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).




PhD Students

Zhuofan Xu


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

Recent Publications

  • (), In , (editors), p. , , , , , , , . .
    [URL] [PDF]


If you are interested, please write an email to: bollig at lsv dot fr