Pôle Interactions Formal Methods for Artificial Intelligence
Contact: Benedikt Bollig
The team is concerned with topics at the interface between formal methods and artificial intelligence:
- Reasoning about knowledge: We study logical formalisms that have applications in planning, synthesis, or formalizing the strategic behavior of intelligent agents (e.g., description logics, strategy logics, fuzzy logic, and dynamic logics).
- Robust and verified AI and ML: Formal methods can help in developing robust, verified, and explainable AI and machine-learning components. In particular, we exploit model learning to extract structural information from recurrent neural networks.
- Application of ML algorithms: We use machine learning to synthesize algorithms (e.g., controllers in cyber-physical systems) and for the identification of system parameters (e.g., in bio-chemical reaction networks).
Members
Permanent
Emeritus
PhD Students
Zhuofan Xu
Associated
Projects and Collaborations
- ACTER: Analyse cognitive des émotions
- DyLo-MPC: Dynamic Logics: Model Theory, Proof Theory and Computational Complexity
- ETSHI: Efficient Test Strategies for SARS-CoV-2 in Healthcare Institutions
- LeaRNNify: New Challenges for Recurrent Neural Networks and Grammatical Inference
- SINFIN: Méthodes formelles pour la modélisation, la spécification, la vérification et le développement de logiciels
- vrAI: FOrmal VeRification and AI
