On the dynamics of multi agent nonlinear filtering and learning

ABSTRACT Multiagent systems aim to accomplish highly complex learni ng tasks through decentralised consensus seeking dynamics and thei r use has garnered a great deal of attention in the signal processing a nd computational intelligence societies. This article examines the behaviour of multiagent networked systems with nonlinear filtering/l earning dynamics. To this end, a general formulation for the actions of an agent in multiagent networked systems is presented and cond itions for achieving a cohesive learning behaviour is given. Impor tantly, application of the so derived framework in distributed and f ederated learning scenarios are presented. Index T erms -- Multiagent systems, nonlinear dynamics, distributed learning, federated learning, 1. INTRODUCTION Traditionally, signal processing and learning techniques have been concerned with single agent operations [1,2].