Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Zen and the Art of Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Automatic generation of XSLT stylesheets using evolutionary algorithms
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Efficient solutions for Mastermind using genetic algorithms
Computers and Operations Research
The Mastermind Attack on Genomic Data
SP '09 Proceedings of the 2009 30th IEEE Symposium on Security and Privacy
Entropy-driven evolutionary approaches to the mastermind problem
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Improving and scaling evolutionary approaches to the mastermind problem
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
Implementation matters: programming best practices for evolutionary algorithms
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Finding better solutions to the mastermind puzzle using evolutionary algorithms
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Guessing Bank PINs by Winning a Mastermind Game
Theory of Computing Systems - Special Issue: Fun with Algorithms
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Solving the MasterMind puzzle, that is, finding out a hidden combination by using hints that tell you how close some strings are to that one is a combinatorial optimization problem that becomes increasingly difficult with string size and the number of symbols used in it. Since it does not have an exact solution, heuristic methods have been traditionally used to solve it; these methods scored each combination using a heuristic function that depends on comparing all possible solutions with each other. In this paper we first optimize the implementation of previous evolutionary methods used for the game of mastermind, obtaining up to a 40% speed improvement over them. Then we study the behavior of an entropy-based score, which has previously been used but not checked exhaustively and compared with previous solutions. The combination of these two strategies obtain solutions to the game of Mastermind that are competitive, and in some cases beat, the best solutions obtained so far. All data and programs have also been published under an open source license.