5 papers
Zeroth-Order Nonsmooth Nonconvex Optimization with Convex Liftings and Its Application to State-Feedback Policy Optimization
Xuhao Wang, Yujie Tang
Direct policy optimization is widely used in reinforcement learning and control, but generally leads to nonconvex optimization problems. For state-feedback control, the…
Harnessing Individual Motivation for Collective Efficiency: A Mechanism-Driven Distributed Optimization Method
Dongwei Xie, Xuhao Wang, Yujie Tang +1
In industrial scenarios involving multi-agent collective decision-making, centralized decision-making may not be admissible due to restrictive access to individual local informatio…
Deep Reinforcement Learning for Flexible Job Shop Scheduling with Random Job Arrivals
Yu Tang, Muhammad Zakwan, Efe Balta +2
The Flexible Job Shop Scheduling Problem (FJSP) is the optimal allocation of a set of jobs to machines. Two primary challenges persist in FJSP: the unpredictable arrival of future…
Zeroth-Order Feedback Optimization in Multi-Agent Systems: Tackling Coupled Constraints
Yingpeng Duan, Yujie Tang
This paper investigates distributed zeroth-order feedback optimization in multi-agent systems with coupled constraints, where each agent operates its local action vector and observ…
Variance-Reduced Gradient Estimator for Nonconvex Zeroth-Order Distributed Optimization
Huaiyi Mu, Yujie Tang, Jie Song +1
This paper investigates distributed zeroth-order optimization for smooth nonconvex problems, targeting the trade-off between convergence rate and sampling cost per zeroth-order gra…