49 citations · 83 across the 8 of their papers we have counts for
5 papers · 1 filter
Experience Transfer for Multimodal LLM Agents in Minecraft Game
Chenghao Li, Jun Liu, Songbo Zhang +7
Multimodal LLM agents operating in complex game environments must continually reuse past experience to solve new tasks efficiently. In this work, we propose Echo, a transfer-orient…
Efficient and Interpretable Multi-Agent LLM Routing via Ant Colony Optimization
Xudong Wang, Chaoning Zhang, Jiaquan Zhang +8
Large Language Model (LLM)-driven Multi-Agent Systems (MAS) have demonstrated strong capability in complex reasoning and tool use, and heterogeneous agent pools further broaden the…
Continual Knowledge Adaptation for Reinforcement Learning
Jinwu Hu, Zihao Lian, Zhiquan Wen +5
Reinforcement Learning enables agents to learn optimal behaviors through interactions with environments. However, real-world environments are typically non-stationary, requiring ag…
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning
Yiqin Yang, Xiaoteng Ma, Chenghao Li +5
Learning from datasets without interaction with environments (Offline Learning) is an essential step to apply Reinforcement Learning (RL) algorithms in real-world scenarios. Howeve…
SOAC: The Soft Option Actor-Critic Architecture
Chenghao Li, Xiaoteng Ma, Chongjie Zhang +3
The option framework has shown great promise by automatically extracting temporally-extended sub-tasks from a long-horizon task. Methods have been proposed for concurrently learnin…