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Project

Here is a list of research projects that use OpenRL. If you use OpenRL in your research projects, feel free to tell us about it and join the list.

MQE

Description: The Multi-agent Quadruped Environment (MQE) is a novel platform designed to facilitate the development and evaluation of multi-agent reinforcement learning (MARL) algorithms in realistic and dynamic scenarios.

LLMArena

Description: LLMArena is a novel and easily extensible framework for evaluating the diverse capabilities of LLM in multi-agent dynamic environments.

TiZero

Description: TiZero is a reinforcement learning agent for Google Research Football full game, trained with distributed self-play.

DGPO

Description: Recent algorithms designed for reinforcement learning tasks focus on finding a single optimal solution. However, in many practical applications, it is important to develop reasonable agents with diverse strategies. In this paper, we propose an on-policy framework for discovering multiple strategies for the same task. Experimental results show that our method efficiently finds diverse strategies in a wide variety of reinforcement learning tasks.