Publications (32)
Implementation-Based Incentive Design for Autonomous Mobility-on-Demand and Transit Systems
Xinling Li, Runyu Zhang, Gioele Zardini
Achieving a socially desirable operating point for a multimodal transportation system is challenging when Autonomous Mobility-on-Demand (AMoD) and Public Transit (PT) operators pur…
Constrained Optimization From a Control Perspective via Feedback Linearization
Runyu Zhang, Arvind Raghunathan, Jeff Shamma +1
Tools from control and dynamical systems have proven valuable for analyzing and developing optimization methods. In this paper, we establish rigorous theoretical foundations for us…
AdamFLIP: Adaptive Momentum Feedback Linearization Optimization for Hard Constrained PINN Training
Binghang Lu, Runyu Zhang, Changhong Mou +2
Physics-informed neural networks (PINNs) provide a flexible framework for solving forward and inverse problems governed by partial differential equations (PDEs), but standard PINN…
Multi-Agent Coverage Control with Transient Behavior Consideration
Runyu Zhang, Haitong Ma, Na Li
This paper studies the multi-agent coverage control (MAC) problem where agents must dynamically learn an unknown density function while performing coverage tasks. Unlike many curre…
Reconstruct the Directories for In-Memory File Systems
Runyu Zhang, Chaoshu Yang
Existing path lookup routines in file systems need to construct an auxiliary index in memory or traverse the dentries of the directory file sequentially, which brings either heavy…
Random-Subspace Sequential Quadratic Programming for Constrained Zeroth-Order Optimization
Runyu Zhang, Gioele Zardini
We study nonlinear constrained optimization problems in which only function evaluations of the objective and constraints are available. Existing zeroth-order methods rely on noisy…
Vision Technologies with Applications in Traffic Surveillance Systems: A Holistic Survey
Wei Zhou, Li Yang, Lei Zhao +5
Traffic Surveillance Systems (TSS) have become increasingly crucial in modern intelligent transportation systems, with vision technologies playing a central role for scene percepti…
Scalable Reinforcement Learning for Linear-Quadratic Control of Networks
Johan Olsson, Runyu Zhang, Emma Tegling +1
Distributed optimal control is known to be challenging and can become intractable even for linear-quadratic regulator problems. In this work, we study a special class of such probl…
Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity
Runyu Zhang, Yang Hu, Na Li
Robust Markov Decision Processes (MDPs) and risk-sensitive MDPs are both powerful tools for making decisions in the presence of uncertainties. Previous efforts have aimed to establ…
Markov Games with Decoupled Dynamics: Price of Anarchy and Sample Complexity
Runyu Zhang, Yuyang Zhang, Rohit Konda +3
This paper studies the finite-time horizon Markov games where the agents' dynamics are decoupled but the rewards can possibly be coupled across agents. The policy class is restrict…
Scalable spectral representations for multi-agent reinforcement learning in network MDPs
Zhaolin Ren, Runyu Zhang, Bo Dai +1
Network Markov Decision Processes (MDPs), a popular model for multi-agent control, pose a significant challenge to efficient learning due to the exponential growth of the global st…
Multi-Agent Reinforcement Learning with Reward Delays
Yuyang Zhang, Runyu Zhang, Yuantao Gu +1
This paper considers multi-agent reinforcement learning (MARL) where the rewards are received after delays and the delay time varies across agents and across time steps. Based on t…
Gradient play in stochastic games: stationary points, convergence, and sample complexity
Runyu Zhang, Zhaolin Ren, Na Li
We study the performance of the gradient play algorithm for stochastic games (SGs), where each agent tries to maximize its own total discounted reward by making decisions independe…
Muon-OGD: Muon-based Spectral Orthogonal Gradient Projection for LLM Continual Learning
Binghang Lu, Zheyuan Deng, Runyu Zhang +6
A central challenge in continual learning for large language models (LLMs) is catastrophic forgetting, where adapting to new tasks can substantially degrade performance on previous…
On the Relationship of Optimal State Feedback and Disturbance Response Controllers
Runyu Zhang, Yang Zheng, Weiyu Li +1
This paper studies the relationship between state feedback policies and disturbance response policies for the standard Linear Quadratic Regulator (LQR). For open-loop stable plants…
Policy Optimization for Markov Games: Unified Framework and Faster Convergence
Runyu Zhang, Qinghua Liu, Huan Wang +3
This paper studies policy optimization algorithms for multi-agent reinforcement learning. We begin by proposing an algorithm framework for two-player zero-sum Markov Games in the f…
On the Regret Analysis of Online LQR Control with Predictions
Runyu Zhang, Yingying Li, Na Li
In this paper, we study the dynamic regret of online linear quadratic regulator (LQR) control with time-varying cost functions and disturbances. We consider the case where a finite…
On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games
Runyu Zhang, Jincheng Mei, Bo Dai +2
Softmax policy gradient is a popular algorithm for policy optimization in single-agent reinforcement learning, particularly since projection is not needed for each gradient update.…
Equilibrium Selection for Multi-agent Reinforcement Learning: A Unified Framework
Runyu Zhang, Gioele Zardini, Asuman Ozdaglar +2
While multi-agent reinforcement learning (MARL) has produced numerous algorithms that converge to Nash or related equilibria, such equilibria are often non-unique and can exhibit w…
Distributed Reinforcement Learning for Decentralized Linear Quadratic Control: A Derivative-Free Policy Optimization Approach
Yingying Li, Yujie Tang, Runyu Zhang +1
This paper considers a distributed reinforcement learning problem for decentralized linear quadratic control with partial state observations and local costs. We propose a Zero-Orde…
Co-Investment with Payoff-Sharing Mechanism for Cooperative Decision-Making in Network Design Games
Mingjia He, Andrea Censi, Runyu Zhang +2
Network-based systems are inherently interconnected, with the design and performance of subnetworks being interdependent. However, the decisions of self-interested operators may le…
An Efficient and Wear-Leveling-Aware Frequent-Pattern Mining on Non-Volatile Memory
Jiaqi Dong, Runyu Zhang, Chaoshu Yang +2
Frequent-pattern mining is a common approach to reveal the valuable hidden trends behind data. However, existing frequent-pattern mining algorithms are designed for DRAM, instead o…
Cooperative Multi-Agent Graph Bandits: UCB Algorithm and Regret Analysis
Phevos Paschalidis, Runyu Zhang, Na Li
In this paper, we formulate the multi-agent graph bandit problem as a multi-agent extension of the graph bandit problem introduced by Zhang, Johansson, and Li [CISS 57, 1-6 (2023)]…
MatrAIx: Simulating the World with 8.3 Billion Persona Agents
Xiaomin Li, Yuexing Hao, Jianheng Hou +90
Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…
Optimism as Risk-Seeking in Multi-Agent Reinforcement Learning
Runyu Zhang, Na Li, Asuman Ozdaglar +2
Risk sensitivity has become a central theme in reinforcement learning (RL), where convex risk measures and robust formulations provide principled ways to model preferences beyond e…
Adaptive-Horizon Conflict-Based Search for Closed-Loop Multi-Agent Path Finding
Jiarui Li, Federico Pecora, Runyu Zhang +1
Multi-Agent Path Finding (MAPF) is a core coordination problem for large robot fleets in automated warehouses and logistics. Existing approaches are typically either open-loop plan…
Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling
Tyler Will, Runyu Zhang, Eli Sadovnik +5
We introduce a new method based on nonnegative matrix factorization, Neural NMF, for detecting latent hierarchical structure in data. Datasets with hierarchical structure arise in…
Certificate-Driven Closed-Loop Multi-Agent Path Finding with Inheritable Factorization
Jiarui Li, Runyu Zhang, Gioele Zardini
Multi-agent coordination in automated warehouses and logistics is commonly modeled as the Multi-Agent Path Finding (MAPF) problem. Closed-loop MAPF algorithms improve scalability b…
On the Optimal Control of Network LQR with Spatially-Exponential Decaying Structure
Runyu Zhang, Weiyu Li, Na Li
This paper studies network LQR problems with system matrices being spatially-exponential decaying (SED) between nodes in the network. The major objective is to study whether the op…
Three-dimensional single gyroid photonic crystals with a mid-infrared bandgap
Siying Peng, Runyu Zhang, Valerian H. Chen +3
A gyroid structure is a distinct morphology that is triply periodic and consists of minimal isosurfaces containing no straight lines. We have designed and synthesized amorphous sil…
FICO: Finite-Horizon Closed-Loop Factorization for Unified Multi-Agent Path Finding
Jiarui Li, Alessandro Zanardi, Federico Pecora +2
Multi-Agent Path Finding is a fundamental problem in robotics and AI, yet most existing formulations treat planning and execution separately and address variants of the problem in…
Zeroth-Order Constrained Optimization from a Control Perspective via Feedback Linearization
Runyu Zhang, Gioele Zardini, Asuman Ozdaglar +2
Safe derivative-free optimization under unknown constraints is a fundamental challenge in modern learning and control. Existing zeroth-order (ZO) methods typically still assume acc…