Hitting Times in Markov Chains with Restart and their Application to Network Centrality

TL;DR

This paper derives an explicit formula for the expected hitting time in Markov chains with restart, enabling optimization of restart probability and applications in network centrality.

Contribution

It provides a novel explicit expression for the expected hitting time in Markov chains with restart, facilitating optimization and applications in network analysis.

Findings

Explicit formula for expected hitting time with restart

Optimization of restart probability for minimal hitting time

Application to network centrality measures

Abstract

Motivated by applications in telecommunications, computer scienceand physics, we consider a discrete-time Markov process withrestart. At each step the process eitherwith a positive probability restarts from a given distribution, orwith the complementary probability continues according to a Markovtransition kernel. The main contribution of the present work is thatwe obtain an explicit expression for the expectation of the hittingtime (to a given target set) of the process with restart.The formula is convenient when considering the problem of optimizationof the expected hitting time with respect to the restart probability.We illustrate our results with two examplesin uncountable and countable state spaces andwith an application to network centrality.