International Center for Computational Logic
From International Center for Computational Logic
International Center for Computational Logic
The International Center for Computational Logic (ICCL) is an interdisciplinary center of competence in research and teaching in the field of Computational Logic, with special emphasis on Algebra, Knowledge Representation, Logic, and Formal Methods in Computer Science. It has been founded at TU Dresden in October 2003. The following research groups are associated with ICCL:
- Algebra and Discrete Structures
- Algebraic and Logical Foundations of Computer Science
- Automata Theory
- Computational Logic
- Knowledge-aware Artificial Intelligence
- Logic Programming and Argumentation
- Knowledge-Based Systems
Members and Guests
Newest Publications
Alex Ivliev, Markus Krötzsch, Maximilian Marx
SPARQLing Datalog for Rule-Based Reasoning over Large Knowledge Graphs
In Maribel Acosta, Marieke van Erp, Sebastian Rudolph, Olaf Hartig, Blerina Spahiu, Anisa Rula, Daniel Garijo, Francesco Osborne, eds., Semantic Web - 23rd International Conference, ESWC 2026, Dubrovnik, Croatia, May 10 - 14, 2026, Proceedings, Lecture Notes in Computer Science, to appear. Springer
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Nils Küchenmeister, Alex Ivliev, Markus Krötzsch
Towards Mass Spectrum Analysis with ASP
Theory and Practice of Logic Programming, 1-23, February 2026
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Manuel Bodirsky, Simon Knäuer, Sebastian Rudolph
Datalog-Expressibility for Monadic and Guarded Second-Order Logic
ACM Transactions on Computational Logic, 27(2):1-42, 2026
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Piotr Gorczyca, Hannes Straß
Non-Monotonic S4F Standpoint Logic
Proceedings of the 40th Annual AAAI Conference on Artificial Intelligence (AAAI-26), January 2026
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NEWS
January 13, 2026Tim Lyon has joined the editorial board of the Bulletin of the Section of Logic
November 27, 2025Best demo award for GPTKB at ISWC
October 23, 2025Dörthe Arndt wins Rule Challenge Best Paper Award at RuleML+RR 2025
September 30, 2025Filippo De Bortoli wins Best Student Paper Award at FroCoS 2025
January 20, 2025ICCL Researchers Contribute to Lean Standard Library
... further results
