Since its inception in 2016, federated learning has evolved into a highly promising decentral-
ized machine learning approach, facilitating collaborative model training across numerous …

In this paper, the problem of distributed resource allocation with coupled equality, nonlinear
inequality and convex set constraints is studied. Each agent only has access to the …

This article investigates the constrained nonsmooth distributed optimization problems
(DOPs) of general linear multiagent systems. Our problem involves the general linear …

This paper presents an adaptive backstep** approach to distributed optimization for a
class of nonlinear multi-agent systems with each agent represented by the parametric strict …

This paper investigates a distributed optimization problem based on the framework of a multi-
agent system over a directed communication network, where the global cost function is the …

This paper studies a cooperative modeling framework to reduce the complexity in deriving
the governing dynamical equations of complex systems composed of multiple bodies such …

This article investigates multicluster games (MCGs) of multiagent systems, where the players
are subject to nonlinear inequality constraints. In contrast to existing MCGs, our problem …

This paper considers distributed allocation strategies, formulated as a distributed sum-
preserving (fixed-sum) allocation of resources over a multi-agent network in the presence of …

In this brief, a surplus-based approach is proposed to solve the distributed optimal resource
allocation problem over directed graphs. Two features distinguish our method from the …

This paper presents one of the first real-life demonstrations of coordinated and distributed
resource control for secondary frequency response in a power distribution grid. A series of …