Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Target motion analysis and track association are the aims of this paper. It is assumed that the target trajectory is only partially observable by using temporal processing of a si...
Partially Observable Markov Decision Processes have been studied widely as a model for decision making under uncertainty, and a number of methods have been developed to find the s...
The Partially Observable Markov Decision Process (POMDP) model is explored for high level decision making for Unmanned Air Vehicles (UAVs). The type of UAV modeled is a flying mun...
Abstract--In both the commercial and defense sectors a compelling need is emerging for rapid, yet secure, dissemination of information. In this paper we address the threat of infor...
Janusz Marecki, Mudhakar Srivatsa, Pradeep Varakan...