static double Evaluate(IAgent model, IAgent benchmark, GridGameParameters _params)
{
double score = 0;
Console.WriteLine("Starting games as player 1..");
for (int i = 0; i < _params.MatchesPerOpponent; i++)
{
var game = _params.GameFunction(model, benchmark);
game.PlayToEnd();
if (game.Winner == 1)
score += _params.WinReward;
else if (game.Winner == 0)
score += _params.TieReward;
else
score += _params.LossReward;
}
Console.WriteLine("Starting games as player 2..");
for (int i = 0; i < _params.MatchesPerOpponent; i++)
{
var game = _params.GameFunction(benchmark, model);
game.PlayToEnd();
if (game.Winner == -1)
score += _params.WinReward;
else if (game.Winner == 0)
score += _params.TieReward;
else
score += _params.LossReward;
}
Console.WriteLine("Done!");
return score;
}
public double Evaluate(int[,] board, GridGameParameters ggp, int player)
{
// ANN should map from board squares to a single value
Debug.Assert(Brain.InputCount == board.Length);
Debug.Assert(Brain.OutputCount == 1);
// Clear the network
Brain.ResetState();
// Console.WriteLine("player: {0}", player);
// Set the board state as the inputs
for (int i = 0; i < board.GetLength(0); i++)
for (int j = 0; j < board.GetLength(1); j++)
{
//Console.WriteLine("[{0},{1}]={2}", pieceX, pieceY, board[pieceX, pieceY].toBoardSensor(player));
Brain.InputSignalArray[i * board.GetLength(0) + j] = board[i, j].toBoardSensor(player);
}
// Activate the network
Brain.Activate();
//Console.WriteLine("{0}: {1}", AgentId, Brain.OutputSignalArray[0]);
// Return the value of the board
return Brain.OutputSignalArray[0] * _params.WinReward;
}
public MctsNeatAgent(int id,
CheckGameOver check,
GetValidNextMoves valid,
IBlackBox brain,
ApplyMove applyMove,
GridGameParameters parameters) : base(id, check, valid, applyMove, parameters)
{
Brain = brain;
}
public BlondieAgent(int id,
MinimaxAgent.CheckGameOver check,
MinimaxAgent.GetValidNextMoves valid,
IBlackBox brain,
MinimaxAgent.ApplyMove apply,
GridGameParameters parameters)
: base(id)
{
Brain = brain;
_params = parameters;
_minimax = new MinimaxAgent(id, check, valid, Evaluate, apply, parameters);
}
public MinimaxAgent(int id,
CheckGameOver check,
GetValidNextMoves valid,
BoardEval eval,
ApplyMove apply,
GridGameParameters parameters) : base(id)
{
Debug.Assert(parameters != null);
_checkGameOver = check;
_validNextMoves = valid;
_boardEval = eval;
_applyMove = apply;
_params = parameters;
}
public MctsAgent(int id,
CheckGameOver check,
GetValidNextMoves valid,
ApplyMove applyMove,
GridGameParameters parameters,
bool benchmarkAgent = false) : base(id)
{
Debug.Assert(parameters != null);
_checkGameOver = check;
_validNextMoves = valid;
_applyMove = applyMove;
_params = parameters;
_random = new Random();
BenchmarkAgent = benchmarkAgent;
mcTrials = benchmarkAgent ? _params.EvaluatorMonteCarloTrials : _params.MonteCarloTrials;
minTrialsPerMove = benchmarkAgent ? _params.EvaluatorMinMcTrialsPerMove : _params.MinMcTrialsPerMove;
uctConst = benchmarkAgent ? _params.EvaluatorUctConst : _params.UctConst;
}
public GridGameExperiment(GridGameParameters parameters)
{
Parameters = parameters;
initialize();
}
public static GridGameParameters DefaultParameters(string name)
{
GridGameParameters gg = new GridGameParameters()
{
Name = name,
Description = "",
Game = "tictactoe",
Inputs = 9,
Outputs = 9,
Evaluator = "random",
WinReward = 2,
TieReward = 1,
LossReward = 0,
Generations = 500,
PopulationSize = 100,
Species = 10,
SocialAgents = false,
LamarckianEvolution = false,
Subcultures = 10,
GenerationsPerMemoryIncrement = 20,
MaxMemorySize = 0,
ExperimentPath = "../../../experiments/tictactoe/random/",
BlondieAgents = false,
MinimaxDepth = 9,
OpponentPath = null,
MatchesPerOpponent = 1,
MonteCarloTrials = 1000,
MinMcTrialsPerMove = 1,
UctConst = 0.5,
HyperNeat = false,
MctsNeat = false,
RoundRobinOpponents = 100
};
gg.ResultsPath = gg.ExperimentPath + gg.Name + "_results.csv";
gg.ConfigPath = gg.ExperimentPath + gg.Name + "_config.xml";
gg.ChampionPath = gg.ExperimentPath + gg.Name + "_gen{0}_champion.xml";
gg.BenchmarkResultsPath = gg.ExperimentPath + gg.Name + "_benchmark.csv";
gg.BenchmarkGameLogPath = gg.ExperimentPath + gg.Name + "_games.txt";
return gg;
}
static void Main(string[] args)
{
_params = GridGameParameters.GetParameters(args);
if (_params == null)
return;
Debug.Assert(_params.AgentPath != null);
Debug.Assert(File.Exists(_params.AgentPath));
using (TextWriter writer = new StreamWriter(_params.ConfigPath))
{
XmlSerializer ser = new XmlSerializer(typeof(GridGameParameters));
ser.Serialize(writer, _params);
}
_experiment = new GridGameExperiment(_params.ConfigPath);
IAgent agent = null;
IAgent benchmark = null;
// Load the agent to benchmark
var modelGenome = _experiment.LoadPopulation(XmlReader.Create(_params.AgentPath))[0];
var brain = _experiment.CreateGenomeDecoder().Decode(modelGenome);
if (_params.MctsNeat)
{
Console.WriteLine("Creating MCTS-NEAT agent");
agent = _params.CreateMctsNeatAgent(1, brain);
}
else
{
Console.WriteLine("Creating MCTS agent");
agent = _params.CreateMctsAgent(1, false);
}
// Create the benchmark MCTS agent
if (_params.Evaluator == "mcts")
{
Console.WriteLine("Creating MCTS benchmark agent");
benchmark = _params.CreateMctsAgent(-1, true);
}
else
{
Console.WriteLine("Creating Random benchmark agent");
benchmark = new RandomAgent(-1);
}
Outcome[] outcomes = new Outcome[_params.MatchesPerOpponent * 2];
Console.WriteLine("Starting games as player 1..");
using (_moveLog = new StreamWriter(_params.BenchmarkGameLogPath))
{
for (int i = 0; i < _params.MatchesPerOpponent; i++)
{
Console.Write(i + "...");
if (i > 0 && i % 10 == 0)
Console.WriteLine();
outcomes[i] = RunTrial(agent, benchmark, 1);
}
Console.WriteLine();
Console.WriteLine("Starting games as player 2..");
for (int i = 0; i < _params.MatchesPerOpponent; i++)
{
Console.Write(i + "...");
if (i > 0 && i % 10 == 0)
Console.WriteLine();
outcomes[i + _params.MatchesPerOpponent] = RunTrial(benchmark, agent, -1);
}
Console.WriteLine();
Console.WriteLine("Saving log file...");
}
using (TextWriter writer = new StreamWriter(_params.BenchmarkResultsPath))
{
// games
// wins, ties, losses
// win %, tie %, loss %
// p1 wins, p1 ties, p1 losses,
// p1 win %, p1 tie %, p1 loss %,
// p2 wins, p2 ties, p2 losses,
// p2 win %, p2 tie %, p2 loss %,
// time per move, turns per game
writer.WriteLine("games,wins,win%,ties,tie%,losses,loss%,p1 wins,p1 win%,p1 ties,p1 tie%,p1 losses,p1 loss%,p2 wins,p2 win%,p2 ties,p2 tie%,p2 losses,p2 loss%,avg time per move, avg total moves per game");
writer.WriteLine(
outcomes.Length + "," + // games
outcomes.Count(o => o.Winner == o.AgentId) + "," + // wins
Pct(outcomes.Count(o => o.Winner == o.AgentId), outcomes.Length) + "," + // win %
outcomes.Count(o => o.Winner == 0) + "," + // ties
Pct(outcomes.Count(o => o.Winner == 0), outcomes.Length) + "," + // tie %
outcomes.Count(o => o.Winner == o.BenchmarkId) + "," + // losses
Pct(outcomes.Count(o => o.Winner == o.BenchmarkId), outcomes.Length) + "," + // loss %
outcomes.Count(o => o.Winner == o.AgentId && o.AgentId == 1) + "," + // p1 wins
Pct(outcomes.Count(o => o.Winner == o.AgentId && o.AgentId == 1), outcomes.Count(o => o.AgentId == 1)) + "," + // p1 win %
outcomes.Count(o => o.Winner == 0 && o.AgentId == 1) + "," + // p1 ties
Pct(outcomes.Count(o => o.Winner == 0 && o.AgentId == 1), outcomes.Count(o => o.AgentId == 1)) + "," + // p1 tie %
outcomes.Count(o => o.Winner == o.BenchmarkId && o.AgentId == 1) + "," + // p1 losses
Pct(outcomes.Count(o => o.Winner == o.BenchmarkId && o.AgentId == 1), outcomes.Count(o => o.AgentId == 1)) + "," + // p1 loss %
outcomes.Count(o => o.Winner == o.AgentId && o.AgentId == -1) + "," + // p2 wins
Pct(outcomes.Count(o => o.Winner == o.AgentId && o.AgentId == -1), outcomes.Count(o => o.AgentId == -1)) + "," + // p2 win %
outcomes.Count(o => o.Winner == 0 && o.AgentId == -1) + "," + // p2 ties
Pct(outcomes.Count(o => o.Winner == 0 && o.AgentId == -1), outcomes.Count(o => o.AgentId == -1)) + "," + // p2 tie %
outcomes.Count(o => o.Winner == o.BenchmarkId && o.AgentId == -1) + "," + // p2 losses
Pct(outcomes.Count(o => o.Winner == o.BenchmarkId && o.AgentId == -1), outcomes.Count(o => o.AgentId == -1)) + "," + // p2 loss %
string.Format("{0:N2},", outcomes.Average(o => o.AverageTurnTime)) +
string.Format("{0:N2}", outcomes.Average(o => o.TotalMoves))
);
}
Console.WriteLine("Done!");
}