Yoann Poupart

I had the occasion to present this work at #EGC2025 during the Explain'AI Workshop.

Always very happy to receive any kind of feedback!🙏

My PhD TL;DR> A short-story about why I decided to do a PhD on the subject of explainable multi-agent reinforcement learning. I detail how I weighted this decision and how I created my proposal. I also try t...

🚀In this SOTA review, I present lines of work to democratise interpretability in MADRL. A necessary step as larger and larger pretrained agent systems are rising.

This also sets the direction of my PhD.

yp-edu.github.io/stories/my-phd

Perspectives for Direct Interpretability in Multi-Agent Deep Reinforcement Learning TL;DR> By addressing Multi-Agent Deep Reinforcement Learning interpretability, we propose directions aiming to advance active topics such as team identification, swarm coordination and sample efficien...

🤔What role can interpretability play in Multi-Agent Deep Reinforcement Learning?

MADRL challenges, ranging from agent control, state analysis or team identification, might be answered by direct interpretability.

yp-edu.github.io/publications...