303 citations · 533 across the 92 of their papers we have counts for
11 papers · 1 filter
Multi-Agent Guided Policy Optimization
Yueheng Li, Guangming Xie, Zongqing Lu
Due to practical constraints such as partial observability and limited communication, Centralized Training with Decentralized Execution (CTDE) has become the dominant paradigm in c…
CORD: Generalizable Cooperation via Role Diversity
Kanefumi Matsuyama, Kefan Su, Jiangxing Wang +2
Cooperative multi-agent reinforcement learning (MARL) aims to develop agents that can collaborate effectively. However, most cooperative MARL methods overfit training agents, makin…
AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games
Kefan Su, Yusen Huo, Zhilin Zhang +5
Decision-making in large-scale games is an essential research area in artificial intelligence (AI) with significant real-world impact. However, the limited access to realistic larg…
From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities
Wanpeng Zhang, Zilong Xie, Yicheng Feng +4
Multimodal Large Language Models have made significant strides in integrating visual and textual information, yet they often struggle with effectively aligning these modalities. We…
Visual Grounding for Object-Level Generalization in Reinforcement Learning
Haobin Jiang, Zongqing Lu
Generalization is a pivotal challenge for agents following natural language instructions. To approach this goal, we leverage a vision-language model (VLM) for visual grounding and…
MTLight: Efficient Multi-Task Reinforcement Learning for Traffic Signal Control
Liwen Zhu, Peixi Peng, Zongqing Lu +1
Traffic signal control has a great impact on alleviating traffic congestion in modern cities. Deep reinforcement learning (RL) has been widely used for this task in recent years, d…
Cradle: Empowering Foundation Agents Towards General Computer Control
Weihao Tan, Wentao Zhang, Xinrun Xu +25
Despite the success in specific scenarios, existing foundation agents still struggle to generalize across various virtual scenarios, mainly due to the dramatically different encaps…
RL-GPT: Integrating Reinforcement Learning and Code-as-policy
Shaoteng Liu, Haoqi Yuan, Minda Hu +5
Large Language Models (LLMs) have demonstrated proficiency in utilizing various tools by coding, yet they face limitations in handling intricate logic and precise control. In embod…
Creative Agents: Empowering Agents with Imagination for Creative Tasks
Penglin Cai, Chi Zhang, Yuhui Fu +2
We study building embodied agents for open-ended creative tasks. While existing methods build instruction-following agents that can perform diverse open-ended tasks, none of them d…
AdaRefiner: Refining Decisions of Language Models with Adaptive Feedback
Wanpeng Zhang, Zongqing Lu
Large Language Models (LLMs) have demonstrated significant success across various domains. However, their application in complex decision-making tasks frequently necessitates intri…
Learning Attentional Communication for Multi-Agent Cooperation
Jiechuan Jiang, Zongqing Lu
Communication could potentially be an effective way for multi-agent cooperation. However, information sharing among all agents or in predefined communication architectures that exi…