Foundation Model-Aided Multi-Agent Reinforcement Learning for Wireless Random Access Network Optimization

arXiv:2610.07550 · cs.LG, cs.AI · Submitted 2026-10-06 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-10-06

Updated: 2026-10-06

Comments: This paper has been accepted in ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc) 2026

Project page: https://kevinliu-osu.github.io/publications/FM-DecMARL_

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Foundation Model — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes

Sources

• An Introduction to Centralized Training for Decentralized Execution in Cooperative Multi-Agent Reinforcement Learning
• Mamba: Linear-Time Sequence Modeling with Selective State Spaces
• A Wireless Foundation Model for Multi-Task Prediction

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