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 ...
JSTOR Daily

MAXIMUM LIKELIHOOD ESTIMATION IN MARKOV REGIME-SWITCHING MODELS WITH COVARIATE-DEPENDENT TRANSITION PROBABILITIES

This is a preview. Log in through your library . Abstract This paper considers maximum likelihood (ML) estimation in a large class of models with hidden Markov regimes. We investigate consistency of ...
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 ...