— This paper studies consensus seeking over noisy networks with time-varying noise statistics. Stochastic approximation type algorithms can ensure consensus in mean square and wi...
We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...
Abstract. Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value funct...
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
— In this paper, we consider the time-slotted ALOHA packetized multiple-access system where the transmission channels obey i.i.d (independent identically distributed) Rayleigh fa...