J. J. Merelo , Carlos Cotta, Antonio Mora U. Granada & Málaga (Spain) Http://geneura.wordpress.com http://twitter.com/geneura Optimizing worst-case scenario in evolutionary solutions to the MasterMind puzzle
Game of MasterMind
7 reasons why you should care
Differential cryptanalisis/ATM cracking
Optimal solution not known
Interesting search problem
Let's play, then
Find a consistent combination and play it.
Looking for consistent solutions
Optimization algorithm based on distance to consistency (for all combinations played)
D = 2
Not all consistent combinations are born the same
There's at least one better than the others (the solution).
Some will reduce the remaining search space more.
But scoring them is an open issue.
What we did before
Apply heuristic methods to speed up finishing games
What we do now Increase diversity in search via new operators and selection mechanisms
Reduce the probability of takeover by a single individual
Reduce the possibility of repeated generation of a single combination
Increase speed to afford tackling bigger sizes
New tricks for old games
Add permutation operator
Add diff uniform crossover
crossover over different positions only
Selection makes sure parents are different
Change to tournament selection
Stronger selective pressure
Higher replacement rate
Results: number of evaluations
Results: any good at MasterMind? Better Better
Worst case is better! Measures to increase diversity have a positive impact on quality of algorithm and also speed