8 citations · 16 across the 8 of their papers we have counts for
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cs.AI2024
A Survey on Self-play Methods in Reinforcement Learning
Ruize Zhang, Zelai Xu, Chengdong Ma +8
Self-play, a learning paradigm where agents iteratively refine their policies by interacting with historical or concurrent versions of themselves or other evolving agents, has show…
cs.RO2024★ 1 cited
MQE: Unleashing the Power of Interaction with Multi-agent Quadruped Environment
Ziyan Xiong, Bo Chen, Shiyu Huang +3
The advent of deep reinforcement learning (DRL) has significantly advanced the field of robotics, particularly in the control and coordination of quadruped robots. However, the com…
cs.CL2024
LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments
Junzhe Chen, Xuming Hu, Shuodi Liu +4
Recent advancements in large language models (LLMs) have revealed their potential for achieving autonomous agents possessing human-level intelligence. However, existing benchmarks…