All Outputs (4)

New directions in fitness evaluation: commentary on Langdon’s JAWS30 (2023)
Journal Article
Johnson, C. G. (2023). New directions in fitness evaluation: commentary on Langdon’s JAWS30. Genetic Programming and Evolvable Machines, 24(2), Article 22. https://doi.org/10.1007/s10710-023-09470-2

Langdon's paper emphasises the key role of fitness in GP, yet notes issues with current approaches to fitness: "In GP, as in most optimisation problems, most of the computation effort is spent on evaluating how good the proposed solutions are". The p... Read More about New directions in fitness evaluation: commentary on Langdon’s JAWS30.

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”.

Creative autonomy in a simple interactive music system (2020)
Journal Article
Paolizzo, F., & Johnson, C. G. (2020). Creative autonomy in a simple interactive music system. Journal of New Music Research, 49(2), 115-125. https://doi.org/10.1080/09298215.2019.1709510

Can autonomous systems be musically creative without musical knowledge? Assumptions from interdisciplinary studies on self-reflection are evaluated using Video Interactive VST Orchestra, a system that generates music from audio and video inputs throu... Read More about Creative autonomy in a simple interactive music system.

A new sequential covering strategy for inducing classification rules with ant colony algorithms (2012)
Journal Article
Otero, F. E. B., Freitas, A. A., & Johnson, C. G. (2012). A new sequential covering strategy for inducing classification rules with ant colony algorithms. IEEE Transactions on Evolutionary Computation, 17(1), 64-76. https://doi.org/10.1109/TEVC.2012.2185846

Ant colony optimization (ACO) algorithms have been successfully applied to discover a list of classification rules. In general, these algorithms follow a sequential covering strategy, where a single rule is discovered at each iteration of the algorit... Read More about A new sequential covering strategy for inducing classification rules with ant colony algorithms.