All Outputs (2)

A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms (2023)
Conference Proceeding
Montague, K., Hart, E., Paechter, B., & Nitschke, G. (2023). A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms. In J. Correia, S. Smith, & R. Qaddoura (Eds.), Applications of Evolutionary Computation: 26th European Conference, EvoApplications 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings (145-160). https://doi.org/10.1007/978-3-031-30229-9_10

Designing controllers for a swarm of robots such that collabo-rative behaviour emerges at the swarm level is known to be challenging. Evolutionary approaches have proved promising, with attention turning more recently to evolving repertoires of dive... Read More about A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms.

On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architecture (2023)
Conference Proceeding
Lupión, M., Cruz, N. C., Paechter, B., & Ortigosa, P. M. (2023). On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architecture. In Metaheuristics: 14th International Conference, MIC 2022, Syracuse, Italy, July 11–14, 2022, Proceedings (133-142). https://doi.org/10.1007/978-3-031-26504-4_10

Neural networks stand out in Artificial Intelligence for their capacity of being applied to multiple challenging tasks such as image classification. However, designing a neural network to address a particular problem is also a demanding task that req... Read More about On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architecture.