComplete;
traveler.SessionStarted += Traveler_SessionStarted;
traveler.MazeCycleError += mazecycle_error;
game.traveler = traveler;
if (Learn)
{
RunUIThread(() => {
StatusText.Content = "Training started...";
});
//Start the training (Play the game)
for (int i = 0; i < RandomnessOver; i++)
{
locations = new List <Location>();
RunUIThread(() => {
lblCurrentSession.Content = 1;
});
CurrentIteration = i + 1;
traveler.Travel(10000);
}
// set to predict instead of learn for the remaining sessions
traveler.Learn = false;
for (int i = 0; i < Temp_num_sessions - RandomnessOver; i++)
{
CurrentIteration++;
locations = new List <Location>();
RunUIThread(() => {
StatusText.Content = $"Training started... {CurrentIteration * 100 / Temp_num_sessions}%";
});
traveler.Travel(10000);
}
//traveler.TrainingDone();
RunUIThread(() => {
StatusText.Content = $"Training done... 100%";
});
}
else
{
RunUIThread(() => {
StatusText.Content = $"RLM preparing to play...";
});
locations = new List <Location>();
RunUIThread(() => {
StatusText.Content = $"RLM Playing...";
});
traveler.Learn = false;
traveler.Travel(10000);
}
}).ContinueWith(async(t) => {
//show AI playing game
Stopwatch watch = new Stopwatch();
foreach (dynamic obj in replayMemory)
{
RunUIThread(() =>
{
lblCurrentSession.Content = (int)obj.cycleNum + 1;
lblRandomness.Content = (int)obj.randomnessLeft;
});
watch.Start();
foreach (Location loc in obj.moves as List <Location> )
{
var x = loc.X;
var y = loc.Y;
RunUIThread(() =>
{
maze.ChangeCellColor(new TravelerLocation()
{
X = loc.X, Y = loc.Y
}, true);
});
await Task.Delay(TimeSpan.FromMilliseconds(2));
//If game is not solved within 5s, go to the next session.
if (watch.Elapsed.TotalSeconds >= 10)
{
break;
}
}
watch.Reset();
RunUIThread(() => {
lblScore.Content = (double)obj.score;
lblMoves.Content = (int)obj.movesCnt;
if (!Learn)
{
StatusText.Content = $"RLM done playing...";
}
else
{
StatusText.Content = $"Showing rlm replay...";
}
maze.setGoalRect();
});
}
RunUIThread(() => {
StatusText.Content = $"Done. Close the window to return back to the menu and train again...";
});
}, TaskContinuationOptions.OnlyOnRanToCompletion);
}
/// <summary>
/// This is where RLM is being configured and trained.
/// </summary>
public void MazeTrain()
{
int mazeSize = Util.GetInput($"Enter Maze size [must be {MIN_MAZE_SIZE} or greater]: ", MIN_MAZE_SIZE);
var maze = GenerateOrGetExistingMaze(mazeSize);
int gameTimeout = Util.GetInput($"Game timeouts after [{MAZE_GAME_TIMEOUT} seconds default]: ", MAZE_GAME_TIMEOUT);
Console.WriteLine($"Perfect move count for this maze would be {maze.PerfectGameMovesCount}");
Console.WriteLine();
Console.WriteLine("RLM network settings:");
int sessions = Util.GetInput("Number of sessions [default 50]: ", 50); //Gets user input for the number of sessions
int startRandomness = Util.GetInput("Start randomness [default 100]: ", 100); //Gets user input for the start randomness
int endRandomness = Util.GetInput("End randomness [default 0]: ", 0); //Gets user input for the end randomness
int randomnessThrough = Util.GetInput("Number of sessions to enforce randomness [default 1]: ", 1);
try
{
RLMMazeTraveler traveler = new RLMMazeTraveler(maze, true, randomnessThrough, startRandomness, endRandomness); //Instantiate RlmMazeTraveler game lib to configure the network.
traveler.SessionComplete += SesionComplete;
// execute it on another thread as not to block the RLM training
Console.WriteLine("\nPress 'd' to show Data persistence progress\n");
Task.Run(() =>
{
while (!Console.KeyAvailable && Console.ReadKey(true).Key == ConsoleKey.D)
{
traveler.ShowDataPersistenceProgress = true;
}
});
System.Diagnostics.Stopwatch watch = new System.Diagnostics.Stopwatch();
watch.Start();
traveler.ResetRLMRandomization();
//Start the training (Play the game)
for (int i = 0; i < randomnessThrough; i++)
{
traveler.Travel(gameTimeout * 1000);
}
// set to predict instead of learn for the remaining sessions
traveler.Learn = false;
for (int i = 0; i < sessions - randomnessThrough; i++)
{
traveler.Travel(gameTimeout * 1000);
}
watch.Stop();
Console.WriteLine($"Elapsed: {watch.Elapsed}");
traveler.TrainingDone();
Console.ReadLine();
}
catch (Exception e)
{
if (e.InnerException != null && e.InnerException is RlmDefaultConnectionStringException)
{
Console.WriteLine($"Error: {e.InnerException.Message}");
}
else
{
Console.WriteLine($"ERROR: {e.Message}");
}
}
}
