static void DrawBoard(Trainer trainer)
{
lock (DrawLock)
{
Console.SetCursorPosition(0, 0);
var b = trainer.Game.Board;
string upper = " ┌───┬───┬───┬═══┬═══┬───┬───┬───┐";
//string row = " │ │ │ │ │ │ │ │ │";
string middle = " ├───┼───┼───┼───┼───┼───┼───┼───┤";
string lower = " └───┴───┴───┴═══┴═══┴───┴───┴───┘";
string xlabel = " a b c d e f g h";
Console.WriteLine(upper);
for (int y = 8; y > 0; --y)
{
Console.Write(" " + y + " │");
for (int x = 0; x < 8; ++x)
{
var card = b[x, y - 1].Card;
if (card == null)
{
Console.Write(" ");
}
else
{
var oldCol = Console.ForegroundColor;
Console.ForegroundColor = card.Owner.PlayerNumber == 1 ? ConsoleColor.Cyan : ConsoleColor.Red;
if (card is FirewallCard)
{
Console.Write(" F ");
}
else
{
var onlCard = card as OnlineCard;
if (onlCard == null)
{
Console.Write("err");
}
else
{
if (onlCard.Type == OnlineCardType.Unknown)
{
Console.Write(onlCard.HasBoost ? "-X-" : " X ");
}
else if (onlCard.Type == OnlineCardType.Link)
{
Console.Write(onlCard.HasBoost ? "-L-" : " L ");
}
else if (onlCard.Type == OnlineCardType.Virus)
{
Console.Write(onlCard.HasBoost ? "-V-" : " V ");
}
else
{
Console.Write("ERR");
}
}
}
Console.ForegroundColor = oldCol;
}
Console.Write("│");
}
if (y == 8)
{
Console.WriteLine(" Stack: ");
Console.Write(middle + " P2: ");
DrawStack(9, trainer);
Console.WriteLine();
}
else if (y == 7)
{
Console.Write(" P1: ");
DrawStack(8, trainer);
Console.WriteLine();
Console.WriteLine(middle);
}
else if (y == 6)
{
Console.WriteLine(" Game Phase: " + trainer.Game.Phase + " ");
Console.WriteLine(middle + " Round: " + trainer.Round + " ");
}
else if (y == 5)
{
Console.WriteLine(" Generation: " + (gen + 1) + "/" + maxGen + " ");
Console.WriteLine(middle + " Progress: " + genProgress + "% ");
}
else if (y == 2)
{
Console.WriteLine(" Board: ");
Console.WriteLine(middle + " X = Unknown");
}
else if (y == 1)
{
Console.WriteLine(" L = Link ");
Console.WriteLine(lower + " V = Virus");
}
else
{
Console.WriteLine();
if (y > 1)
{
Console.WriteLine(middle);
}
}
}
//Console.WriteLine(lower);
Console.WriteLine(xlabel);
}
}
static void Main(string[] args)
{
Console.WriteLine("NOU AI Trainer\n");
Console.WriteLine("Select mode: ");
Console.WriteLine("\t1: Genetic algorithm against MIA AI. (default)");
Console.WriteLine("\t2: Backproagation learning from MIA AI.");
var usrInput = Console.ReadLine();
if (usrInput == "2")
{
BackPropTraining();
return;
}
Console.Clear();
Console.WriteLine("NOU AI Trainer\n");
string dir = "Nou_AI";
string genTxt = dir + "\\gen.txt";
string genLogTxt = dir + "\\genLog.txt";
Func <int, int, string> netFile = (a, b) => { return(dir + "\\net" + a + "." + b + ".txt"); };
if (!Directory.Exists(dir))
{
Directory.CreateDirectory(dir);
}
if (File.Exists(genTxt))
{
uint.TryParse(File.ReadAllText(genTxt), out gen);
}
Console.WriteLine("Current generation: " + gen);
Console.WriteLine("Please enter number of iterations: ");
var inp = Console.ReadLine();
if (!uint.TryParse(inp, out uint gen2Go))
{
Console.WriteLine("Not a number! Press any key to exit");
Console.ReadKey();
return;
}
Console.CursorVisible = false;
Trainer.MaxRound = 15;
// We have 50 AIs. All fight the same MIA instance.
int aiCnt = 50; // Number of AIs per generation
double mutationDelta = Nou.MutateDelta / 3;
var log = new Dictionary <int, TrainingLog>();
var fac = new NouFactory(); // Loads pretrained NouAi_0.txt
for (int i = 0; i < aiCnt; ++i)
{
log.Add(i, new TrainingLog {
AI = (Nou)fac.CreateInstance(), ID = i
});
}
// Check if there are saved nets on the hard drive
if (gen > 0) // Ignore if we start from gen 0
{
for (int i = 0; i < aiCnt; ++i)
{
log[i].AI.ReadFromFile(0, netFile(i, 0));
log[i].AI.ReadFromFile(1, netFile(i, 1));
}
}
var rnd = new Random(); // Used for applying seed to MIA.
genProgress = 0;
maxGen = gen + gen2Go;
byte mutateFlags = 1; // Only train net1.
// Cycle through all defined generations
for (int it = 0; it < gen2Go; ++it)
{
genProgress = (int)(0.5 + 100.0 * ((1.0 * it) / gen2Go));
int curGenSeed = rnd.Next();
int nouSeed = rnd.Next();
#region NextGen Prep
if (it > 0)
{
// Based on 50 AIs:
// 1. Delete the 25 least scoring nets
// 2. Keep the best 5 nets untouched // +5 -> 5
// 3. Mutate the remaining 20 nets // +20 -> 25
// 4. Create 4 copies of the 5 best
// nets and mutate them // +20 -> 45
// 5. Add 5 ranom nets // +5 -> 50
// We do not create new randoms AIs.
// All our progress might get lost if a random ai accidentally scores high
// 1. + 2.
// Sort by score
var sortedList = log.Select(o => o.Value).OrderByDescending(o => o.Score).ToList();
log.Clear(); // Clear list
for (int i = 0; i < aiCnt / 2; ++i) // Add the 25 best nets
{
sortedList[i].ID = i; // Update ID
log.Add(i, sortedList[i]);
}
// 3. Mutate the last 20 nets in the new list
for (int i = 5; i < aiCnt / 2; ++i)
{
log[i].AI.Mutate(mutationDelta, mutateFlags);
}
// 4.
int fillerRatio = (aiCnt / 2 - 5) / 4; // =5 when aiCnt=50
int nId = aiCnt / 2;
for (int iAi = 0; iAi < 5; iAi++) // The first five AIs
{
for (int ii = 0; ii < fillerRatio; ++ii)
{
var nou = Nou.Copy(log[iAi].AI);
nou.Mutate(mutationDelta, mutateFlags);
log[nId] = new TrainingLog()
{
ID = nId, AI = nou
};
++nId;
}
}
// 5.
while (log.Count < aiCnt)
{
log.Add(log.Count, new TrainingLog {
ID = log.Count, AI = (Nou)fac.CreateInstance()
});
}
}
// Reset score at the start of each generation
for (int ai = 0; ai < aiCnt; ++ai)
{
log[ai].Score = 0;
}
#endregion
Trainer trainer = null;
// Cycle through all AIs
Parallel.ForEach(log.Select(o => o.Value), new ParallelOptions()
{
MaxDegreeOfParallelism = 8
}, (aiLog) =>
{
Trainer trn = new Trainer();
var mia = new Mia();
mia.SetSeed(curGenSeed);
mia.Depth = 1;
if (aiLog.ID == 0)
{
trainer = trn;
trn.AiDelay = 0; // This is the displayed trainer.
}
var waitHandle = new AutoResetEvent(false);
EventHandler handler = (s, a) =>
{
if (trn.GameOver)
{
try { waitHandle.Set(); } catch { }
}
};
trn.NeedsUiUpdate += handler;
aiLog.AI.DeploySeed = nouSeed;
// Run game:
trn.StartGame(aiLog.AI, mia);
waitHandle.WaitOne(100 * Trainer.MaxRound); // Give 100ms per round
trn.NeedsUiUpdate -= handler;
trn.Abort = true;
if (trn.Game.Phase == GamePhase.Player1Win)
{
Interlocked.Increment(ref nouWins);
}
else if (trn.Game.Phase == GamePhase.Player2Win)
{
Interlocked.Increment(ref miaWins);
}
// Post Game: Add score
aiLog.Score = aiLog.AI.Fitness();
});
genProgress = (int)(0.5 + 100.0 * ((it + 1.0) / gen2Go));
if (trainer != null)
{
DrawBoard(trainer);
}
// Log score to file
++gen;
try
{
var genSorted = log.Select(o => o.Value).OrderByDescending(o => o.Score).ToList();
using (var f = File.AppendText(genLogTxt))
{
f.WriteLine("Gen:\t" + gen + "\tScore:\t" + genSorted[0].Score.ToString(System.Globalization.CultureInfo.InvariantCulture));
}
}
catch { }
}
// Save all current Nets
for (int i = 0; i < aiCnt; ++i)
{
log[i].AI.Net1.SaveAsFile(netFile(i, 0));
log[i].AI.Net2.SaveAsFile(netFile(i, 1));
}
File.WriteAllText(genTxt, gen.ToString());
System.Threading.Thread.Sleep(500); // Wait for UI updates
Console.CursorVisible = true;
Console.WriteLine("Finished. Press any key to exit");
Console.ReadKey();
}