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PhD Thesis

I'm a PhD Student from 01/10/2025 to 01/10/2028 working on Multi-Agent Reinforcement Learning and, in particular, an approach based on communication between agents. If you'd like to discuss it, I would be pleased to talk about it. Contact me through email!
Supervisor: Maxime Morge and Laetitia Matignon.
Title: Hierarchical and transferable multi-agent reinforcement learning: an approach based on communication and graph representations
Abstract: This thesis focuses on multi-agent reinforcement learning (MARL) in dynamic and partially observable environments, where decentralized coordination is essential. Traditional CTDE (Centralized Training with Decentralized Execution) approaches assume perfect communication during training, an unrealistic assumption in real systems subject to communication and resource constraints. The objective is to develop a decentralized, hierarchical, and transferable learning framework that enables agents to communicate adaptively, coordinate their behaviors despite limited observability, and transfer their skills to new tasks, agent configurations, or communication structures, with the goal of continuous learning.

I was present at ECAI 2025 for presenting VIRAL Paper in the LLAIS workshop. I had some good discussions with researchers, and I have learn many new things focusing on Large Language Model, Reinforcement Learning, and Multi-Agent Systems fields.
[ ] Todo add slides presenting interesting papers