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Alexander Hagg
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Zitiert von
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Evolving parsimonious networks by mixing activation functions
A Hagg, M Mensing, A Asteroth
Proceedings of the Genetic and Evolutionary Computation Conference, 425-432, 2017
232017
Prototype discovery using quality-diversity
A Hagg, A Asteroth, T Bäck
International Conference on Parallel Problem Solving from Nature, 500-511, 2018
202018
How to successfully apply genetic algorithms in practice: Representation and parametrization
A Asteroth, A Hagg
2015 International Symposium on Innovations in Intelligent SysTems and …, 2015
152015
Multi-stage evolution of single-and multi-objective MCLP
H Spieker, A Hagg, A Gaier, S Meilinger, A Asteroth
Soft Computing 21 (17), 4859-4872, 2017
102017
Designing air flow with surrogate-assisted phenotypic niching
A Hagg, D Wilde, A Asteroth, T Bäck
International Conference on Parallel Problem Solving from Nature, 140-153, 2020
82020
On recognizing transparent objects in domestic environments using fusion of multiple sensor modalities
A Hagg, F Hegger, PG Plöger
Robot world cup, 3-15, 2016
82016
Expressivity of parameterized and data-driven representations in quality diversity search
A Hagg, S Berns, A Asteroth, S Colton, T Bäck
Proceedings of the Genetic and Evolutionary Computation Conference, 678-686, 2021
72021
Modeling user selection in quality diversity
A Hagg, A Asteroth, T Bäck
Proceedings of the Genetic and Evolutionary Computation Conference, 116-124, 2019
62019
Prediction of neural network performance by phenotypic modeling
A Hagg, M Zaefferer, J Stork, A Gaier
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019
52019
An analysis of phenotypic diversity in multi-solution optimization
A Hagg, M Preuss, A Asteroth, T Bäck
International Conference on Bioinspired Methods and Their Applications, 43-55, 2020
32020
Hierarchical surrogate modeling for illumination algorithms
A Hagg
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2017
32017
Methodische Grundlegung für eine Strategie zum sukzessiven Ausbau der Ladeinfrastruktur für Elektromobilität in Bonn und dem Rhein-Sieg-Kreis: Studie zur Strategie für den …
A Hagg, H Spieker, A Oslislo, V Jacobs, A Asteroth, S Meilinger
32015
The b-it-bots Robo-Cup@ Home 2014 Team Description Paper
R Dwiputra, M Füller, F Hegger, S Schneider, N Hochgeschwender, ...
Joao Pessoa, Brazil, 2014
32014
Phenotypic Niching Using Quality Diversity Algorithms
A Hagg
Metaheuristics for Finding Multiple Solutions, 287-315, 2021
22021
A Deep Dive Into Exploring the Preference Hypervolume
A Hagg, A Asteroth, T Bäck
International Conference on Computational Creativity, 394-397, 2020
22020
Successive evolution of charging station placement
H Spieker, A Hagg, A Asteroth, S Meilinger, V Jacobs, A Oslislo
2015 International Symposium on Innovations in Intelligent SysTems and …, 2015
22015
Artificial Intelligence in Elite Sports—A Narrative Review of Success Stories and Challenges
F Hammes, A Hagg, A Asteroth, D Link
Frontiers in sports and active living 4, 2022
2022
Discovering the preference hypervolume: an interactive model for real world computational co-creativity
A Hagg
Leiden Institute of Advanced Computer Science, Faculty of Science, Leiden …, 2021
2021
Einsatzmöglichkeiten und Transfer von Künstlicher Intelligenz im inter-nationalen Spitzensport–zwischen Small und Big Data
A Hagg, A Asteroth, M Pfeiffer, F Hammes, D Link
spinfortec 2020 digital, 26, 2020
2020
Einsatz von Künstlicher Intelligenz im internationalen Spitzensport–Eine Erhebung des Status Quo
F Hammes, D Link, M Lames, A Hagg, A Asteroth, M Pfeiffer
spinfortec 2020 digital, 28, 2020
2020
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