19 citations · 32 across the 11 of their papers we have counts for
11 papers
Generalized Early Stopping in Evolutionary Direct Policy Search
Etor Arza, Leni K. Le Goff, Emma Hart
Lengthy evaluation times are common in many optimization problems such as direct policy search tasks, especially when they involve conducting evaluations in the physical world, e.g…
To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features
Diederick Vermetten, Hao Wang, Kevin Sim +1
Dynamic algorithm selection aims to exploit the complementarity of multiple optimization algorithms by switching between them during the search. While these kinds of dynamic algori…
Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches
Mohamad Alissa, Kevin Sim, Emma Hart
We propose a novel technique for algorithm-selection, applicable to optimisation domains in which there is implicit sequential information encapsulated in the data, e.g., in online…
Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers
Rui P. Cardoso, Emma Hart, David Burth Kurka +1
Using Neuroevolution combined with Novelty Search to promote behavioural diversity is capable of constructing high-performing ensembles for classification. However, using gradient…
Comparison of atlas-based and neural-network-based semantic segmentation for DENSE MRI images
Elle Buser, Emma Hart, Ben Huenemann
Two segmentation methods, one atlas-based and one neural-network-based, were compared to see how well they can each automatically segment the brain stem and cerebellum in Displacem…
Morpho-evolution with learning using a controller archive as an inheritance mechanism
Léni K. Le Goff, Edgar Buchanan, Emma Hart +9
The joint optimisation of body-plan and control via evolutionary processes can be challenging in rich morphological spaces in which offspring can have body-plans that are very diff…