Multi-Agent Reinforcement Learning (MARL) algorithms face two main difficulties: the curse of dimensionality. and environment non-stationarity due to the independent learning processes carried out by the agents concurrently. In this paper we formalize and prove the convergence of a Distributed Round Robin Q-learning (D-RR-QL) algorithm for cooperative systems. The computational comple... https://herbsdailyes.shop/product-category/garcinia-cambogia/