Posts tagged with “programming”

overhead run #4

and a run w/another hidden layer
run length:33
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avg0.11048140.1368160.19085030.32848490.66843531.2827341.3022611.2063011.3588411.1262561.3977361.2466041.3233510.89090271.1224781.1082331.6312261.2917641.2202251.215471.2995221.2957941.3604451.0066651.0052651.2855061.7236880.98484360.94554330.93132651.1489891.272345
max0.28713411.2145761.0672691.1039581.3546961.4754171.3662021.2345411.3906231.1732981.4265181.7649771.3961520.91080251.1449391.1335091.905031.3205141.2461031.2393811.4987611.3394911.463061.1353131.0306481.3285661.7724881.1661320.97462161.0904311.1798141.307164
Population Size
100
Run Length
20
Do Training
False
Do Hybrid Training
True
Do Competitive Run
False
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

Overhead run #3

Revisiting this whole neural net thing. Did another, longer run after tweaking a bunch of things (mostly removing cruft from the side-view test, like jumping and "grounded" and such).
run length:28
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avg0.11118350.11751510.11617130.12565720.13688070.1563310.16561640.20839510.26791690.37956520.49561230.65011810.5612270.7630230.6263450.6848750.91963410.75143650.88850591.0652710.96150930.8098810.7446751.0010240.8382290.89157540.8473446
max0.24504590.27551090.22391210.42355140.48726720.48368050.91547671.0488010.80019580.85897091.1265221.1067790.94524681.0103830.79434391.0487691.185260.94576761.1496091.2348391.2027670.98070281.0266311.0796510.87430930.93146660.9513353
Population Size
100
Run Length
20
Do Training
False
Do Hybrid Training
True
Do Competitive Run
False
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 8
Back Propogation
True
Learning rate
0.5
Momentum
0.1
Growth rate
0.5

Overhead run #1

run length:21
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avg0.13202310.13210560.14047360.13925690.1437630.15051850.15502730.15820350.15826860.15943360.1748240.19810150.18125470.18265510.19213080.20931670.21108390.21980890.19083510.2198777
max0.37585550.33449690.33492360.33683450.3164830.31835540.3149510.32411090.30053030.35697240.36063690.34416720.34026580.36688360.45493260.57286720.51493490.45049550.38249250.4372288
Population Size
100
Run Length
20
Do Training
False
Do Hybrid Training
True
Do Competitive Run
False
Inputs
hasTarget,targetLeft,targetRight,targetNorth,targetSouth,dirToTarget,distToTarget,grounded,wall,ladder,sensor0,sensor1,sensor2
Outputs
left,right,up,down,run,jump,sensordir0,sensordir1,sensordir2
Hidden Layers
8 12 12 8
Back Propogation
True
Learning rate
0.5
Momentum
0.1
Growth rate
0.5

combine 1&2 (another)

run length:18
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avg0.046179480.055051140.057261590.11134380.36669770.66336660.90150560.95562291.0769611.0430331.1341550.83810421.142270.91605030.72957931.1060271.074763
max0.36390810.44029130.60784241.0974671.1718661.1725331.1320851.066311.1584161.1667491.1623521.1552281.1749371.1469381.1496021.165071.174278
Population Size
100
Run Length
30
Do Training
False
Do Hybrid Training
True
Do Competitive Run
False
Inputs
hasTarget,targetLeft,targetRight,dirToTarget,distToTarget,grounded,wall,ladder,sensor0,sensor1,sensor2
Outputs
left,right,up,down,run,jump,sensordir0,sensordir1,sensordir2
Hidden Layers
8 12 12 8
Back Propogation
True

several runs w/one target to the right

run length:16
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avg0.023740350.022947190.024840450.027167880.03681750.076822240.16133370.24915820.32311040.33676880.24911510.28302670.38352270.38903420.3153373
max0.067697240.039253420.044986020.12634960.4042370.3743890.35557730.31379610.37356670.35483430.36517610.30218480.40516380.40516380.4040922
Population Size:100
Run Length:30
Do Training:False
Do Hybrid Training:True
Do Competitive Run:False
Inputs:hasTarget,targetLeft,targetRight,dirToTarget,distToTarget,grounded,wall,ladder,sensor0,sensor1,sensor2
Outputs:left,right,up,down,run,jump,sensordir0,sensordir1,sensordir2
Hidden Layers:8 12 12 8 
Back Propogation:True
run length:9
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avg0.030601370.029954930.040247280.05757450.095490890.15289040.23825980.3359577
max0.32106930.09311760.34051520.39873120.31567440.35779930.40414740.4036549

Population Size:100
Run Length:30
Do Training:False
Do Hybrid Training:True
Do Competitive Run:False
Inputs:hasTarget,targetLeft,targetRight,dirToTarget,distToTarget,grounded,wall,ladder,sensor0,sensor1,sensor2
Outputs:left,right,up,down,run,jump,sensordir0,sensordir1,sensordir2
Hidden Layers:8 12 12 8 
Back Propogation:True
run length:13
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avg0.030172940.039395330.07137590.11559570.16438360.16525810.1753730.18232410.20878380.26993070.26073250.2376547
max0.24596230.25104350.33833530.38782510.40206720.31078250.36920910.32404980.39789290.39962280.38204940.3360826

Population Size:100
Run Length:30
Do Training:False
Do Hybrid Training:True
Do Competitive Run:False
Inputs:hasTarget,targetLeft,targetRight,dirToTarget,distToTarget,grounded,wall,ladder,sensor0,sensor1,sensor2
Outputs:left,right,up,down,run,jump,sensordir0,sensordir1,sensordir2
Hidden Layers:8 12 12 8 
Back Propogation:True
run length:17
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avg0.028908390.051553750.13598760.14489090.17365770.20036680.22627910.20800240.24380670.21974630.34052910.30466820.23683580.23792230.31823420.3583929
max0.37947180.34134240.35956810.3387110.22745840.23682330.38412630.23682330.28037760.25002440.38589060.35020610.27157270.27352270.36423750.3841804

Population Size:100
Run Length:30
Do Training:False
Do Hybrid Training:True
Do Competitive Run:False
Inputs:hasTarget,targetLeft,targetRight,dirToTarget,distToTarget,grounded,wall,ladder,sensor0,sensor1,sensor2
Outputs:left,right,up,down,run,jump,sensordir0,sensordir1,sensordir2
Hidden Layers:8 12 12 8 
Back Propogation:True