Research output per year
Research output per year
Project Details
Description
The project “Bilateral AI” aims at lifting artificial intelligence (AI) to the next level. Current AI systems are in a sense narrow. They center on a specific application or task such as object or speech recognition. Our project will combine two of the most important types of AI which have been developed separately so far: symbolic and sub-symbolic AI. While symbolic AI works with clearly defined logical rules, sub-symbolic AI (such as ChatGPT) is based on training a machine with the help of large datasets to create intelligent behavior. This integration, resulting in a Broad AI, is intended to mirror something that humans do naturally: the simultaneous use of cognition and reasoning skills.
| Status | Active |
|---|---|
| Effective start/end date | 01.10.2024 → 30.09.2029 |
Collaborative partners
- Johannes Kepler University Linz (lead)
- IST Institute of Science and Technology Austria (Project partner)
- Graz University of Technology (Project partner)
- Vienna University of Economics and Business (Project partner)
- University of Klagenfurt (Project partner)
- Vienna University of Technology (Project partner)
Fields of science
- 101013 Mathematical logic
- 603109 Logic
- 102 Computer Sciences
- 102031 Theoretical computer science
- 102030 Semantic technologies
- 102011 Formal languages
- 102022 Software development
- 102001 Artificial intelligence
- 101019 Stochastics
- 103029 Statistical physics
- 101018 Statistics
- 101017 Game theory
- 101016 Optimisation
- 202017 Embedded systems
- 101015 Operations research
- 101014 Numerical mathematics
- 101029 Mathematical statistics
- 101028 Mathematical modelling
- 101026 Time series analysis
- 101024 Probability theory
- 102025 Distributed systems
- 202037 Signal processing
- 202036 Sensor systems
- 202035 Robotics
- 102003 Image processing
- 102006 Computer supported cooperative work (CSCW)
- 102032 Computational intelligence
- 102004 Bioinformatics
- 101027 Dynamical systems
- 102013 Human-computer interaction
- 305907 Medical statistics
- 202002 Audiovisual media
- 101004 Biomathematics
- 502007 E-commerce
- 305905 Medical informatics
- 505002 Data protection
- 101031 Approximation theory
- 102010 Database systems
- 102035 Data science
- 102033 Data mining
- 506002 E-government
- 305901 Computer-aided diagnosis and therapy
- 102019 Machine learning
- 106007 Biostatistics
- 102018 Artificial neural networks
- 106005 Bioinformatics
- 102028 Knowledge engineering
- 202007 Computer integrated manufacturing (CIM)
- 102016 IT security
- 102015 Information systems
- 509018 Knowledge management
- 102014 Information design
- 202006 Computer hardware
JKU Focus areas
- Digital Transformation
- Sustainable Development: Responsible Technologies and Management
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Active Automata Learning with Noisy Data: From Big to Small Data
Wallner, F., Aichernig, B., von Berg, B. & Rindler, M., May 2026, Formal Methods: 27th International Symposium, FM 2026, Tokyo, Japan, May 18–22, 2026, Proceedings, Part II. Sampaio, A. & Stoelinga, M. (eds.). 1 ed. Springer Nature, p. 326-346 21 p. (Lecture Notes in Computer Science (LNCS); vol. 16557).Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review
Open Access -
Antic: Adaptive Neural Temporal In-situ Compressor
Cranganore, S. S., Bodnar, A., Galleti, G., Paischer, F. & Brandstetter, J., 10 Apr 2026, arXiv, 31 p. (arXiv.org; no. 2604.09543).Research output: Working paper and reports › Preprint
Open Access -
Automata Learning Versus Process Mining: The Case for User Journeys
Kobialka, P., Pferscher, A., Aichernig, B., Johnsen, E. B. & Tapia Tarifa, S. L., 03 Apr 2026, In: IEEE Transactions on Software Engingeering. 52, 6, p. 1858-1874 17 p.Research output: Contribution to journal › Article › peer-review
Activities
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Avoiding Big Integers: Parallel Multimodular Algebraic Verification of Arithmetic Circuits
Hofstadler, C. (Speaker)
29 Jul 2026Activity: Talk or presentation › Contributed talk › science-to-science
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Automata Learning and Testing with AALpy
Aichernig, B. (Speaker)
15 May 2026Activity: Talk or presentation › Invited talk › science-to-science
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Vertrauen ist gut, Kontrolle ist besser! Künstliche Intelligenz auf dem Prüfstand.
Aichernig, B. (Speaker)
21 Mar 2026Activity: Talk or presentation › Invited talk › science-to-public
Datasets
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QRP+Gen: Checking Q-Resolution Proofs with Generalized Axioms
Peyrer, M. (Creator) & Seidl, M. (Creator), Zenodo, 22 Jul 2025
DOI: 10.5281/zenodo.16307432, https://zenodo.org/records/16307432
Dataset