In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...
Abstract—This paper considers maximizing throughput utility in a multi-user network with partially observable Markov ON/OFF channels. Instantaneous channel states are never known...
This paper reports on a theoretical Bayesian modeling development for residual life prediction in the context of condition-based maintenance. At each monitoring point during a comp...
imps is an Interactive Mathematical Proof System intended as a general purpose tool for formulating and applying mathematics in a familiar fashion. The logic of imps is based on a...
William M. Farmer, Joshua D. Guttman, F. Javier Th...
In this paper we introduce a formalism for optimal camera parameter selection for iterative state estimation. We consider a framework based on Shannon’s information theory and se...
Joachim Denzler, Christopher M. Brown, Heinrich Ni...