6 citations · 6 across the 6 of their papers we have counts for
3 papers · 1 filter
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…