Publicaciones en las que colabora con JUAN JULIÁN MERELO GUERVOS (10)

2017

  1. Programa Patrimonio Abierto de la Universidad de Granada

    PH: Boletín del Instituto Andaluz del Patrimonio Histórico, Año 25, Núm. 91, pp. 31-32

2016

  1. A statistical approach to dealing with noisy fitness in evolutionary algorithms

    Studies in Computational Intelligence (Springer Verlag), pp. 79-95

  2. Performance for the masses: Experiments with A Web based architecture to harness volunteer resources for low cost distributed evolutionary computation

    GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference

  3. The uncertainty quandary: A study in the context of the evolutionary optimization in games and other uncertain environments

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2015

  1. Comparing optimization methods, in continuous space, for modelling with a diffusion process

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. There is noisy lunch: A study of noise in evolutionary optimization problems

    IJCCI 2015 - Proceedings of the 7th International Joint Conference on Computational Intelligence

2014

  1. Studying and tackling noisy fitness in evolutionary design of game characters

    ECTA 2014 - Proceedings of the International Conference on Evolutionary Computation Theory and Applications

2013

  1. Influence of selective pressure on quality of solutions and speed of evolutionary mastermind

    Proceedings of the 2013 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013

  2. Using statistical tools to determine the significance and relative importance of the main parameters of an evolutionary algorithm

    Intelligent Data Analysis, Vol. 17, Núm. 5, pp. 771-789

2012

  1. Determining the significance and relative importance of parameters of a simulated quenching algorithm using statistical tools

    Applied Intelligence, Vol. 37, Núm. 2, pp. 239-254