21 citations · 47 across the 14 of their papers we have counts for
3 papers · 1 filter
Assessing Quality-Diversity Neuro-Evolution Algorithms Performance in Hard Exploration Problems
Felix Chalumeau, Thomas Pierrot, Valentin Macé +4
A fascinating aspect of nature lies in its ability to produce a collection of organisms that are all high-performing in their niche. Quality-Diversity (QD) methods are evolutionary…
Empirical analysis of PGA-MAP-Elites for Neuroevolution in Uncertain Domains
Manon Flageat, Felix Chalumeau, Antoine Cully
Quality-Diversity algorithms, among which MAP-Elites, have emerged as powerful alternatives to performance-only optimisation approaches as they enable generating collections of div…
Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery
Felix Chalumeau, Raphael Boige, Bryan Lim +5
Deep Reinforcement Learning (RL) has emerged as a powerful paradigm for training neural policies to solve complex control tasks. However, these policies tend to be overfit to the e…