Connectivity-Influence Weighting: A Structural Bias for Graph-Based MARL
Graph neural networks used for multi-agent reinforcement learning typically treat every edge of the communication graph as equally important. This paper introduces …

I am a Ph.D. student in Artificial Intelligence at Ai Movement, the International Artificial Intelligence Center of Morocco at UM6P. My research interests are multi-agent reinforcement learning, graph-based communication between agents, and heterogeneous swarm coordination — in particular how structural priors over an agent’s communication graph can make coordination scale under partial observability.
Before starting the Ph.D. I graduated from the School of Information Sciences (ESI) as a Data and Knowledge engineer, and worked on applied computer vision and conversational AI.
Graph neural networks used for multi-agent reinforcement learning typically treat every edge of the communication graph as equally important. This paper introduces …
A UAV acts as an aerial shepherd guiding a ground vehicle that leads a UGV swarm, while the UGVs autonomously select local leaders to improve cohesion and reduce communication …