Before revision:  In this work, we investigate Multi-Agent PPO (MAPPO), a  multi-agent PPO variant which adopts a centralized value function . Using a 1-GPU desktop, we show that MAPPO achieves performance comparable to the state-of-the-art in three popular multi-agent testbeds: the Particle World environments, Starcraft II Micromanagement Tasks , and the Hanabi Challenge , with minimal hyperparameter tuning and without any domain-specific algorithmic modifications or architectures.
After revision:  In this work, we investigate Multi-Agent PPO (MAPPO), a multi-agent PPO variant which adopts a centralized value function . Using a 1-GPU desktop, we show that MAPPO achieves surprisingly strong performance in three popular multi-agent testbeds: the Particle World environments, Starcraft II Micromanagement Tasks , and the Hanabi Challenge , with minimal hyperparameter tuning and without any domain-specific algorithmic modifications or architectures.