Jesús Muñoz
Joined: 13 Jul 2011
Posts: 691
Location: Madrid, Spain.
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 Post subject: Perft(14) estimate after averaging 120 MC perft samples. Posted: Fri Feb 17, 2012 8:00 pm |
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Hello:
As I promised some weeks ago, I resumed this experiment in mid February; I have ran other 24 MonteCarlo samples:
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perftmc 14 (GNU 5.07.173b w32):
97) m=6.189968e+019 sd=9.968961e+015 ci(99%)=[6.187400e+019,6.192536e+019] n=501276978 sdn=2.231972e+020 t=1817.47s
98) m=6.187422e+019 sd=1.047597e+016 ci(99%)=[6.184724e+019,6.190121e+019] n=501280763 sdn=2.345497e+020 t=1805.58s
99) m=6.187648e+019 sd=1.095249e+016 ci(99%)=[6.184826e+019,6.190469e+019] n=501280884 sdn=2.452187e+020 t=1807.66s
100) m=6.188386e+019 sd=1.081047e+016 ci(99%)=[6.185602e+019,6.191171e+019] n=501278574 sdn=2.420383e+020 t=1804.91s
101) m=6.188416e+019 sd=1.081914e+016 ci(99%)=[6.185629e+019,6.191203e+019] n=501278937 sdn=2.422324e+020 t=1805.38s
102) m=6.188435e+019 sd=1.033910e+016 ci(99%)=[6.185771e+019,6.191098e+019] n=501279884 sdn=2.314851e+020 t=1805.92s
103) m=6.188559e+019 sd=1.117139e+016 ci(99%)=[6.185682e+019,6.191437e+019] n=501279281 sdn=2.501193e+020 t=1808.84s
104) m=6.189134e+019 sd=1.133385e+016 ci(99%)=[6.186215e+019,6.192054e+019] n=501279579 sdn=2.537567e+020 t=1815.66s
105) m=6.187967e+019 sd=1.013839e+016 ci(99%)=[6.185356e+019,6.190579e+019] n=501278569 sdn=2.269909e+020 t=1804.41s
106) m=6.187396e+019 sd=9.922992e+015 ci(99%)=[6.184839e+019,6.189952e+019] n=501279194 sdn=2.221685e+020 t=1818.95s
107) m=6.187536e+019 sd=1.101518e+016 ci(99%)=[6.184699e+019,6.190374e+019] n=501279098 sdn=2.466218e+020 t=1804.69s
108) m=6.187363e+019 sd=1.109060e+016 ci(99%)=[6.184506e+019,6.190220e+019] n=501280477 sdn=2.483108e+020 t=1806.41s
109) m=6.186728e+019 sd=1.111241e+016 ci(99%)=[6.183865e+019,6.189590e+019] n=501280536 sdn=2.487991e+020 t=1808.86s
110) m=6.187670e+019 sd=1.072955e+016 ci(99%)=[6.184907e+019,6.190434e+019] n=501278981 sdn=2.402266e+020 t=1811.28s
111) m=6.186937e+019 sd=1.113884e+016 ci(99%)=[6.184068e+019,6.189806e+019] n=501278139 sdn=2.493902e+020 t=1808.75s
112) m=6.188844e+019 sd=1.005461e+016 ci(99%)=[6.186254e+019,6.191434e+019] n=501276761 sdn=2.251148e+020 t=1837.12s
113) m=6.189127e+019 sd=1.050394e+016 ci(99%)=[6.186421e+019,6.191833e+019] n=501280428 sdn=2.351758e+020 t=1829.86s
114) m=6.188861e+019 sd=1.064436e+016 ci(99%)=[6.186119e+019,6.191603e+019] n=501279647 sdn=2.383195e+020 t=1837.08s
115) m=6.188280e+019 sd=1.089486e+016 ci(99%)=[6.185473e+019,6.191086e+019] n=501277456 sdn=2.439274e+020 t=1787.16s
116) m=6.188394e+019 sd=1.041013e+016 ci(99%)=[6.185712e+019,6.191075e+019] n=501279502 sdn=2.330752e+020 t=1786.92s
117) m=6.188412e+019 sd=1.011535e+016 ci(99%)=[6.185806e+019,6.191018e+019] n=501278484 sdn=2.264750e+020 t=1787.61s
118) m=6.187346e+019 sd=1.024464e+016 ci(99%)=[6.184707e+019,6.189985e+019] n=501278990 sdn=2.293699e+020 t=1788.97s
119) m=6.187020e+019 sd=1.016764e+016 ci(99%)=[6.184401e+019,6.189639e+019] n=501279750 sdn=2.276461e+020 t=1788.77s
120) m=6.188485e+019 sd=1.097793e+016 ci(99%)=[6.185657e+019,6.191313e+019] n=501278229 sdn=2.457876e+020 t=1788.67s |
It is not easy for me find the requested time for running those samples, so the number of them will grow, but (very) slowly. I do not know the number of samples I will run until I finish this experiment.
Averaging the accumulated data with Excel:
| Code: |
Averages after N = 120 MonteCarlo perft samples:
<m> ~ 61,882,166,247,766,000,000
<sd> ~ 10,532,596,445,177,000
(Minimum value with 99% confidence) ~ <m> - (2.575829303)<sd> ~ 61,855,036,077,205,900,000
(Maximum value with 99% confidence) ~ <m> + (2.575829303)<sd> ~ 61,909,296,418,326,200,000
<m>/<sd> ~ 5,875.300
<n> ~ 501,279,506.50 |
Results seem credible IMHO.
Regards from Spain.
Ajedrecista.
_________________
Six Fortran 95 tools.
Chess will never be solved. |
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