Collaborative multiagent Gaussian inference in a dynamic environment using belief propagation

Stefano Ermon, Carla P. Gomes, Bart Selman

Abstract: The problem of multiagent Gaussian inference in a dynamic environment, also known as distributed Kalman filtering, is formulated into the framework of message passing algorithms. Upon generalizing the derivation of the standard Kalman filter to the distributed case, we propose novel solutions that outperform current state of the art techniques.