This research explores how a wide range of automobile crash, emergency responder, hospital, and trauma information could be useful to emergency medical practitioners for making de...
Benjamin L. Schooley, Thomas A. Horan, Michael Mar...
In many applications, decision making under uncertainty often involves two steps- prediction of a certain quality parameter or indicator of the system under study and the subseque...
: Numerous design decisions are made in model-driven software development which are mostly implicit and not documented properly. Hence, the design knowledge is usually 'in the...
This paper presents a user-centered design methodology for Decision Support Systems (DSSs), which is specifically built to face the socio-technical gap that often impedes DSS accep...
Pietro Baroni, Daniela Fogli, Massimiliano Giacomi...
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...