Department of Electrical Engineering, Mechanical Engineering and Technical Journalism

Alexander Hagg (DE)

Dr Alexander Hagg

PhD student/Retired from the Department of Computer Science on: 2020

alexander.hagg@h-brs.de

Unit

Department of Electrical Engineering, Mechanical Engineering and Technical Journalism

Research fields

  • Computer Aided Ideation, Computer Aided Intuition
  • Optimization, insb. evolutionary algorithms, quality diversity, phenotypic niching
  • Surrogatmodellierung und maschinellem Lernen, insb. Gaußprocessregression, neuronale Netze, Neuroevolution
  • Computer Vision
  • Robotics

Location

Sankt Augustin

Address

Grantham-Allee 20

53757 Sankt Augustin

Publications

  • Hagg, A., 2021. Discovering the preference hypervolume: an interactive model for real world computational co-creativity (Doctoral dissertation, Leiden University).
  • Hagg, A., 2021. Phenotypic Niching Using Quality Diversity Algorithms. In Metaheuristics for Finding Multiple Solutions (pp. 287-315). Springer, Cham.
  • Hagg, A., Preuss, M., Asteroth, A. and Bäck, T., 2020. An Analysis of Phenotypic Diversity in Multi-Solution Optimization (No. 3286). EasyChair.
  • Hagg, A., Wilde, D., Asteroth, A. and Bäck, T., 2020. Designing Air Flow with Surrogate-assisted Phenotypic Niching.
  • Asteroth, A., Hagg, A., Meng, J., Priesnitz, A., Prochnau, L. and Reith, D., 2020. AErOmAt Abschlussbericht.
  • Hagg, A., Zaefferer, M., Stork, J. and Gaier, A., 2019, July. Prediction of neural network performance by phenotypic modeling. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1576-1582).
  • Hagg, A., Asteroth, A. and Bäck, T., 2019, July. Modeling user selection in quality diversity. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 116-124).
  • Hagg, A., Asteroth, A., Bäck, T. Prototype Discovery using Quality-Diversity (PPSN 2018)
  • Hagg, A. Hierarchical Surrogate Modeling for Illumination Algorithms. (GECCO 2017).
  • Hagg, A., Mensing M., Asteroth A. Evolving Parsimonious Networks by Mixing Activation Functions. (GECCO 2017).
  • Spieker H., Hagg, A., Gaier, A., Meilinger, S., Asteroth, A. Multi-stage evolution of single-and multiobjective MCLP. (Soft Computing 2016).
  • Hagg, A., Hegger, F., Plöger, P. (2016). On Recognizing Transparent Objects in Domestic Environments Using Fusion of Multiple Sensor Modalities. (RoboCup International Symposium 2016).
  • Hagg, A., Spieker, H., Oslislo, A., Jacobs, V., Asteroth, A. and Meilinger, S., 2015. Methodische Grundlegung für eine Strategie zum sukzessiven Ausbau der Ladeinfrastruktur für Elektromobilität in Bonn und dem Rhein-Sieg-Kreis.
  • Asteroth, A., Hagg, A. How to successfully apply genetic algorithms in practice: Representation and parametrization. (INISTA 2015).
  • Spieker, H., Hagg, A., Asteroth, A., Meilinger, S., Jacobs, V., Oslislo, A. Successive evolution of charging station placement. (INISTA 2015).
  • Dwiputra, R., Füller, M., Hegger, F., Schneider, S., Hochgeschwender, N., Awaad, I., Loza, J.M.S., Ozhigov, A.Y., Biswas, S., Deshpande, N.V. and Hagg, A., The b-it-bots RoCKIn@ Work 2014 Team Description Paper.
  • Dwiputra, R., Füller, M., Hegger, F., Schneider, S., Hochgeschwender, N., Awaad, I., Loza, J.M.S., Ozhigov, A.Y., Biswas, S., Deshpande, N.V. and Hagg, A., 2014. The b-it-bots Robo-Cup@ Home 2014 Team Description Paper. Joao Pessoa, Brazil.