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Thomas Gabor
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A simulation-based architecture for smart cyber-physical systems
T Gabor, L Belzner, M Kiermeier, MT Beck, A Neitz
2016 IEEE International Conference on Autonomic Computing (ICAC), 374-379, 2016
1922016
A hybrid solution method for the capacitated vehicle routing problem using a quantum annealer
S Feld, C Roch, T Gabor, C Seidel, F Neukart, I Galter, W Mauerer, ...
Frontiers in ICT 6, 13, 2019
622019
Software engineering for smart cyber-physical systems: Challenges and promising solutions
T Bures, D Weyns, B Schmer, E Tovar, E Boden, T Gabor, ...
ACM SIGSOFT Software Engineering Notes 42 (2), 19-24, 2017
522017
Software engineering for smart cyber-physical systems--towards a research agenda: Report on the First International Workshop on Software Engineering for Smart CPS
T Bures, D Weyns, C Berger, S Biffl, M Daun, T Gabor, D Garlan, ...
ACM SIGSOFT Software Engineering Notes 40 (6), 28-32, 2015
362015
Reasoning and learning for awareness and adaptation
M Hölzl, T Gabor
Software Engineering for Collective Autonomic Systems, 249-290, 2015
312015
Approximate approximation on a quantum annealer
I Sax, S Feld, S Zielinski, T Gabor, C Linnhoff-Popien, W Mauerer
Proceedings of the 17th ACM International Conference on Computing Frontiers …, 2020
212020
Continuous collaboration: A case study on the development of an adaptive cyber-physical system
M Hölzl, T Gabor
2015 IEEE/ACM 1st International Workshop on Software Engineering for Smart …, 2015
192015
Emergent escape-based flocking behavior using multi-agent reinforcement learning
C Hahn, T Phan, T Gabor, L Belzner, C Linnhoff-Popien
arXiv preprint arXiv:1905.04077, 2019
132019
Leveraging statistical multi-agent online planning with emergent value function approximation
T Phan, L Belzner, T Gabor, K Schmid
arXiv preprint arXiv:1804.06311, 2018
132018
The holy grail of quantum artificial intelligence: Major challenges in accelerating the machine learning pipeline
T Gabor, L Sünkel, F Ritz, T Phan, L Belzner, C Roch, S Feld, ...
Proceedings of the IEEE/ACM 42nd International Conference on Software …, 2020
122020
Optimizing evolutionary CSG tree extraction
M Friedrich, PA Fayolle, T Gabor, C Linnhoff-Popien
Proceedings of the Genetic and Evolutionary Computation Conference, 1183-1191, 2019
102019
Preparing for the unexpected: Diversity improves planning resilience in evolutionary algorithms
T Gabor, L Belzner, T Phan, K Schmid
2018 IEEE International Conference on Autonomic Computing (ICAC), 131-140, 2018
102018
Uncertainty-based out-of-distribution detection in deep reinforcement learning
A Sedlmeier, T Gabor, T Phan, L Belzner, C Linnhoff-Popien
arXiv preprint arXiv:1901.02219, 2019
92019
The scenario coevolution paradigm: Adaptive quality assurance for adaptive systems
T Gabor, A Sedlmeier, T Phan, F Ritz, M Kiermeier, L Belzner, B Kempter, ...
International Journal on Software Tools for Technology Transfer 22 (4), 457-476, 2020
82020
Adapting quality assurance to adaptive systems: the scenario coevolution paradigm
T Gabor, M Kiermeier, A Sedlmeier, B Kempter, C Klein, H Sauer, ...
International Symposium on Leveraging Applications of Formal Methods, 137-154, 2018
82018
Inheritance-based diversity measures for explicit convergence control in evolutionary algorithms
T Gabor, L Belzner, C Linnhoff-Popien
Proceedings of the Genetic and Evolutionary Computation Conference, 841-848, 2018
82018
Genealogical distance as a diversity estimate in evolutionary algorithms
T Gabor, L Belzner
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2017
82017
Software engineering for distributed autonomous real-time systems
L Belzner, MT Beck, T Gabor, H Roelle, H Sauer
Proceedings of the 2nd International Workshop on Software Engineering for …, 2016
82016
Resilient Multi-Agent Reinforcement Learning with Adversarial Value Decomposition
T Phan, L Belzner, T Gabor, A Sedlmeier, F Ritz, C Linnhoff-Popien
Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11308 …, 2021
72021
Uncertainty-based out-of-distribution classification in deep reinforcement learning
A Sedlmeier, T Gabor, T Phan, L Belzner, C Linnhoff-Popien
arXiv preprint arXiv:2001.00496, 2019
72019
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