static void Main(string[] args)
{
GridGameParameters gg = GridGameParameters.GetParameters(args);
if (gg == null)
return;
experiment = new GridGameExperiment(gg.ConfigPath);
experiment.Evaluator = new CondorEvaluator(gg, CondorGroup.Grad);
ea = experiment.CreateEvolutionAlgorithm();
ea.UpdateScheme = new SharpNeat.Core.UpdateScheme(1);
ea.UpdateEvent += new EventHandler(ea_UpdateEvent);
using (TextWriter writer = new StreamWriter(gg.ResultsPath))
writer.WriteLine("Generation,Best,Average");
ea.StartContinue();
while (!finished) Thread.Sleep(1000);
}
static void Main(string[] args)
{
GridGameParameters gg = GridGameParameters.GetParameters(args);
if (gg == null)
return;
using (TextWriter writer = new StreamWriter(gg.ConfigPath))
{
XmlSerializer ser = new XmlSerializer(typeof(GridGameParameters));
ser.Serialize(writer, gg);
}
experiment = new GridGameExperiment(gg.ConfigPath);
ea = experiment.CreateEvolutionAlgorithm();
ea.UpdateScheme = new SharpNeat.Core.UpdateScheme(1);
ea.UpdateEvent += new EventHandler(ea_UpdateEvent);
using (TextWriter writer = new StreamWriter(gg.ResultsPath))
writer.WriteLine("Generation,Best,Average");
ea.StartContinue();
while (!finished) Thread.Sleep(1000);
}
static void Main(string[] args)
{
if (args.Length != 5)
{
Console.WriteLine("Usage: CondorEvaluator.exe <model_id> <model_file> <results_file> <finished_flag> <config_file>");
return;
}
int curArg = 0;
int modelId = int.Parse(args[++curArg]);
string modelFile = args[++curArg];
string resultsFile = args[++curArg];
string finishedFlag = args[++curArg];
string configFile = args[++curArg];
GridGameExperiment experiment = new GridGameExperiment(configFile);
IAgent model = experiment.CreateTargetAgent();
IAgent benchmark = experiment.CreateEvalAgent();
using (TextWriter tw = new StreamWriter(resultsFile))
{
// Evaluate
if (model == null)
{ // Non-viable genome.
tw.WriteLine("0.0 0.0");
}
else
{
double score = Evaluate(model, benchmark, experiment.Parameters);
tw.WriteLine(score + " " + score);
}
}
File.Create(finishedFlag);
}
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!");
}