In this article, we consider decentralized optimization problems where agents have individual cost functions to minimize subject to subspace constraints that require the minimizers across the network to lie in low-dimensional subspaces. This constrained fo ...
Electric vehicle charging facilities offer their capacity constrained electric charge and parking to users for a fee. As electric vehicle adoption grows, so too does the potential for excessive resource utilization. In this paper, we study how prices set b ...
This work proposes a decentralized architecture, where individual agents aim at solving a classification problem while observing streaming features of different dimensions and arising from possibly different distributions. In the context of social learning ...
Modern digital connectivity has necessitated the creation of robust methods for securely storing and transferring data. At the heart of all security infrastructure is the random number generator (RNG). While random numbers find use in a variety of applicat ...
Vision-based drone swarms have recently emerged as a promising alternative to address the fault-tolerance and flexibility limitations of centralized and communication-based aerial collective systems. Although most vision-based control algorithms rely on th ...
In this paper, we introduce a new class of potential fields, i.e., meta navigation functions (MNFs) to coordinate multi-agent systems. Thanks to the MNF formulation, agents can contribute to each other's coordination via partial and/or total associations, ...
We consider the problem of making a multi-agent system (MAS) resilient to Byzantine failures through replication. We consider a very general model of MAS, where randomness can be involved in the behavior of each agent. We propose the first universal scheme ...
A plethora of real world problems consist of a number of agents that interact, learn, cooperate, coordinate, and compete with others in ever more complex environments. Examples include autonomous vehicles, robotic agents, intelligent infrastructure, IoT de ...
Aerial robot swarms have the potential to perform time-critical and dangerous tasks such as disaster response without compromising human safety. However, their reliance on external infrastructure such as global positioning for localization and wireless net ...
Today, automatic control is integrated into a wide spectrum of real-world systems such as electrical grids and transportation networks. Many of these systems comprise numerous interconnected agents, perform safety-critical operations, or generate large amo ...
An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...
