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Much work has been dedicated to the exploration of Multi-Agent ReinforcementLearning (MARL) paradigms implementing a centralized learning withdecentralized execution (CLDE) approach to achieve human-like collaboration incooperative tasks. Here, we discuss variations of centralized training anddescribe a recent survey of algorithmic approaches. The goal is to explore howdifferent implementations of information sharing mechanism in centralizedlearning may give rise to distinct group coordinated behaviors in multi-agentsystems performing cooperative tasks.

Survey of Recent Multi-Agent Reinforcement Learning Algorithms Utilizing Centralized Training