29 citations · 76 across the 28 of their papers we have counts for
29 papers
Differentiable Adaptive Kalman Filtering via Optimal Transport
Yangguang He, Wenhao Li, Minzhe Li +3
Learning-based filtering has demonstrated strong performance in non-linear dynamical systems, particularly when the statistics of noise are unknown. However, in real-world deployme…
Optimization Problem Solving Can Transition to Evolutionary Agentic Workflows
Wenhao Li, Bo Jin, Mingyi Hong +2
This position paper argues that optimization problem solving can transition from expert-dependent to evolutionary agentic workflows. Traditional optimization practices rely on huma…
A Survey of Automatic Prompt Engineering: An Optimization Perspective
Wenwu Li, Xiangfeng Wang, Wenhao Li +1
The rise of foundation models has shifted focus from resource-intensive fine-tuning to prompt engineering, a paradigm that steers model behavior through input design rather than we…
Generative Multi-Agent Collaboration in Embodied AI: A Systematic Review
Di Wu, Xian Wei, Guang Chen +4
Embodied multi-agent systems (EMAS) have attracted growing attention for their potential to address complex, real-world challenges in areas such as logistics and robotics. Recent a…
SkyRover: A Modular Simulator for Cross-Domain Pathfinding
Wenhui Ma, Wenhao Li, Bo Jin +2
Unmanned Aerial Vehicles (UAVs) and Automated Guided Vehicles (AGVs) increasingly collaborate in logistics, surveillance, inspection tasks and etc. However, existing simulators oft…
TrackDiffuser: Nearly Model-Free Bayesian Filtering with Diffusion Model
Yangguang He, Wenhao Li, Minzhe Li +3
State estimation remains a fundamental challenge across numerous domains, from autonomous driving, aircraft tracking to quantum system control. Although Bayesian filtering has been…
Verbalized Bayesian Persuasion
Wenhao Li, Yue Lin, Xiangfeng Wang +3
Information design (ID) explores how a sender influence the optimal behavior of receivers to achieve specific objectives. While ID originates from everyday human communication, exi…
GraphThought: Graph Combinatorial Optimization with Thought Generation
Zixiao Huang, Lifeng Guo, Wenhao Li +6
Graph combinatorial optimization (GCO) problems are central to domains like logistics and bioinformatics. While traditional solvers dominate, large language models (LLMs) offer new…
FPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework
Yuchen He, Chuyun Shen, Xiangfeng Wang +1
Federated continual learning (FCL) aims to learn from sequential data stream in the decentralized federated learning setting, while simultaneously mitigating the catastrophic forge…
Complementary Information Mutual Learning for Multimodality Medical Image Segmentation
Chuyun Shen, Wenhao Li, Haoqing Chen +5
Radiologists must utilize multiple modal images for tumor segmentation and diagnosis due to the limitations of medical imaging and the diversity of tumor signals. This leads to the…
Can language agents be alternatives to PPO? A Preliminary Empirical Study On OpenAI Gym
Junjie Sheng, Zixiao Huang, Chuyun Shen +5
The formidable capacity for zero- or few-shot decision-making in language agents encourages us to pose a compelling question: Can language agents be alternatives to PPO agents in t…
Negotiated Reasoning: On Provably Addressing Relative Over-Generalization
Junjie Sheng, Wenhao Li, Bo Jin +3
Over-generalization is a thorny issue in cognitive science, where people may become overly cautious due to past experiences. Agents in multi-agent reinforcement learning (MARL) als…
Semantically Aligned Task Decomposition in Multi-Agent Reinforcement Learning
Wenhao Li, Dan Qiao, Baoxiang Wang +3
The difficulty of appropriately assigning credit is particularly heightened in cooperative MARL with sparse reward, due to the concurrent time and structural scales involved. Autom…
LOPT: Learning Optimal Pigovian Tax in Sequential Social Dilemmas
Yun Hua, Shang Gao, Wenhao Li +5
In multi-agent reinforcement learning, each agent acts to maximize its individual accumulated rewards. Nevertheless, individual accumulated rewards could not fully reflect how othe…
Boundary-aware Supervoxel-level Iteratively Refined Interactive 3D Image Segmentation with Multi-agent Reinforcement Learning
Chaofan Ma, Qisen Xu, Xiangfeng Wang +4
Interactive segmentation has recently been explored to effectively and efficiently harvest high-quality segmentation masks by iteratively incorporating user hints. While iterative…
Learning Roles with Emergent Social Value Orientations
Wenhao Li, Xiangfeng Wang, Bo Jin +2
Social dilemmas can be considered situations where individual rationality leads to collective irrationality. The multi-agent reinforcement learning community has leveraged ideas fr…
ReAssigner: A Plug-and-Play Virtual Machine Scheduling Intensifier for Heterogeneous Requests
Haochuan Cui, Junjie Sheng, Bo Jin +5
With the rapid development of cloud computing, virtual machine scheduling has become one of the most important but challenging issues for the cloud computing community, especially…
Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning
Junjie Sheng, Lu Wang, Fangkai Yang +9
Oversubscription is a common practice for improving cloud resource utilization. It allows the cloud service provider to sell more resources than the physical limit, assuming not al…
Multi-Agent Path Finding with Prioritized Communication Learning
Wenhao Li, Hongjun Chen, Bo Jin +3
Multi-agent pathfinding (MAPF) has been widely used to solve large-scale real-world problems, e.g., automation warehouses. The learning-based, fully decentralized framework has bee…
Obtaining Dyadic Fairness by Optimal Transport
Moyi Yang, Junjie Sheng, Xiangfeng Wang +4
Fairness has been taken as a critical metric in machine learning models, which is considered as an important component of trustworthy machine learning. In this paper, we focus on o…
VMAgent: Scheduling Simulator for Reinforcement Learning
Junjie Sheng, Shengliang Cai, Haochuan Cui +9
A novel simulator called VMAgent is introduced to help RL researchers better explore new methods, especially for virtual machine scheduling. VMAgent is inspired by practical virtua…
Interactive Medical Image Segmentation with Self-Adaptive Confidence Calibration
Wenhao Li, Qisen Xu, Chuyun Shen +5
Medical image segmentation is one of the fundamental problems for artificial intelligence-based clinical decision systems. Current automatic medical image segmentation methods are…
Structured Diversification Emergence via Reinforced Organization Control and Hierarchical Consensus Learning
Wenhao Li, Xiangfeng Wang, Bo Jin +3
When solving a complex task, humans will spontaneously form teams and to complete different parts of the whole task, respectively. Meanwhile, the cooperation between teammates will…
Dealing with Non-Stationarity in MARL via Trust-Region Decomposition
Wenhao Li, Xiangfeng Wang, Bo Jin +2
Non-stationarity is one thorny issue in cooperative multi-agent reinforcement learning (MARL). One of the reasons is the policy changes of agents during the learning process. Some…