In this paper we show that any separable stochastic process on a compact metric space can be derived from a temporally homogeneous Markov process on the extreme points of a compact convex set of ...

High-order Markov chain models extend the conventional framework by incorporating dependencies that span several previous states rather than solely the immediate past. This extension allows for a ...

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 ...

If we can ‘talk’ to AI programs today, it’s in part because of a Russian from the 1800s. Markov’s approach to data in flux changed how we navigate our world. There’s an odd little trick to how AI ...