I try to organise personal news by theme so it’s easier to walk through. Better organisation suggestions are always welcome (and might even be necessary) !

Papers and Publications

Papers from my PhD work - this is mostly around Algorithmic Game Theory (Nash Equilibrium Computatation) and MARL for the moment.

Multi-Adversarial Team Games

Multi-Adversarial Team Gamea model the team vs. independent adversary dynamic that is central to APE. We model this first as a normal form game, where we show that equilibria in this game are poly-time approximable.

  • (Paper, AAMAS 2026) Our paper on Multi-Adversarial Team Games has been accepted to AAMAS 2026 ! The algorithm is also provided as an implementation here: Code. See all of you in Cyprus this May !
  • (Workshop, Mannheim) Presented a poster and attended the Workshop on Reinforcement Learning at Mannheim, this 7th February, 2025.

Anti-Poaching Environment

This is the body of work we produced on modelling Anti-Poaching as a partially observable stochastic game. This is the first environment in this space with a theoretical model and a reference implementation (Code: APE)

  • (JFSMA 2024)(Paper) I’ll be presenting our work at the 32nd (-ième?) Journées Francophones sur les Systèmes Multi-Agents at Cargèse, Corsica this year. Find me there between 5-9 November !
  • (EWRL 2024)(Paper) Presenting a poster at the 17th European Workshop on Reinforcement Learning, held at Toulouse this year!
  • (WLiG 2024)(Paper) Attended the Workshop on Learning in Games held at the IMT, Toulouse, and presented a poster.
  • (ROADEF 2024)(Paper) Presented the Anti-Poaching Game at ROADEF 2024, held in Amiens.

Teaching

In addition to my PhD work, I also teach at the University of Toulouse. This is usually a 12-hour primer on Deep Learning for the students of the MSE Master.

  • (Teaching, Deep Learning) Really enjoyed teaching the students of the MSE Master this year as well ! Merry Christmas, everyone :)
  • (Math Festival, Les Maths en Scène) Had the pleasure to animate an atelier on the Nash Equilibrium for schoolchildren this year. Huge thanks to Les Maths En Scène and everyone for the opportunity, and also for guiding me throughout !
  • (Teaching, Deep Learning) I’ve had the pleasure to give a short introductory course on Deep Learning to the students of the MSE Master at the University of Toulouse III :)