6 citations · 6 across the 6 of their papers we have counts for
6 papers
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…
Time to Play: Simulating Early-Life Animal Dynamics Enhances Robotics Locomotion Discovery
Paul Templier, Hannah Janmohamed, David Labonte +1
Developmental changes in body morphology profoundly shape locomotion in animals, yet artificial agents and robots are typically trained under static physical parameters. Inspired b…
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…
Genetic Drift Regularization: on preventing Actor Injection from breaking Evolution Strategies
Paul Templier, Emmanuel Rachelson, Antoine Cully +1
Evolutionary Algorithms (EA) have been successfully used for the optimization of neural networks for policy search, but they still remain sample inefficient and underperforming in…
Quality with Just Enough Diversity in Evolutionary Policy Search
Paul Templier, Luca Grillotti, Emmanuel Rachelson +2
Evolution Strategies (ES) are effective gradient-free optimization methods that can be competitive with gradient-based approaches for policy search. ES only rely on the total episo…
Searching Search Spaces: Meta-evolving a Geometric Encoding for Neural Networks
Tarek Kunze, Paul Templier, Dennis G Wilson
In evolutionary policy search, neural networks are usually represented using a direct mapping: each gene encodes one network weight. Indirect encoding methods, where each gene can…