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Comparing evolutionary algorithms
to solve the game of MasterMind
J. J. Merelo, A. M. Mora, P. A. Castillo,
C. Cotta, M. Valdez
UGR, UMA, ITT
Combination played
Consistent!
Not consistent! Always play consistent!
Optimization algorithm
based on distance to
consistency (for all
combinations played)
D = 2
Not all consistent combinations are
the same: use partitions
0b-0w 0b-1w 0b-2w 0b-3w 1b-0w 1b-1w 1b-2w 2b-0w
AAA 2 0 0 0 3 0 0 3
BBB 4 0 0 0 4 0 0 0
CCC 4 0 0 0 4 0 0 0
ABC 0 0 0 1 4 1 1 1
CBA 0 1 2 0 3 0 2 0
AAB 1 0 2 0 1 1 0 3
AAC 1 0 2 0 1 0 0 4
AAD 2 2 0 0 1 0 0 3
BCA 0 1 2 1 3 0 1 0
Most parts. Score = 5 Best worst case. Score = -3
1.31
0.96
0.96
1.58
1.52
1.67
1.42
1.52
1.67
Entropy. Score = 1.67
We use entropy for scoring.
Check the size of the consistent set needed
for good and fast solutions.

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Poster: A search for scalable evolutionary solutions to the game of MasterMind

  • 1. Comparing evolutionary algorithms to solve the game of MasterMind J. J. Merelo, A. M. Mora, P. A. Castillo, C. Cotta, M. Valdez UGR, UMA, ITT Combination played Consistent! Not consistent! Always play consistent! Optimization algorithm based on distance to consistency (for all combinations played) D = 2 Not all consistent combinations are the same: use partitions 0b-0w 0b-1w 0b-2w 0b-3w 1b-0w 1b-1w 1b-2w 2b-0w AAA 2 0 0 0 3 0 0 3 BBB 4 0 0 0 4 0 0 0 CCC 4 0 0 0 4 0 0 0 ABC 0 0 0 1 4 1 1 1 CBA 0 1 2 0 3 0 2 0 AAB 1 0 2 0 1 1 0 3 AAC 1 0 2 0 1 0 0 4 AAD 2 2 0 0 1 0 0 3 BCA 0 1 2 1 3 0 1 0 Most parts. Score = 5 Best worst case. Score = -3 1.31 0.96 0.96 1.58 1.52 1.67 1.42 1.52 1.67 Entropy. Score = 1.67 We use entropy for scoring. Check the size of the consistent set needed for good and fast solutions.