Posts tagged with “programming”

several runs w/one target to the right December 3

run length:16
	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14
avg	0.02374035	0.02294719	0.02484045	0.02716788	0.0368175	0.07682224	0.1613337	0.2491582	0.3231104	0.3367688	0.2491151	0.2830267	0.3835227	0.3890342	0.3153373
max	0.06769724	0.03925342	0.04498602	0.1263496	0.404237	0.374389	0.3555773	0.3137961	0.3735667	0.3548343	0.3651761	0.3021848	0.4051638	0.4051638	0.4040922

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
	0	1	2	3	4	5	6	7
avg	0.03060137	0.02995493	0.04024728	0.0575745	0.09549089	0.1528904	0.2382598	0.3359577
max	0.3210693	0.0931176	0.3405152	0.3987312	0.3156744	0.3577993	0.4041474	0.4036549


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
	0	1	2	3	4	5	6	7	8	9	10	11
avg	0.03017294	0.03939533	0.0713759	0.1155957	0.1643836	0.1652581	0.175373	0.1823241	0.2087838	0.2699307	0.2607325	0.2376547
max	0.2459623	0.2510435	0.3383353	0.3878251	0.4020672	0.3107825	0.3692091	0.3240498	0.3978929	0.3996228	0.3820494	0.3360826


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
	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
avg	0.02890839	0.05155375	0.1359876	0.1448909	0.1736577	0.2003668	0.2262791	0.2080024	0.2438067	0.2197463	0.3405291	0.3046682	0.2368358	0.2379223	0.3182342	0.3583929
max	0.3794718	0.3413424	0.3595681	0.338711	0.2274584	0.2368233	0.3841263	0.2368233	0.2803776	0.2500244	0.3858906	0.3502061	0.2715727	0.2735227	0.3642375	0.3841804


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

test #2 November 21

run length:41
	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39
avg	0.01927173	0.02359534	0.02811977	0.03708193	0.04255582	0.04157518	0.04394267	0.04458875	0.04318643	0.0428228	0.04052364	0.04658583	0.04347268	0.04582917	0.04374065	0.04100496	0.04889515	0.04540672	0.05006592	0.04564475	0.0427879	0.04929592	0.04859376	0.05339097	0.0507197	0.04825098	0.0510525	0.05413477	0.05213727	0.05151764	0.04749117	0.04965009	0.05784012	0.05404992	0.05237118	0.0525284	0.04783949	0.05376031	0.04847497	0.04896856
max	0.07964461	0.08627302	0.05624481	0.05402947	0.08477216	0.08375464	0.07554159	0.05623543	0.056537	0.05158523	0.05063492	0.06058157	0.05097674	0.08965258	0.06569902	0.08290169	0.08512975	0.08331195	0.05962069	0.05511965	0.05520427	0.05549694	0.06359167	0.06454556	0.05882515	0.08750984	0.08758585	0.08901581	0.08712924	0.08604776	0.08736121	0.08734716	0.08858384	0.08958311	0.08687814	0.0894415	0.08734188	0.08857764	0.0873366	0.07351736

testing... November 12

run length:20
	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
avg	2.411733	2.758116	3.25697	3.483885	3.342978	3.401604	3.541905	3.582529	3.657223	3.531241	3.554353	3.705153	3.652175	3.666475	3.813221	3.806489	3.901693	3.742233	3.697415	3.964206
max	5.011492	4.036042	4.152324	4.133807	4.150167	4.126954	4.097853	4.108099	4.233071	4.10865	4.03889	4.040823	4.020371	4.043088	4.125445	4.098948	4.067454	4.036376	4.124011	5.39157

UnityEngine.Debug:Log(Object)
Chart:chart(Array) (at Assets/Scripts/Brain/Chart.js:18)
Chart:exportChart(Array) (at Assets/Scripts/Brain/Chart.js:5)
TrainingController:InputHandler() (at Assets/Scripts/Brain/TrainingController.js:185)
TrainingController:Update() (at Assets/Scripts/Brain/TrainingController.js:74)

I'm a geek: hello, world in lua in ruby January 5

> require "rubygems"
> require "rufus/lua"
> s = Rufus::Lua::State.new
> s.eval("print('Hello LUA')")
Hello LUA
 => nil

ruby GP performance pt.2 December 19

And with ruby 1.9.2p0

sammael:rubyGP greay$ time ruby tinyGP.rb 

real    0m12.546s
user    0m11.819s
sys 0m0.631s

MacRuby definitely seems to be the winner here...