Changeset 11972 for branches/HeuristicLab.Problems.GrammaticalOptimization/Main/Program.cs

Timestamp:

02/09/15 09:48:30 (10 years ago)

Author:

gkronber

Message:

#2283 new experiments

File:

• branches/HeuristicLab.Problems.GrammaticalOptimization/Main/Program.cs (modified) (6 diffs)

branches/HeuristicLab.Problems.GrammaticalOptimization/Main/Program.cs

@@ -27 +27 @@
 
       //RunDemo();
-      // RunGpDemo();
-      RunGridTest();
-      //RunGpGridTest();
+      //RunGpDemo();
+      //RunGridTest();
+      RunGpGridTest();
     }
 
@@ -229 +229 @@
       // - ant: UCB1Tuned with canonical states also works very well for the artificial ant! constistent solutions in less than 10k iters      
 
-      var problem = new SymbolicRegressionPoly10Problem();
+      //var problem = new SymbolicRegressionPoly10Problem();
       //var problem = new SantaFeAntProblem();
-      //var problem = new SymbolicRegressionProblem(random, "Tower"); 
+      var problem = new SymbolicRegressionProblem(random, "Breiman");
       //var problem = new PalindromeProblem();
       //var problem = new HardPalindromeProblem();
@@ -244 +244 @@
       //var alg = new SequentialSearch(problem, 23, random, 0,
       //  new HeuristicLab.Algorithms.Bandits.GrammarPolicies.GenericContextualGrammarPolicy(problem, new GenericThompsonSamplingPolicy(new GaussianModel(0.5, 10, 1, 1)), true));
-      var alg = new SequentialSearch(problem, 23, random, 0,
+      var alg = new SequentialSearch(problem, 30, random, 0,
         new HeuristicLab.Algorithms.Bandits.GrammarPolicies.GenericFunctionApproximationGrammarPolicy(problem, true));
       //var alg = new MctsQLearningSampler(problem, sentenceLen, random, 0, null);
@@ -265 +265 @@
         globalStatistics.AddSentence(sentence, quality);
 
-        if (iterations % 1000 == 0) {
-          if (iterations % 10000 == 0) Console.Clear();
-          Console.SetCursorPosition(0, 0);
-          alg.PrintStats();
+        //if (iterations % 100 == 0) {
+        //  if (iterations % 10000 == 0) Console.Clear();
+        //  Console.SetCursorPosition(0, 0);
+        //  alg.PrintStats();
+        //}
+
+        //Console.WriteLine(sentence);
+
+        if (iterations % 100 == 0) {
+          Console.WriteLine("{0}", globalStatistics);
         }
-
-        //Console.WriteLine(sentence);
-
-        //if (iterations % 10000 == 0) {
-        //  Console.WriteLine("{0}", globalStatistics);
-        //}
       };
 
@@ -309 +309 @@
       const int nReps = 20;
       const int seed = 31415;
-      const int maxIters = 200000;
+      //const int maxIters = 50000;
       var rand = new Random(seed);
-      var problemFactories = new Func<ISymbolicExpressionTreeProblem>[]
+      var problemFactories = new Func<Tuple<int, int, ISymbolicExpressionTreeProblem>>[]
       {
-        () => new SymbolicRegressionPoly10Problem(), 
-        () => new SantaFeAntProblem(), 
-      };
-      foreach (var popSize in new int[] { 50, 100, 250, 500, 1000, 2500, 5000, 10000 }) {
+        () => Tuple.Create(50000, 32, (ISymbolicExpressionTreeProblem)new PermutationProblem()), 
+        () => Tuple.Create(50000, 32, (ISymbolicExpressionTreeProblem)new RoyalPairProblem()), 
+        () => Tuple.Create(50000, 32,(ISymbolicExpressionTreeProblem)new RoyalSymbolProblem()), 
+        () => Tuple.Create(50000, 64, (ISymbolicExpressionTreeProblem)new RoyalPairProblem()), 
+        () => Tuple.Create(50000, 64,(ISymbolicExpressionTreeProblem)new RoyalSymbolProblem()), 
+        () => Tuple.Create(50000, 128, (ISymbolicExpressionTreeProblem)new RoyalPairProblem()), 
+        () => Tuple.Create(50000, 128,(ISymbolicExpressionTreeProblem)new RoyalSymbolProblem()), 
+        () => Tuple.Create(50000, 256, (ISymbolicExpressionTreeProblem)new RoyalPairProblem()), 
+        () => Tuple.Create(50000, 256,(ISymbolicExpressionTreeProblem)new RoyalSymbolProblem()), 
+        //() => new RoyalPairProblem(), 
+        //() => new FindPhrasesProblem(rand, 20, 5, 3, 5, 0, 1, 0, true), 
+        //() => new FindPhrasesProblem(rand, 20, 5, 3, 5, 0, 1, 0, false), 
+        //() => new FindPhrasesProblem(rand, 20, 5, 3, 5, 50, 1, 0.8, false), 
+      };
+
+      foreach (var popSize in new int[] { 100 /*, 250, 500, 1000, 2500, 5000, 10000 */ }) {
         foreach (var mutationRate in new double[] { /* 0.05, /* 0.10, */ 0.15, /* 0.25, 0.3 */}) {
-          foreach (var maxSize in new int[] { 30, 50, 100, 150, 250 }) {
-            // skip experiments that are already done
-            if (popSize == 10000 || maxSize == 150 || maxSize == 250) {
-              foreach (var problemFactory in problemFactories)
-                for (int i = 0; i < nReps; i++) {
-                  var solverSeed = rand.Next();
-                  {
-                    var prob = problemFactory();
-                    var sgp = new StandardGP(prob, new Random(solverSeed));
-                    RunGP(sgp, prob, maxIters, popSize, mutationRate, maxSize);
-                  }
-                  // {
-                  //   var prob = problemFactory();
-                  //   var osgp = new OffspringSelectionGP(prob, new Random(solverSeed));
-                  //   RunGP(osgp, prob, maxIters, popSize, mutationRate, maxSize);
-                  // }
-                }
+          // skip experiments that are already done
+          foreach (var problemFactory in problemFactories) {
+            for (int i = 0; i < nReps; i++) {
+              {
+                var solverSeed = rand.Next();
+                var tupel = problemFactory();
+                var maxIters = tupel.Item1;
+                var maxSize = tupel.Item2;
+                var prob = tupel.Item3;
+                var sgp = new StandardGP(prob, new Random(solverSeed));
+                RunGP(sgp, prob, maxIters, popSize, mutationRate, maxSize);
+              }
+              //{
+              //  var prob = problemFactory();
+              //  var osgp = new OffspringSelectionGP(prob, new Random(solverSeed));
+              //  RunGP(osgp, prob, maxIters, popSize, mutationRate, maxSize);
+              //}
             }
           }
         }
+
       }
     }
@@ -350 +363 @@
         globalStatistics.AddSentence(sentence, quality);
 
-        if (iterations % 1000 == 0) {
+        if (iterations % 100 == 0) {
           Console.WriteLine("\"{0,25}\" {1} {2:N2} {3} \"{4,25}\" {5}", gpName, popSize, mutationRate, maxSize, probName, globalStatistics);
         }