Multi-Agent Reinforcement Learning via Distributed MPC as a Function Approximator

Samuel Mallick, Filippo Airaldi, Azita Dabiri +1

This paper presents a novel approach to multi-agent reinforcement learning (RL) for linear systems with convex polytopic constraints. Existing work on RL has demonstrated the use o…