All Outputs (3)

Metaheuristics “In the Large” (2021)
Journal Article
Swan, J., Adriaensen, S., Johnson, C. G., Kheiri, A., Krawiec, F., Merelo, J. J., …White, D. R. (2022). Metaheuristics “In the Large”. European Journal of Operational Research, 297(2), 393-406. https://doi.org/10.1016/j.ejor.2021.05.042

Following decades of sustained improvement, metaheuristics are one of the great success stories of optimization research. However, in order for research in metaheuristics to avoid fragmentation and a lack of reproducibility, there is a pressing need... Read More about Metaheuristics “In the Large”.

Creating a Digital Mirror of Creative Practice (2021)
Presentation / Conference Contribution
Johnson, C. (2021). Creating a Digital Mirror of Creative Practice. In Computational Intelligence in Music, Sound, Art and Design – 10th International Conference, EvoMUSART 2021 (427-442). https://doi.org/10.1007/978-3-030-72914-1_28

This paper describes an ongoing project to create a “digital mirror” to my practice as a composer of contemporary classical music; that is, a system that takes descriptions (in code) of aspects of that practice, and reflects them back as computer-gen... Read More about Creating a Digital Mirror of Creative Practice.

Solving the Rubik's cube with stepwise deep learning (2021)
Journal Article
Johnson, C. G. (2021). Solving the Rubik's cube with stepwise deep learning. Expert Systems, 38(3), Article e12665. https://doi.org/10.1111/exsy.12665

This paper explores a novel technique for learning the fitness function for search algorithms such as evolutionary strategies and hillclimbing. The aim of the new technique is to learn a fitness function (called a Learned Guidance Function) from a se... Read More about Solving the Rubik's cube with stepwise deep learning.