10 citations · 30 across the 9 of their papers we have counts for
7 papers · 1 filter
A Gradient-Free Distributed Optimization Method for Convex Sum of Non-Convex Cost Functions
Yipeng Pang, Guoqiang Hu
This paper presents a special type of distributed optimization problems, where the summation of agents' local cost functions (i.e., global cost function) is convex, but each indivi…
Distributed Nash Equilibrium Seeking in N-Cluster Games with Fully Uncoordinated Constant Step-Sizes
Yipeng Pang, Guoqiang Hu
Distributed optimization and Nash equilibrium (NE) seeking problems have drawn much attention in the control community recently. This paper studies a class of non-cooperative games…
Gradient-Free Nash Equilibrium Seeking in N-Cluster Games with Uncoordinated Constant Step-Sizes
Yipeng Pang, Guoqiang Hu
This work investigates a problem of simultaneous global cost minimization and Nash equilibrium seeking, which commonly exists in -cluster non-cooperative games. Specifically, th…
Nash Equilibrium Seeking in N-Coalition Games via a Gradient-Free Method
Yipeng Pang, Guoqiang Hu
This paper studies an -coalition non-cooperative game problem, where the players in the same coalition cooperatively minimize the sum of their local cost functions under a direc…
Gradient-Free Distributed Optimization with Exact Convergence
Yipeng Pang, Guoqiang Hu
In this paper, a gradient-free distributed algorithm is introduced to solve a set constrained optimization problem under a directed communication network. Specifically, at each tim…
Distributed Nash Equilibrium Seeking with Limited Cost Function Knowledge via A Consensus-Based Gradient-Free Method
Yipeng Pang, Guoqiang Hu
This paper considers a distributed Nash equilibrium seeking problem, where the players only have partial access to other players' actions, such as their neighbors' actions. Thus, t…
Randomized Gradient-Free Distributed Online Optimization via a Dynamic Regret Analysis
Yipeng Pang, Guoqiang Hu
This work considered an online distributed optimization problem, with a group of agents whose local objective functions vary with time. Moreover, the value of the objective functio…