most citedME-IGM: Individual-Global-Max in Maximum Entropy Multi-Agent Reinforcement Learning

1 citations · 2 across the 5 of their papers we have counts for

collaborators
Showing cs.CLShow all

1 paper · 1 filter

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…