output.bipolar.60.fitness

PostsBayesian Optimization Algorithm with Decision Graphs in C++,

  0    2000   9.099999   6.863800   2.600000
  1    3000   9.099999   7.339151   2.600000
  2    4000   9.099999   7.658951   4.300000
  3    5000   9.099999   7.802701   3.500000
  4    6000   9.200000   8.091701   4.400000
  5    7000   9.200000   8.377801   5.700000
  6    8000   9.200000   8.488051   6.600001
  7    9000   9.200000   8.568850   6.700001
  8   10000   9.400000   8.637000   6.700000
  9   11000   9.400000   8.560350   6.000000
 10   12000   9.400000   8.529950   5.200000
 11   13000   9.400000   8.602700   6.000000
 12   14000   9.400000   8.641050   5.800000
 13   15000   9.400000   8.649700   6.000000
 14   16000   9.400000   8.635250   6.000000
 15   17000   9.400000   8.772100   6.400000
 16   18000   9.600000   8.935950   8.100000
 17   19000   9.600000   8.869350   6.900001
 18   20000   9.600000   8.928500   6.900001
 19   21000   9.800000   9.051650   7.300000
 20   22000   9.800000   9.144700   7.900000
 21   23000   9.800000   9.241400   7.900001
 22   24000   9.800000   9.255100   8.100000
 23   25000   9.800000   9.353650   8.200001
 24   26000   9.900000   9.461450   8.700001
 25   27000   9.900000   9.545300   9.000000
 26   28000  10.000000   9.593300   8.500000
 27   29000  10.000000   9.663200   8.700001
 28   30000  10.000000   9.740250   9.400000
 29   31000  10.000000   9.797300   8.600000
 30   32000  10.000000   9.848000   9.600000
 31   33000  10.000000   9.906350   9.700001
 32   34000  10.000000   9.932200   8.900000
 33   35000  10.000000   9.967650   9.800000
 34   36000  10.000000  10.000000  10.000000