test #2

run length:20 generations
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
max 0.8278201 0.8749934 0.9777876 0.9670284 0.9136718 3.220692 2.815182 3.268469 3.22443 3.580076 2.969378 3.61642 2.962922 3.085169 3.068109 2.74214 3.512394 3.55677 3.107811 4.185637
max 3.511007 2.91327 2.252049 3.536019 3.134709 3.385681 3.419258 3.317267 2.612051 3.417869 2.431517 2.490661 3.31127 3.349222 2.620521 3.16761 3.452976 3.60968 2.82757 2.784959
max 1.242083 3.399157 3.527213 3.372939 3.596447 4.466602 2.668887 3.741586 4.324578 1.690305 2.121684 2.683657 3.903839 2.916723 3.928953 3.662849 3.936197 4.04638 3.557748 3.32352
max 3.666266 3.650939 3.946907 3.256672 4.348071 1.420043 2.664589 3.123181 3.019968 4.838627 3.972589 3.741165 3.240901 3.513802 4.036836 3.893865 3.271496 4.03652 3.201042 4.325753
max 3.433275 3.409322 3.327416 3.645406 3.696878 3.680146 4.663756 3.338467 2.957809 3.947436 3.602751 4.132272 3.228299 4.070083 4.579495 2.098974 4.396971 4.540826 4.561467 3.527181
Population Size
100
Run Length
15
Do Training
False
Do Hybrid Training
True
Do Competitive Run
False
Do Adaptive Training
True
Inputs
hasTarget,targetLeft,targetRight,targetNorth,targetSouth,dirToTarget,distToTarget,wall,sensor0,sensor1,sensor2
Outputs
left,right,up,down,run,sensordir0,sensordir1,sensordir2
Hidden Layers
8 12 12 12 8
Back Propogation
True
Learning rate
0.5
Momentum
0.1
Growth rate
0.5