Pôle Interactions Formal Methods for Artificial Intelligence
Contact: Benedikt Bollig
Topics
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 develop 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 to identify system parameters (e.g., in bio-chemical reaction networks).
News
Stéphane Demri (LMF, CNRS) and Karin Quaas (Leipzig University) won the Best-Paper Award at JELIA 2023 for their article First Steps Towards Taming Description Logics with Strings.
Working Group
We regularly welcome speakers to talk about AI-related topics. Usually, talks take place on Friday at 11 am and are transmitted via Zoom.
Upcoming Talk
- Programmatic Reinforcement Learning: why and how?
Roman Kniazev (LaBRI, Université de Bordeaux)
Friday, 24th January 2025, 11:00 (1Z71)
Abstract:
Reinforcement Learning has achieved remarkable success in the past decade, employing deep neural networks to represent policies. However, the interpretational opaqueness of these networks poses a challenge, making it difficult to comprehend and reason with the policies they generate. In response to this growing demand for interpretability and verifiability, the field of Programmatic Reinforcement Learning has emerged. The objective of this field is to learn policies in the form of programs.
In this talk, I will provide an overview of the existing approaches to using programs as policies. In particular, I will focus on our rapid Jax-based implementation of a recently proposed algorithm for learning oblique decision trees, a machine learning model that stands out by being simultaneously a simple if-then-else program.
Recent Talks
- How to manage a budget with ATL+
Stéphane Demri (LMF, CNRS)
Friday, 25th October 2024, 11:00 (room 1Z61)
Paper available at: https://proceedings.kr.org/2023/19/ - Statistical Language Modeling: From N-grams to Transformers
Gustave Cortal (LMF)
Friday, 31st May 2024, 11:00 (room 1Z18)
Recorded talk: https://www.youtube.com/watch?v=PenKM-gZX_4
Slides: https://gustavecortal.com/data/Gustave_Cortal_Tutorial_on_Language_Models.pdf - First Steps Towards Taming Description Logics with Strings
Stéphane Demri (LMF, CNRS)
Friday, 26th January 2024, 11:00 (room 1Z71)
Paper available at: https://hal.science/hal-04212642 - An approach for inferring geometric expressions in topology-based modeling
Romain Pascual (MICS, CentraleSupélec, Université Paris-Saclay)
Friday, 6th October 2023, 11:00 (room 1Z56)
Slides: https://romainpascual.fr/talk/fmai2023/FMAI2023_slides.pdf - Updating Knowing How
Raul Fervari (Universidad Nacional de Córdoba / CONICET; Guangdong Technion - Israel Institute of Technology)
Friday, 29th September 2023, 11:00 (room 1Z56)
Slides: https://cs.famaf.unc.edu.ar/~rfervari/files/talks/2023-lmf.pdf - Autonomous systems in the intersection of formal methods, learning, and control
Ufuk Topcu (The University of Texas at Austin)
Friday, 23rd June 2023, 14:00 (room 1Z18) - Towards the Formal Verification of Neural Networks in Isabelle/HOL
Achim Brucker (Chair of Cybersecurity, University of Exeter, UK)
Friday, 26th May 2023, 11:00 (room 1Z56)
Publications
A list of AI-related publications by LMF members can be found at the following link: https://hal.science/LMF-AI
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
- SAIF: [S]afe [AI] through [F]ormal Methods
- SINFIN: Méthodes formelles pour la modélisation, la spécification, la vérification et le développement de logiciels
Members
Permanent
Emeritus
PhD Students
Associated
Zhuofan Xu