Publications

Journal papers

Pagliuca, P., Inglese, D. Y., & Vitanza, A. (2023). Measuring emergent behaviors in a mixed competitive-cooperative environment. International Journal of Computer Information Systems and Industrial Management Applications, vol. 15, pp. 69-86.
Pagliuca, P., & Nolfi, S. (2022). The dynamic of body and brain co-evolution. Adaptive Behavior, 30(3), 245-255. DOI: https://doi.org/10.1177/1059712321994685
Pagliuca, P., Milano, N., & Nolfi, S. (2020). Efficacy of modern neuro-evolutionary strategies for continuous control optimization. Frontiers in Robotics and AI, 7, 98. DOI: https://doi.org/10.3389/frobt.2020.00098
Pagliuca, P., & Nolfi, S. (2019). Robust optimization through neuroevolution. PloS one, 14(3), e0213193. DOI: https://doi.org/10.1371/journal.pone.0213193
Milano, N., Pagliuca, P., & Nolfi, S. (2019). Robustness, evolvability and phenotypic complexity: insights from evolving digital circuits. Evolutionary Intelligence, 12, 83-95. DOI: https://doi.org/10.1177/1059712315608424
Pagliuca, P., Milano, N., & Nolfi, S. (2018). Maximizing adaptive power in neuroevolution. PloS one, 13(7), e0198788. DOI: https://doi.org/10.1371/journal.pone.0198788
Pagliuca, P., & Nolfi, S. (2015). Integrating learning by experience and demonstration in autonomous robots. Adaptive Behavior, 23(5), 300-314. DOI: https://doi.org/10.1177/1059712315608424

Book chapters

Pagliuca, P., & Vitanza, A. (2023). Evolving aggregation behaviors in swarms from an evolutionary algorithms point of view. In Applications of Artificial Intelligence and Neural Systems to Data Science (pp. 317-328). Singapore: Springer Nature Singapore. DOI: https://doi.org/10.1007/978-981-99-3592-5_30

Conference papers

Vitanza, A., Pagliuca, P., Cantucci, F., & Nolfi, S. (2023, October). Skeleton Timed Up and Go on MARIO robot. In 2023 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (pp. 1171-1176). IEEE. DOI: https://doi.org/10.1109/MetroXRAINE58569.2023.10405769
Pagliuca, P., & Vitanza, A. (2022, December). Self-organized Aggregation in Group of Robots with OpenAI-ES. In International Conference on Soft Computing and Pattern Recognition (pp. 770-780). Cham: Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-031-27524-1_75
Pagliuca, P., Milano, N., & Nolfi, S. (2022, October). Automated Categorization of Behavioral Quality Through Deep Neural Networks. In 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (pp. 372-376). IEEE. DOI: https://doi.org/10.1109/MetroXRAINE54828.2022.9967505

Workshop papers

Pagliuca, P., & Vitanza, A. (2023, November). N-Mates Evaluation: a New Method to Improve the Performance of Genetic Algorithms in Heterogeneous Multi-Agent Systems. Proceedings of the 24th Workshop From Objects to Agents (WOA 2023), vol. 3579, pp. 123-137.

Abstracts in conference proceedings

Zribi, M., Pagliuca, P., & Pitolli, F. (2023, October). Convolutional Neural Networks for the Automatic Control of Consumables for Analytical Laboratories. BUILD-IT 2023 Workshop, pp. 95-97.
Tufo, G., Zribi, M., Pitolli, F. & Pagliuca, P. (2023, September). Advanced Computer Vision Techniques for Drug Abuse Detection. 21st IMACS World Congress (IMACS2023), vol. 23, pp. 226.