This paper surveys recent advances related to adaptation, learning, and optimization over
networks. Various distributed strategies are discussed that enable a collection of networked …

This article reviews significant advances in networked signal and information processing
(SIP), which have enabled in the last 25 years extending decision making and inference …

This work deals with the topic of information processing over graphs. The presentation is
largely self-contained and covers results that relate to the analysis and design of multi-agent …

Nature provides splendid examples of real-time learning and adaptation behavior that
emerges from highly localized interactions among agents of limited capabilities. For …

Adaptive networks are well-suited to perform decentralized information processing and
optimization tasks and to model various types of self-organized and complex behavior …

This paper develops a distributed optimization strategy with guaranteed exact convergence
for a broad class of left-stochastic combination policies. The resulting exact diffusion strategy …

Adaptive networks are suitable for decentralized inference tasks. Recent works have
intensively studied distributed optimization problems in the case where the nodes have to …

The diffusion LMS algorithm has been extensively studied in recent years. This efficient
strategy allows to address distributed optimization problems over networks in the case …

This paper proposes a multiagent-based optimal microgrid control scheme using a fully
distributed diffusion strategy. A two-level cooperative optimization multiagent system is …

We study the consensus decentralized optimization problem where the objective function is
the average of agents private non-convex cost functions; moreover, the agents can only …