Record link: 
http://hdl.handle.net/20.500.12708/231950
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Title: 
ATLAS: Discovering Agent Strategies through LLM-Guided Abstraction and Automata Learning
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Citation: 
Lopez-Miguel, I. D., Happe, A., Cito, J., Bartocci, E., Könighofer, B., & Tappler, M. (2026). ATLAS: Discovering Agent Strategies through LLM-Guided Abstraction and Automata Learning. In MODELS ’26: Proceedings of the ACM/IEEE 29th International Conference on Model Driven Engineering Languages and Systems (pp. 463–469). Association for Computing Machinery. https://doi.org/10.1145/3822455.3838777
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Publisher DOI: 
10.1145/3822455.3838777
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Lopez-Miguel, Ignacio D. 
Happe, Andreas 
Cito, Jürgen 
Bartocci, Ezio 
Könighofer, Bettina 
Tappler, Martin 
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Organisational Unit: 
E191-01 - Forschungsbereich Cyber-Physical Systems 
E194-01 - Forschungsbereich Software Engineering 
E192-04 - Forschungsbereich Formal Methods in Systems Engineering 
E056-13 - Fachbereich LogiCS 
E056-17 - Fachbereich Trustworthy Autonomous Cyber-Physical Systems 
E056-26 - Fachbereich Automated Reasoning 
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Published in: 
MODELS '26: Proceedings of the ACM/IEEE 29th International Conference on Model Driven Engineering Languages and Systems 
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ISBN: 
979-8-4007-2809-9
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Date (published): 
3-Oct-2026
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Event name: 
29th International ACM/IEEE Conference on Model Driven Engineering Languages and Systems (MODELS 2026) 
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Event date: 
4-Oct-2026 - 9-Oct-2026
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Event place: 
Málaga, Spain
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Number of Pages: 
7
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Publisher: 
Association for Computing Machinery, New York
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Peer reviewed: 
Yes
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Keywords: 
AgenticAI; Automata Learning; Knowledge Transfer
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Project title: 
RobustifAI: Robustifying Generative AI through Human-Centric Integration of Neural and Symbolic Methods: 101212818 (European Commission) 
Neuro-symbolic Ethical Safe Traffic: 936797 (FFG - Österr. Forschungsförderungs- gesellschaft mbH) 
Training and Guiding AI Agents with Ethical Rules: ICT22-023 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds) 
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Research Areas: 
Computer Engineering and Software-Intensive Systems: 100%
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Science Branch: 
1020 - Informatik: 100%
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Appears in Collections:
Conference Paper

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