Markov Chains : The Strange Math That Predicts Almost Anything

Discover how Markov chains predict real systems, from Ulam and von Neumann’s Monte Carlo to PageRank, so you can grasp ...
Nature

Markov Processes and Self-Similar Stochastic Models

Markov processes form a fundamental class of stochastic models in which the evolution of a system is delineated by the memoryless property. In such processes, the future state depends solely on the ...
Nature

Quasi-Stationary Distributions In Markov Processes

Quasi-stationary distributions (QSDs) offer a compelling framework for understanding the long-term behaviour of Markov processes that possess an absorbing state. In many natural and engineered systems ...
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 ...

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

Optimality of Quasi-Open-Loop Policies for Discounted Semi-Markov Decision Processes

Quasi-open-loop policies consist of sequences of Markovian decision rules that are insensitive to one component of the state space. Given a semi-Markov decision process (SMDP), we distinguish between ...
CU Boulder News & Events

APPA 5002: Discrete-Time Markov Chains and Monte Carlo Methods

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...