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Table 4 Rule sets evolved for the 1st network instance, shown with [performance estimate, fitness]

From: Evolution of control with learning classifier systems

Set 1 Set 2 Set 3 Set 4 Set 5
##### : 1 [94.67/0.9031] ##### : 3 [106.62/0.9998] ##### : 2 [101.2/0.9999] ##### : 2 [102.59/0.9999] ##### : 1 [106.46/0.9691]
##### : 2 [96.39/0.999] ##### : 1 [100.4/1] ##### : 1 [104.67/0.9999] ##### : 3 [101.54/1] ##### : 3 [106.86/0.9907]
##### : 3 [95.01/0.9968] ##### : 2 [97.51/1] ##### : 3 [101.57/1] ##### : 1 [98.45/0.9994] ##### : 2 [105.79/0.9885]
####0 : 5 [103.31/0.8209] ###0# : 0 [100.08/0.8696] ####1 : 0 [98.06/0.8865] ####1 : 0 [104.46/0.9143] ####1 : 0 [110.8/0.9087]
####1 : 0 [101/0.8834] ###1# : 4 [99.61/0.6823] ###0# : 0 [104.69/0.878] ###0# : 0 [98.97/0.9045] ###0# : 0 [99.03/0.9037]
###0# : 0 [98.82/0.8742] ####1 : 0 [104.48/0.8532] ####0 : 5 [106.82/0.6445] ###1# : 4 [101.47/0.6664] ####0 : 5 [107.1/0.7033]
###1# : 4 [100.56/0.5989] ####0 : 5 [102.1/0.6612] ###1# : 4 [108.2/0.6296] ####0 : 5 [100.98/0.7138] ###1# : 4 [102.56/0.6743]
####1 : 4 [97.87/0.4512] ####1 : 4 [100.21/0.3237] ###0# : 5 [105.84/0.3973] ####1 : 4 [99.05/0.3768] ###0# : 5 [98.76/0.3346]
##### : 0 [135.11/0.0642] ###0# : 5 [100.38/0.3645] ####1 : 4 [104.92/0.409] ##### : 5 [114.67/0.077] ####1 : 4 [98.63/0.3579]
##### : 4 [117.54/0.0547] ##### : 0 [173.14/0.0583] ##### : 0 [178.02/0.0632] ###0# : 5 [99.32/0.2865] ##### : 5 [116.26/0.0925]
  ##### : 4 [109.75/0.0622] ##### : 5 [126.9/0.0724] ##### : 0 [158.1/0.0458] ##### : 4 [118.29/0.0599]
  ##### : 5 [127.45/0.0594]   ##0## : 4 [120.77/0.0474] ##### : 0 [225.99/0.0472]
  ##0## : 0 [173.14/0.0399]    
  0#### : 5 [127.45/0.0505]    
  0#### : 0 [173.14/0.0342]    
  ##0## : 5 [127.45/0.0375]    
  #0### : 0 [173.14/0.0279]