Uma Abordagem Baseada em Algoritmos Genéticos para Resolução do Jogo Mastermind: Comparação com Estratégias da Literatura
Resumo
Este estudo propõe uma solução para o jogo MasterMind utilizando Algoritmos Genéticos (AGs) em uma estratégia de duas etapas: identificação das cores do código secreto e determinação de suas posições. Foram testadas variações nos operadores genéticos, com destaque para a Matriz de Recompensa, que adota um processo de aprendizado coletivo baseado em memória histórica e evidencia um comportamento análogo à inteligência coletiva. Os resultados mostraram desempenho superior em relação a outras estratégias, especialmente em cenários complexos.Referências
Abreu, P. and Mendes, P. (2008). Mastermind: an augment reality approach: [porting a legacy game to new interaction paradigms]. In Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts, pages 205–210.
Bento, L., Pereira, L., and Rosa, A. (1999). Mastermind by evolutionary algorithms. In Proceedings of the 1999 ACM symposium on Applied computing, pages 307–311.
Berghman, L., Goossens, D., and Leus, R. (2009). Efficient solutions for mastermind using genetic algorithms. Computers & operations research, 36(6):1880–1885.
Bernier, J. L., Herráiz, C. I., Merelo, J., Olmeda, S., and Prieto, A. (1996). Solving mastermind using gas and simulated annealing: a case of dynamic constraint optimization. In Parallel Problem Solving from Nature—PPSN IV: International Conference on Evolutionary Computation—The 4th International Conference on Parallel Problem Solving from Nature Berlin, Germany, September 22–26, 1996 Proceedings 4, pages 553–563. Springer.
Kalisker, T. and Camens, D. (2003). Solving mastermind using genetic algorithms. In Genetic and Evolutionary Computation Conference, pages 1590–1591. Springer.
Maestro-Montojo, J., Salcedo-Sanz, S., and Merelo, J. (2014). New solver and optimal anticipation strategies design based on evolutionary computation for the game of mastermind. Evolutionary Intelligence, 6:219–228.
Merelo, J. J., Cotta, C., and Mora, A. (2011). Improving and scaling evolutionary approaches to the mastermind problem. In European Conference on the Applications of Evolutionary Computation, pages 103–112. Springer.
Merelo, J.-J., Mora, A. M., Castillo, P. A., Cotta, C., and Valdez, M. (2013). A search for scalable evolutionary solutions to the game of mastermind. In 2013 IEEE Congress on Evolutionary Computation, pages 2298–2305. IEEE.
Merelo-Guervós, J., Castillo, P., and Rivas, V. (2006). Finding a needle in a haystack using hints and evolutionary computation: the case of evolutionary mastermind. Applied Soft Computing, 6(2):170–179.
Oijen, V. v. (2018). Genetic algorithms playing mastermind. B.S. thesis.
Bento, L., Pereira, L., and Rosa, A. (1999). Mastermind by evolutionary algorithms. In Proceedings of the 1999 ACM symposium on Applied computing, pages 307–311.
Berghman, L., Goossens, D., and Leus, R. (2009). Efficient solutions for mastermind using genetic algorithms. Computers & operations research, 36(6):1880–1885.
Bernier, J. L., Herráiz, C. I., Merelo, J., Olmeda, S., and Prieto, A. (1996). Solving mastermind using gas and simulated annealing: a case of dynamic constraint optimization. In Parallel Problem Solving from Nature—PPSN IV: International Conference on Evolutionary Computation—The 4th International Conference on Parallel Problem Solving from Nature Berlin, Germany, September 22–26, 1996 Proceedings 4, pages 553–563. Springer.
Kalisker, T. and Camens, D. (2003). Solving mastermind using genetic algorithms. In Genetic and Evolutionary Computation Conference, pages 1590–1591. Springer.
Maestro-Montojo, J., Salcedo-Sanz, S., and Merelo, J. (2014). New solver and optimal anticipation strategies design based on evolutionary computation for the game of mastermind. Evolutionary Intelligence, 6:219–228.
Merelo, J. J., Cotta, C., and Mora, A. (2011). Improving and scaling evolutionary approaches to the mastermind problem. In European Conference on the Applications of Evolutionary Computation, pages 103–112. Springer.
Merelo, J.-J., Mora, A. M., Castillo, P. A., Cotta, C., and Valdez, M. (2013). A search for scalable evolutionary solutions to the game of mastermind. In 2013 IEEE Congress on Evolutionary Computation, pages 2298–2305. IEEE.
Merelo-Guervós, J., Castillo, P., and Rivas, V. (2006). Finding a needle in a haystack using hints and evolutionary computation: the case of evolutionary mastermind. Applied Soft Computing, 6(2):170–179.
Oijen, V. v. (2018). Genetic algorithms playing mastermind. B.S. thesis.
Publicado
02/06/2025
Como Citar
CUNHA, João Pedro Silva; SILVA, Alexandre Tadeu Rossini da.
Uma Abordagem Baseada em Algoritmos Genéticos para Resolução do Jogo Mastermind: Comparação com Estratégias da Literatura. In: CONCURSO DE TESES, DISSERTAÇÕES E TCCS EM SISTEMAS COLABORATIVOS - SIMPÓSIO BRASILEIRO DE SISTEMAS COLABORATIVOS (SBSC), 20. , 2025, Manaus/AM.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 132-138.
DOI: https://doi.org/10.5753/sbsc_estendido.2025.8603.
