My research interests are in the area of evolutionary machine learning. These relate to the analysis of Neuroevolution algorithms through effective visualisation techniques, in order to explain their inherent mechanisms. My research is specifically directed to evolutionary algorithms that evolve both the structure and the weights of Artificial Neural Networks. Precisely, my interests and current work extends to the understanding of efficient utilisation of (indirect) plasticity encoding for said Neural Networks.
Conference Proceeding
Neuroevolution Trajectory Networks of the Behaviour Space
Sarti S, Adair J & Ochoa G (2022) Neuroevolution Trajectory Networks of the Behaviour Space. In: Jiménez Laredo JL, Hidalgo JI & Babaagba KO (eds.) Applications of Evolutionary Computation. Lecture Notes in Computer Science, 13224. EvoApplications 2022, Madrid, Spain, 20.04.2022-22.04.2022. Cham, Switzerland: Springer International Publishing, pp. 685-703. https://doi.org/10.1007/978-3-031-02462-7_43
Article
Recombination and Novelty in Neuroevolution: A Visual Analysis
Sarti S, Adair J & Ochoa G (2022) Recombination and Novelty in Neuroevolution: A Visual Analysis. SN Computer Science, 3 (3), Art. No.: 185. https://doi.org/10.1007/s42979-022-01064-6
Conference Proceeding
A NEAT Visualisation of Neuroevolution Trajectories
Sarti S & Ochoa G (2021) A NEAT Visualisation of Neuroevolution Trajectories. In: Castillo PA & Jiménez Laredo JL (eds.) Applications of Evolutionary Computation. Lecture Notes in Computer Science, 12694. 24th International Conference, EvoApplications 2021, Seville, Spain, 07.04.2021-09.04.2021. Cham, Switzerland: Springer, pp. 714-728. https://doi.org/10.1007/978-3-030-72699-7_45
