Raphaël Boige Phd candidate in Machine Learning RL and Game Theory @ Inria email: raphael.boige [at] inria.fr [Scholar] [Github] [Twitter]

I am a Phd candidate (expected end in 2027) at Inria. I'm mainly interested in Deep (Reinforcement) Learning, Games and Discrete Search. I am currently advised by Bruno Scherrer and Amine Boumaza, here is a fair outline of what my PhD is about.

Prior to Inria, I was a researcher for 3 years at InstaDeep. At that time, I worked on (1) diversity in deep RL agents, (2) language models as foundational models for RL and (3) language models adapted to genomics modalities.

I am also a contributor to the Jax ecosystem, I mainly participated in the projects Jumanji, QDax and pgx, and also I created a little CFR library cfrx.

I graduated from Télécom Paris and IP Paris in 2021 with a B.S. and a M. Eng in Computer Science and Applied Mathematics.

I serve as a reviewer for Neurips and RLC.

Selected Publications

• Pasta: Pretrained action-state transformer agents
  R. Boige*, Y. Flet-Berliac* A. Flajolet, L. Quaedvlieg, G. Richard, T. Pierrot (*equal contribution)
  Reinforcement Learning Conference (RLC), 2024
• Jumanji: a diverse suite of scalable reinforcement learning environments in jax
  C. Bonnet, D. Luo, D. Byrne, S. Surana, S Abramowitz, P. Duckworth, V. Coyette, L. Midgley, E. Tegegn, T. Kalloniatis, O. Mahjoub, M. Macfarlane, A. Smit, N. Grinsztajn, R. Boige, C. Waters, M. Mimouni, U. Mbou Sob, R. de Kock, S. Singh, D. Furelos-Blanco, V. Le, A. Pretorius, A.Laterre
  International Conference on Learning Representations (ICLR), 2024
• Qdax: A library for quality-diversity and population-based algorithms with hardware acceleration
  F. Chalumeau, B. Lim, R. Boige, M. Allard, L. Grillotti, M. Flageat, V. Macé, G. Richard, A. Flajolet, T. Pierrot, A. Cully
  Journal of Machine Learning Research (JMLR), 2024
• Neuroevolution is a competitive alternative to reinforcement learning for skill discovery
  F. Chalumeau*, R. Boige*, B. Lim, V. Macé, M. Allard, A. Flajolet, A. Cully, T. Pierrot (*equal contribution)
  (Spotlight - top 15%) International Conference on Learning Representations (ICLR), 2023.
• The quality-diversity transformer: Generating behavior-conditioned trajectories with decision transformers
  V. Macé, R. Boige, F. Chalumeau, T. Pierrot, G. Richard, N. Perrin-Gilbert
  Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2023
• Gradient-informed quality diversity for the illumination of discrete spaces
  R. Boige*, G.Richard*, J. Dona, T. Pierrot, A. Cully (*equal contribution)
  Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2023