31 citations · 33 across the 6 of their papers we have counts for
11 papers
Mobile Network Control with a World Model
Maxime Bouton, Ioanna Mitsioni, Simon Lindståhl +1
The increasing complexity of mobile networks necessitates intelligent and dynamic control strategies for efficient, energy-conserving management. We propose a world model-based app…
Temporally Consistent Graph Q-Networks for Intelligent Network Control
Zacharias Veiksaar, Maxime Bouton
Mobile networks continue to grow in complexity and next generation networks are expected to support both increasing traffic loads and more diverse services. As network complexity r…
Collaborative Safe Bayesian Optimization
Alina Castell Blasco, Maxime Bouton
Mobile networks require safe optimization to adapt to changing conditions in traffic demand and signal transmission quality, in addition to improving service performance metrics. W…
Coordinated Reinforcement Learning for Optimizing Mobile Networks
Maxime Bouton, Hasan Farooq, Julien Forgeat +3
Mobile networks are composed of many base stations and for each of them many parameters must be optimized to provide good services. Automatically and dynamically optimizing all the…
Reinforcement Learning with Iterative Reasoning for Merging in Dense Traffic
Maxime Bouton, Alireza Nakhaei, David Isele +2
Maneuvering in dense traffic is a challenging task for autonomous vehicles because it requires reasoning about the stochastic behaviors of many other participants. In addition, the…
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes
Maxime Bouton, Jana Tumova, Mykel J. Kochenderfer
Autonomous systems are often required to operate in partially observable environments. They must reliably execute a specified objective even with incomplete information about the s…