public Features(IMultHeuristic multHeuristic, Func <double, double> responseFunc, Func <double, double> responseFuncInv)
{
if (Global.DOMAINTYPE != typeof(SlidingPuzzle))
{
throw new Exception();
}
this.numInputs = multHeuristic.HArr.Length + 1;
this.multHeuristic = multHeuristic;
this.responseFunc = responseFunc;
this.responseFuncInv = responseFuncInv;
}
public Features(IMultHeuristic multHeuristic, Func <double, double> responseFunc, Func <double, double> responseFuncInv)
{
if (Global.DOMAINTYPE != typeof(PancakePuzzle))
{
throw new Exception();
}
this.numInputs = multHeuristic.HArr.Length + 2;
this.multHeuristic = multHeuristic;
this.responseFunc = responseFunc;
this.responseFuncInv = responseFuncInv;
this.middleTokenIndex = Global.SIZE / 2;
}
static void Main(string[] args)
{
Control.UseNativeMKL();
Console.WriteLine("start1");
//PancakePuzzle.BuildPDBs.BuildPDBs24();
//GenTest(null, 50,Global.MAXSTEPS);
multHeuristic = null;
representationSolve = new SlidingPuzzle.Representations.TwoDim(new Func <double, double>(x => x / 10), new Func <double, double>(x => x * 10));
representationUncert = new SlidingPuzzle.Representations.TwoDim(null, null);
for (int r = 1; r <= 5; r++)
{
{
List <Tuple <int, bool, int> > paramaters = new List <Tuple <int, bool, int> >();
paramaters.Add(new Tuple <int, bool, int>(1, true, 1));
foreach (var p in paramaters)
{
Train(r, Global.NITER, p.Item1, p.Item2, p.Item3, false);
}
}
{
int nnIndex = Global.NITER - 1;
List <Tuple <string, int, double?> > paramaters = new List <Tuple <string, int, double?> >();
paramaters.Add(new Tuple <string, int, double?>("1", nnIndex, null));
foreach (var p in paramaters)
{
TestAdmissibility(r, p.Item1, p.Item2, p.Item3);
}
}
{
List <Tuple <int, bool, int> > paramaters = new List <Tuple <int, bool, int> >();
paramaters.Add(new Tuple <int, bool, int>(2, true, 1));
foreach (var p in paramaters)
{
Train(r, Global.NITER, p.Item1, p.Item2, p.Item3, false);
}
}
{
int nnIndex = Global.NITER - 1;
List <Tuple <string, int, double?> > paramaters = new List <Tuple <string, int, double?> >();
paramaters.Add(new Tuple <string, int, double?>("2", nnIndex, 0.5));
paramaters.Add(new Tuple <string, int, double?>("2", nnIndex, 0.95));
paramaters.Add(new Tuple <string, int, double?>("2", nnIndex, 0.9));
paramaters.Add(new Tuple <string, int, double?>("2", nnIndex, 0.75));
paramaters.Add(new Tuple <string, int, double?>("2", nnIndex, 0.25));
paramaters.Add(new Tuple <string, int, double?>("2", nnIndex, 0.1));
paramaters.Add(new Tuple <string, int, double?>("2", nnIndex, 0.05));
foreach (var p in paramaters)
{
TestAdmissibility(r, p.Item1, p.Item2, p.Item3);
}
}
{
List <Tuple <int, bool, int> > paramaters = new List <Tuple <int, bool, int> >();
paramaters.Add(new Tuple <int, bool, int>(1, true, 1));
paramaters.Add(new Tuple <int, bool, int>(1, false, 1));
paramaters.Add(new Tuple <int, bool, int>(1, false, 2));
paramaters.Add(new Tuple <int, bool, int>(1, false, 4));
paramaters.Add(new Tuple <int, bool, int>(1, false, 6));
paramaters.Add(new Tuple <int, bool, int>(1, false, 8));
paramaters.Add(new Tuple <int, bool, int>(1, false, 10));
foreach (var p in paramaters)
{
Train(r, Global.NITER, p.Item1, p.Item2, p.Item3, true);
}
}
{
int numTasks = 1000;
int numIter = 5;
int nnIndex = Global.NITER - 1;
TestDomainData[][] testData = new TestDomainData[numIter][];
for (int i = 0; i < numIter; i++)
{
TestDomainData[] data = new TestDomainData[numTasks];
for (int j = 0; j < numTasks; j++)
{
data[j] = GenTest(null, 1, j + 1, false, false)[0];
}
testData[i] = data;
}
List <Tuple <string, int> > paramaters = new List <Tuple <string, int> >();
paramaters.Add(new Tuple <string, int>("1e", nnIndex));
paramaters.Add(new Tuple <string, int>("k1", nnIndex));
paramaters.Add(new Tuple <string, int>("k2", nnIndex));
paramaters.Add(new Tuple <string, int>("k4", nnIndex));
paramaters.Add(new Tuple <string, int>("k6", nnIndex));
paramaters.Add(new Tuple <string, int>("k8", nnIndex));
paramaters.Add(new Tuple <string, int>("k10", nnIndex));
foreach (var p in paramaters)
{
TestEfficiency(r, p.Item1, p.Item2, testData);
}
}
}
Console.ReadLine();
}
public MaxHeuristic(IMultHeuristic multHeuristic)
{
this.multHeuristic = multHeuristic;
}
