9 citations · 10 across the 3 of their papers we have counts for
8 papers
Ensemble Feature Extraction for Multi-Container Quality-Diversity Algorithms
Leo Cazenille
Quality-Diversity algorithms search for large collections of diverse and high-performing solutions, rather than just for a single solution like typical optimisation methods. They a…
Exploring Self-Assembling Behaviors in a Swarm of Bio-micro-robots using Surrogate-Assisted MAP-Elites
Leo Cazenille, Nicolas Bredeche, Nathanael Aubert-Kato
Swarms of molecular robots are a promising approach to create specific shapes at the microscopic scale through self-assembly. However, controlling their behavior is a challenging p…
Comparing reliability of grid-based Quality-Diversity algorithms using artificial landscapes
Leo Cazenille
Quality-Diversity (QD) algorithms are a recent type of optimisation methods that search for a collection of both diverse and high performing solutions. They can be used to effectiv…
Automatic Calibration of Artificial Neural Networks for Zebrafish Collective Behaviours using a Quality Diversity Algorithm
Leo Cazenille, Nicolas Bredeche, José Halloy
During the last two decades, various models have been proposed for fish collective motion. These models are mainly developed to decipher the biological mechanisms of social interac…
Exploration and Exploitation in Symbolic Regression using Quality-Diversity and Evolutionary Strategies Algorithms
J. -P. Bruneton, L. Cazenille, A. Douin +1
By combining Genetic Programming, MAP-Elites and Covariance Matrix Adaptation Evolution Strategy, we demonstrate very high success rates in Symbolic Regression problems. MAP-Elites…
Modelling zebrafish collective behaviours with multilayer perceptrons optimised by evolutionary algorithms
Leo Cazenille, Nicolas Bredeche, José Halloy
Collective movements are pervasive behaviours among social organisms and have led to the development of many models. However, modelling animal trajectories and social interactions…