Interacting Particle Systems on Networks: joint inference of the network and the interaction kernel

Modeling multi-agent systems on networks is a fundamental challenge in a wide variety of disciplines. We jointly infer the weight matrix of the network and the interaction kernel, which determine respectively which agents interact with which others and the rules of such interactions from data consisting of multiple trajectories. The estimator we propose leads naturally to a non-convex optimization problem, and we investigate two approaches for its solution: one is based on the alternating least squares (ALS) algorithm; another is …

agent agents challenge cs.lg data inference interactions kernel math.ds math.st matrix modeling multi-agent network networks rules stat.ml stat.th systems weight matrix