How Clear Probabilistic Models Can Strengthen Intelligent Systems in an Uncertain World

Software engineer Sai Bhargav Yalamanchi notes that mathematical tools helping practitioners interpret uncertainty have ...
Nature

Probabilistic Model Checking and Markov Decision Processes

Probabilistic model checking and Markov decision processes (MDPs) form two interlinked branches of formal analysis for systems operating under uncertainty. These techniques offer a mathematical ...
JSTOR Daily

Partially Observable Total-Cost Markov Decision Processes with Weakly Continuous Transition Probabilities

This paper describes sufficient conditions for the existence of optimal policies for partially observable Markov decision processes (POMDPs) with Borel state, observation, and action sets, when the ...
JSTOR Daily

On Measurability and Representation of Strategic Measures in Markov Decision Processes

Lecture Notes-Monograph Series, Vol. 30, Statistics, Probability and Game Theory: Papers in Honor of David Blackwell (1996), pp. 29-43 (15 pages) This paper deals with a discrete time Markov Decision ...
University of Bristol

Markov disease progression models

Markov Models for disease progression are common in medical decision making (see references below). The parameters in a Markov model can be estimated by observing the time it takes patients in any ...
Forbes

New Study: 49% Of Companies Have Stagnant Decision Styles – Can Technology Help?

Forbes contributors publish independent expert analyses and insights. I write about the decision intelligence revolution. Aug 20, 2024, 10:26am EDT New research finds that over half of companies ...