457 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Max Planck Institute for Radio AstronomyDE14 papers
- University of SiegenDE9 papers
- University of CologneDE8 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)DE5 papers
- Ruhr University BochumDE5 papers
- Université de LorraineFR5 papers
- University of BonnDE5 papers
- University of BremenDE5 papers
- Fraunhofer Institute for Algorithms and Scientific ComputingDE4 papers
- Fraunhofer Institute for Applied Information TechnologyDE4 papers
- Fraunhofer Institute for Intelligent Analysis and Information SystemsDE4 papers
10 papers · 1 filter
Designing Air Flow with Surrogate-assisted Phenotypic Niching
Alexander Hagg, Dominik Wilde, Alexander Asteroth +1
In complex, expensive optimization domains we often narrowly focus on finding high performing solutions, instead of expanding our understanding of the domain itself. But what if we…
An Analysis of Phenotypic Diversity in Multi-Solution Optimization
Alexander Hagg, Mike Preuss, Alexander Asteroth +1
More and more, optimization methods are used to find diverse solution sets. We compare solution diversity in multi-objective optimization, multimodal optimization, and quality dive…
Discovering Representations for Black-box Optimization
Adam Gaier, Alexander Asteroth, Jean-Baptiste Mouret
The encoding of solutions in black-box optimization is a delicate, handcrafted balance between expressiveness and domain knowledge -- between exploring a wide variety of solutions,…
Prediction of neural network performance by phenotypic modeling
Alexander Hagg, Martin Zaefferer, Jörg Stork +1
Surrogate models are used to reduce the burden of expensive-to-evaluate objective functions in optimization. By creating models which map genomes to objective values, these models…
Modeling User Selection in Quality Diversity
Alexander Hagg, Alexander Asteroth, Thomas Bäck
The initial phase in real world engineering optimization and design is a process of discovery in which not all requirements can be made in advance, or are hard to formalize. Qualit…
Prototype Discovery using Quality-Diversity
Alexander Hagg, Alexander Asteroth, Thomas Bäck
An iterative computer-aided ideation procedure is introduced, building on recent quality-diversity algorithms, which search for diverse as well as high-performing solutions. Dimens…
Data-efficient Neuroevolution with Kernel-Based Surrogate Models
Adam Gaier, Alexander Asteroth, Jean-Baptiste Mouret
Surrogate-assistance approaches have long been used in computationally expensive domains to improve the data-efficiency of optimization algorithms. Neuroevolution, however, has so…
Hierarchical Surrogate Modeling for Illumination Algorithms
Alexander Hagg
Evolutionary illumination is a recent technique that allows producing many diverse, optimal solutions in a map of manually defined features. To support the large amount of objectiv…
Evolving Parsimonious Networks by Mixing Activation Functions
Alexander Hagg, Maximilian Mensing, Alexander Asteroth
Neuroevolution methods evolve the weights of a neural network, and in some cases the topology, but little work has been done to analyze the effect of evolving the activation functi…
Data-Efficient Exploration, Optimization, and Modeling of Diverse Designs through Surrogate-Assisted Illumination
Adam Gaier, Alexander Asteroth, Jean-Baptiste Mouret
The MAP-Elites algorithm produces a set of high-performing solutions that vary according to features defined by the user. This technique has the potential to be a powerful tool for…