A message passing approach to multiagent gaussian inference for dynamic processes
Stefano Ermon, Carla Pedro Gomes, Bart Selman · 2011
In [1], we introduced a novel distributed inference algorithm for the multiagent Gaussian inference problem, based on the framework of graphical models and message passing algorithms. We compare it to current state of the art techniques and we demonstrate that it is the most efficient one in terms of communication resources used. Moreover, we show experimentally that it outperforms the other methods in terms of estimation error on a general class of problems, even in presence of data loss. Categories and Subject Descriptors