activity
20162026
most citedDesigning Air Flow with Surrogate-assisted Phenotypic Niching

17 citations · 58 across the 12 of their papers we have counts for

collaborators

13 papers

cs.NE2026

U-Net-Accelerated Quality-Diversity Optimization for Climate-Adaptive Urban Layouts

Alexander Hagg, Tania Guerrero, Dirk Reith

Optimizing urban layouts for climate adaptation requires balancing building density with cold-air ventilation. Because physics-based climate simulations are computationally expensi…

cs.LG2025

Full Domain Analysis in Fluid Dynamics

Alexander Hagg, Adam Gaier, Dominik Wilde +3

Novel techniques in evolutionary optimization, simulation and machine learning allow for a broad analysis of domains like fluid dynamics, in which computation is expensive and flow…

cs.NE2023

On the Suitability of Representations for Quality Diversity Optimization of Shapes

Ludovico Scarton, Alexander Hagg

The representation, or encoding, utilized in evolutionary algorithms has a substantial effect on their performance. Examination of the suitability of widely used representations fo…

cs.NE2023

Efficient Quality Diversity Optimization of 3D Buildings through 2D Pre-optimization

Alexander Hagg, Martin L. Kliemank, Alexander Asteroth +4

Quality diversity algorithms can be used to efficiently create a diverse set of solutions to inform engineers' intuition. But quality diversity is not efficient in very expensive p…

cs.NE2021★ 17 cited

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…

cs.NE2021★ 7 cited

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…