About me
I am currently a PhD student in Computer Science at IRIT, France. My thesis focuses on theoretical and practical aspects of extracting knowledge from automated planning models, without actually solving the planning problem.
Before pursuing a PhD, I studied computer science and applied mathematics at Ecole Normale Supérieure de Rennes.
More generally, I am interested in Automated Planning, Operations Research and theoretical CS - especially Complexity Theory and Logics.
You can find a quick résumé here.
I am fond of algorithmics and programming, but I also enjoying reading and music. I have been playing the guitar (both electric and classical) for a few years. I also collect and play board games and Magic cards.
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Résumé
Education
- 2021-2024 - PhD in Computer Science
Université Toulouse III - Paul Sabatier
- 2020-2021 - Master 2 of Computer Science
ENS de Rennes
- 2019-2020 - PréLab (see research experience)
ENS de Rennes
- 2018-2019 - Master 1 of Computer Science
ENS de Rennes
- 2017-2018 - Bachelor of Computer Science
ENS de Rennes
- 2015-2017 - Preparatory program in Maths and Physics
Lycée Louis-le-Grand
Research Experience
- September 2021 - August 2024 - Extracting Knowledge from Planning Models - Theory and Practice
Prof. Martin Cooper. IRIT (Toulouse, France)
- February - July 2021 - A Compilation Map for Automated Planning Problems
Dr. Hélène Fargier, Prof. Martin Cooper. IRIT (Toulouse, France)
- February - July 2020 - Dynamic Epistemic Logic - Parameterized Complexity
Prof. Thomas Bolander. DTU (Copenhaguen, Denmark)
- September - December 2019 - Understanding Planning Width
Dr. Hector Geffner. UPF (Barcelona, Spain)
- May - July 2019 - Weak-Bisimulation Based Shrinking Strategies
Dr. Silvan Sievers. University of Basel (Switzerland)
- May - June 2018 Benchmarks for Hierarchical Planning
Prof. Damien Pellier. LIG (Grenoble, France)
Languages
- French - Mother Tongue
- English - Fluent (C1+)
English certifications
- CAE: 198/210
- TOEIC: 990/990
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Publications
Published works
- Thomas Bolander, Arnaud Lequen. Parameterized Complexity of Dynamic Belief Updates: A Complete Map. Journal of Logic and Computation, 2023. [preprint]
- Martin C. Cooper, Arnaud Lequen, Frédéric Maris. Isomorphisms Between STRIPS Problems and Sub-Problems. CP 2022. [open access]
- Thomas Bolander, Arnaud Lequen. Parametrized Complexity of Dynamic Belief Updates. In Proceedings of Dynamic Logic: New Trends and Applications (DaLí), 2020. Lecture Notes in Computer Science, vol 12569. [pdf] [slides]
Work presented in national conferences
- Arnaud Lequen. Learning Interpretable Classifiers for PDDL Planning. JIAF, 2024.
- Martin C. Cooper, Arnaud Lequen, Frédéric Maris. Analysis of planning instances without search. JIAF, 2023.
- Martin C. Cooper, Arnaud Lequen, Frédéric Maris. Isomorphismes entre instances et sous-instances de planification STRIPS. JFPC, 2022.
Nowhere-Zero Flows
Nowhere-zero flows (NZF) are related to the common notion of flows, except that they take their values in any finite abelian group. They are a generalization of the k-flow problem, as
formalized by W. Tutte with the 5-flow conjecture.
I come back to this project every now and then. I first implemented a polynomial algorithm that finds a k-flow for k > 3, through its dual problem, 4-coloration.
Later, I developped an algorithm that tries to solves the general problem when possible.
Although my works shows no novel technique, it helped me get familiar with various operations research algorithms.
A (very) quickly written report is available here.
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Parameterized Problem Solver
A simple problem in Python meant to facilitate research in parameterized complexity, by finding quickly which sub-problems of a problem with multiple parameters can have their complexity decided with a database of
known reductions, and of known tractable and intractable problems. In addition, problems whose complexity is not yet known can be found, and the impact of finding their complexity is given by the program.
This was done during my internship with Prof. Thomas Bolander, PhD, on a parameterized version of a variant of the model-checking problem for Dynamic Epistemic Logic. As such, the code comes with various examples in that domain.
The code can be found here.
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Teaching (in French)
2023-2024
- Réseaux Bayésiens et Modèles pour la Planification (M2)
- Intelligence Artificelle (L3)
2022-2023
- Réseaux Bayésiens et Modèles pour la Planification (M2)
- Algorithmique 2 - Preuve et analyse de la complexité des algorithmes (L2)
2021-2022
- Logique 1 (L1)
- Complexité des algorithmes (L2)