Comparing evolutionary algorithms
to solve the game of MasterMind
J. J. Merelo, A. M. Mora, P. A. Castillo,
C. Cotta, M. V...
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Poster: A search for scalable evolutionary solutions to the game of MasterMind

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Presented at CEC 2013, including moving parts which obviously can't be shown here.

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

  1. 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.

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