Changeset 461

Timestamp:

02/03/16 23:10:26 (8 years ago)

Author:

Maciej Komosinski

Message:

• Fixed an external variable (MAX_WITHOUT_PENALTY) accessed invalidly inside a function
• Moved some code to a separate UserScripts?.script_Find_best_genotype_on_average_args(...)

File:

• experiments/frams/evolve-speed-vs-gravity/data/scripts/evolve-speed-vs-gravity.script (modified) (3 diffs)

experiments/frams/evolve-speed-vs-gravity/data/scripts/evolve-speed-vs-gravity.script

@@ -3 +3 @@
 help:Evolve for speed in different gravity settings
 code:~
-function main(gravity,min_evaluations)
+function main_args(gravity,min_evaluations)
 {
         Math.randomize();
@@ -12 +12 @@
         //custom fitness function: velocity minus small penalty for complexity (high number of parts, joints, neurons, connections)
         GenePools[0].fitness="""
- var MAX_WITHOUT_PENALTY=50;
  function penalty(count)
  {
- var toomany=count-MAX_WITHOUT_PENALTY;
- if (toomany<=0) return 0; else return -toomany*0.001;
+  var MAX_WITHOUT_PENALTY=50;
+  var toomany=count-MAX_WITHOUT_PENALTY;
+  if (toomany<=0) return 0; else return -toomany*0.001;
  }
  return this.velocity+penalty(this.numparts)+penalty(this.numjoints)+penalty(this.numneurons)+penalty(this.numconnections);""";
@@ -24 +24 @@
                 
         Simulator.start();
-        while (Simulator.running) Simulator.step(); //runs until the experiment stops by itself
+        while (Simulator.running) Simulator.step(); //runs until the experiment stops by itself (due to stagnation detected)
+        
         var best=GenePools[0].best();
-        Simulator.print("%g (x%g) %s" % best.fit % best.popsiz % best.genotype);
+        Simulator.print("Optimization ends, best: %g (x%g) %s" % best.fit % best.instances % best.genotype);
         
         // Now, since we have indeterminism (default.sim used: random initialization of neural states and random placement of creatures),
         // we cannot trust fitness values that have not been confirmed (averaged) during multiple evaluations.
-        // So we start another phase where we wait until the best genotype is evaluated at least min_evaluations times.
+        // So we start another phase where we wait until the single best genotype is evaluated at least min_evaluations times.
         // No new genotypes are introduced in this phase.
-        ExpParams.stagnation=0; //turn off stagnation detection mechanism
-        ExpParams.p_mut=0; //we don't want evolution and new genotypes anymore. We only want to evaluate existing genotypes multiple times
-        ExpParams.p_xov=0;
-        Simulator.start();
-        while (Simulator.running && best.popsiz<min_evaluations) //repeat until the best genotype will be evaluated at least min_evaluations times
-        {
-                for(var t=best.lifespan; t>0 && Simulator.running; t--) // simulate 'expected lifespan' steps after which 'best' may have changed. This helps avoid frequent unnecessary calls to best()
-                        Simulator.step();
-                best=GenePools[0].best();
-        }
-        Simulator.stop();
-        Simulator.print("%g (x%g) %s" % best.fit % best.popsiz % best.genotype);
-        
-        GenePools[0].clear(); //remove all...
-        best.moveTo(GenePools[0]); //...then restore best...
-        Simulator.save("best_%g_%u.expt" % gravity % (0+Math.time)); //...and save it in a file just in case we want to see all of its data
+        UserScripts.script_Find_best_genotype_on_average_args(min_evaluations,"best_%g_%u.expt" % gravity % (0+Math.time));
 }
 ~
-