38 citations · 96 across the 20 of their papers we have counts for
3 papers · 1 filter
Efficient Exploration using Model-Based Quality-Diversity with Gradients
Bryan Lim, Manon Flageat, Antoine Cully
Exploration is a key challenge in Reinforcement Learning, especially in long-horizon, deceptive and sparse-reward environments. For such applications, population-based approaches h…
Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning
Manon Flageat, Bryan Lim, Luca Grillotti +3
We present a Quality-Diversity benchmark suite for Deep Neuroevolution in Reinforcement Learning domains for robot control. The suite includes the definition of tasks, environments…
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…