public MoveOnlyAlphaBetaWithPreplacerMoveMaker(int maxSearchDepth, IUtilityCalculator calculator, PreplacerStrategy preplacer)
{
_thisThreadPool = _pool.Value;
_maxSearchDepth = maxSearchDepth;
_calculator = calculator;
_preplacer = preplacer;
}
public MoveOnlyMonteCarloTreeSearchWithPreplacerMoveMaker(int iterations, IMoveDecisionMaker rolloutMoveMaker, PreplacerStrategy preplacer) : base(iterations, rolloutMoveMaker)
{
_preplacer = preplacer;
}
static void TestFullAi()
{
var aiToTest = new Func <PlayerDecisionMaker>[]
{
//() => new PlayerDecisionMaker(new GreedyCardValueUtilityMoveMaker(-1), PlacementMaker.TightDoublerInstance),
//() => new PlayerDecisionMaker(new GreedyCardValueUtilityMoveMaker(0), PlacementMaker.TightDoublerInstance),
//() => new PlayerDecisionMaker(new GreedyCardValueUtilityMoveMaker(1), PlacementMaker.TightDoublerInstance),
//() => new PlayerDecisionMaker(new GreedyCardValueUtilityMoveMaker(2), PlacementMaker.TightDoublerInstance),
//
//() => new PlayerDecisionMaker(new GreedyCardValueUtilityMoveMaker(-1), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
//() => new PlayerDecisionMaker(new GreedyCardValueUtilityMoveMaker(0), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
//() => new PlayerDecisionMaker(new GreedyCardValueUtilityMoveMaker(1), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
//() => new PlayerDecisionMaker(new GreedyCardValueUtilityMoveMaker(2), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
//() => new PlayerDecisionMaker(new QuickRandomSearchMoveMaker(6, 1000), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
//() => new PlayerDecisionMaker(new QuickRandomSearchMoveMaker(10, 2000), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
//() => new PlayerDecisionMaker(new QuickRandomSearchMoveMaker(20, 5000), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
//() => new PlayerDecisionMaker(new QuickRandomSearchMoveMaker(30, 10000), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
//() => new PlayerDecisionMaker(new MoveOnlyMonteCarloTreeSearchMoveMaker(1000, TuneableUtilityMoveMaker.Tuning1), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
() => new PlayerDecisionMaker(new MoveOnlyMonteCarloTreeSearchMoveMaker(10000, TuneableUtilityMoveMaker.Tuning1), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
() => new PlayerDecisionMaker(new MoveOnlyMonteCarloTreeSearchMoveMaker(10000, TuneableUtilityMoveMaker.Tuning1), new PlacementMaker(new BestEvaluatorStrategy(TuneablePattern2x2BoardEvaluator.Tuning1))),
() =>
{
var p = new PreplacerStrategy(new EvaluatorTreeSearchPreplacer(TuneablePattern2x2BoardEvaluator.Tuning1, 4, 4, true));
var m = new MoveOnlyMonteCarloTreeSearchWithPreplacerMoveMaker(10000, TuneableUtilityMoveMaker.Tuning1, p);
return(new PlayerDecisionMaker(m, new PlacementMaker(p)));
},
() => new PlayerDecisionMaker(new AlphaBetaMoveMaker(15, TuneableByBoardPositionUtilityCalculator.Tuning1), PlacementMaker.ExhaustiveMostFuturePlacementsInstance1_6),
() => new PlayerDecisionMaker(new AlphaBetaMoveMaker(15, TuneableByBoardPositionUtilityCalculator.Tuning1), new PlacementMaker(new BestEvaluatorStrategy(TuneablePattern2x2BoardEvaluator.Tuning1))),
//
//() =>
//{
// var p = new PreplacerStrategy(new EvaluatorTreeSearchPreplacer(new Pattern2x2BoardEvaluator(), 4, 4, true));
// var m = new MoveOnlyMinimaxWithAlphaBetaPruningWithPreplacerMoveMaker(13, TuneableByBoardPositionUtilityCalculator.Tuning1, p);
// return new PlayerDecisionMaker(m, new PlacementMaker(p));
//},
() =>
{
var p = new PreplacerStrategy(new EvaluatorTreeSearchPreplacer(TuneablePattern2x2BoardEvaluator.Tuning1, 4, 4, true));
var m = new MoveOnlyAlphaBetaWithPreplacerMoveMaker(15, TuneableByBoardPositionUtilityCalculator.Tuning1, p);
return(new PlayerDecisionMaker(m, new PlacementMaker(p)));
},
};
const int TotalRuns = 500;
const bool enableConsoleLogging = false;
//TODO: Play each AI against each other AI 100 times and print a table of results
var totalWins = new int[aiToTest.Length, aiToTest.Length];
var totalTimeTaken = new long[aiToTest.Length];
Console.WriteLine($"Running {aiToTest.Length * (aiToTest.Length - 1) / 2} * {TotalRuns} Games");
int gameNumber = 0;
for (var a = 0; a < aiToTest.Length; a++)
{
for (var b = a; b < aiToTest.Length; b++)
{
if (a == b)
{
continue;
}
long aiATime = 0;
long aiBTime = 0;
var aiA = aiToTest[a];
var aiB = aiToTest[b];
Console.WriteLine($"{++gameNumber} {aiA().Name} vs {aiB().Name}");
Parallel.For(0, TotalRuns, new ParallelOptions {
MaxDegreeOfParallelism = 6
}, (run) =>
//for (var run = 0; run < TotalRuns; run++)
{
var state = new SimulationState(SimulationHelpers.GetRandomPieces(run / 2), 0);
ConsoleLogger logger = null;
if (enableConsoleLogging)
{
state.Logger = logger = new ConsoleLogger(state);
}
//state.Fidelity = SimulationFidelity.NoPiecePlacing;
//Let each Ai have half of the goes first and half second
var runner = new SimulationRunner(state, run % 2 == 0 ? aiA() : aiB(), run % 2 == 1 ? aiA() : aiB());
while (!state.GameHasEnded)
{
runner.PerformNextStep();
if (logger != null)
{
logger.PrintBoards(true);
}
}
var aWin = run % 2 == state.WinningPlayer;
lock (totalWins)
{
if (aWin)
{
totalWins[a, b]++;
}
else
{
totalWins[b, a]++;
}
}
Interlocked.Add(ref aiATime, runner.Stopwatches[run % 2].ElapsedMilliseconds);
Interlocked.Add(ref aiBTime, runner.Stopwatches[(run + 1) % 2].ElapsedMilliseconds);
//Console.WriteLine(aWin);
}
);
Console.WriteLine(totalWins[a, b]);
totalTimeTaken[a] += aiATime;
totalTimeTaken[b] += aiBTime;
}
}
//Calculate the total points for each
var total = Enumerable.Range(0, aiToTest.Length).Select(ai => Enumerable.Range(0, aiToTest.Length).Sum(opponent => totalWins[ai, opponent])).ToArray();
//Dump a CSV with the results
var filename = "result_" + DateTimeOffset.Now.Ticks + ".csv";
var res = new List <string>();
res.Add("," + string.Join(", ", aiToTest.Select(ai => ai().Name)) + ",Win%,Rank,Total Time");
for (var a = 0; a < aiToTest.Length; a++)
{
var line = aiToTest[a]().Name;
for (var b = 0; b < aiToTest.Length; b++)
{
if (a == b)
{
line += ",";
}
else
{
line += "," + totalWins[a, b];
}
}
//Win%, rank, time
line += "," + (total[a] / (float)(aiToTest.Length - 1) * 100 / TotalRuns).ToString("0.0");
line += "," + (aiToTest.Length - total.Count(c => c < total[a]));
line += "," + totalTimeTaken[a];
res.Add(line);
}
Console.WriteLine("Saving results as " + filename);
File.WriteAllLines(filename, res);
Process.Start(filename);
}
