From 0817c7e2b0f0b49ea605e29fb8bc43243657b69c Mon Sep 17 00:00:00 2001 From: huangshiyu Date: Tue, 26 Mar 2024 19:48:43 +0800 Subject: [PATCH] update --- Project.md | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/Project.md b/Project.md index ffdd5d9..7dc12f6 100644 --- a/Project.md +++ b/Project.md @@ -5,14 +5,16 @@ If you use OpenRL in your research projects, feel free to tell us about it and j ### 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. +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. - Paper: [MQE: Unleashing the Power of Interaction with Multi-agent Quadruped Environment](https://arxiv.org/abs/2403.16015) - Authors: Ziyan Xiong, Bo Chen, Shiyu Huang, Wei-Wei Tu, Zhaofeng He, Yang Gao +- Main Page: https://ziyanx02.github.io/multiagent-quadruped-environment/ +- Github: https://github.com/ziyanx02/multiagent-quadruped-environment ### LLMArena -Description: LLMArena is a novel and easily extensible framework for evaluating the diverse capabilities of LLM in multi-agent dynamic environments. +Description: LLMArena is a novel and easily extensible framework for evaluating the diverse capabilities of LLM in multi-agent dynamic environments. - Paper: [LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments](https://arxiv.org/abs/2402.16499) - Authors: Junzhe Chen, Xuming Hu, Shuodi Liu, Shiyu Huang, Wei-Wei Tu, Zhaofeng He, Lijie Wen @@ -34,5 +36,6 @@ Experimental results show that our method efficiently finds diverse strategies i - Paper: [DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization](https://arxiv.org/abs/2207.05631)(AAAI 2024) - Authors: Wenze Chen, Shiyu Huang, Yuan Chiang, Tim Pearce, Wei-Wei Tu, Ting Chen, Jun Zhu +- Github: https://github.com/OpenRL-Lab/DGPO