activity
20232026
most citedOvercoming Deceptiveness in Fitness Optimization with Unsupervised Quality-Diversity

6 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2026

Sampling-Based MuJoCo MPC for Double-Pendulum Sway Suppression on a Shipboard Crane

Oscar Pang, Lisa Coiffard, Paul Templier +3

Transferring heavy payloads in maritime settings relies on efficient crane operation, limited by hazardous double-pendulum payload sway. This sway motion is further exacerbated in…

cs.RO2025★ 1 cited

From Tabula Rasa to Emergent Abilities: Discovering Robot Skills via Real-World Unsupervised Quality-Diversity

Luca Grillotti, Lisa Coiffard, Oscar Pang +2

Autonomous skill discovery aims to enable robots to acquire diverse behaviors without explicit supervision. Learning such behaviors directly on physical hardware remains challengin…

cs.NE2025★ 6 cited

Overcoming Deceptiveness in Fitness Optimization with Unsupervised Quality-Diversity

Lisa Coiffard, Paul Templier, Antoine Cully

Policy optimization seeks the best solution to a control problem according to an objective or fitness function, serving as a fundamental field of engineering and research with appl…

cs.NE2025★ 1 cited

Dominated Novelty Search: Rethinking Local Competition in Quality-Diversity

Ryan Bahlous-Boldi, Maxence Faldor, Luca Grillotti +4

Quality-Diversity is a family of evolutionary algorithms that generate diverse, high-performing solutions through local competition principles inspired by natural evolution. While…

cs.LG2023★ 2 cited

Multiscale Neural Operators for Solving Time-Independent PDEs

Winfried Ripken, Lisa Coiffard, Felix Pieper +1

Time-independent Partial Differential Equations (PDEs) on large meshes pose significant challenges for data-driven neural PDE solvers. We introduce a novel graph rewiring technique…