— This paper presents a novel distributed estimation algorithm based on the concept of moving horizon estimation. Under weak observability conditions we prove convergence of the ...
Abstract. We present a method for estimating unknown geometric entities based on identical, incident, parallel or orthogonal observed entities. These entities can be points and lin...
We model reinforcement learning as the problem of learning to control a Partially Observable Markov Decision Process ( ¢¡¤£¦¥§ ), and focus on gradient ascent approache...
This study observed the challenges of taking an existing facility's inpatient volumes and procedures and projecting them into a replacement facility with differently sized un...
Marshall Ashby, David M. Ferrin, Martin J. Miller,...
We develop a hierarchical approach to planning for partially observable Markov decision processes (POMDPs) in which a policy is represented as a hierarchical finite-state control...