Algorithms and hardness results for computing cores of Markov chains

• Main Authors: AHMADI, Ali, CHATTERJEE, Krishnendu, KAFSHDAR GOHARSHADY, Amir, MEGGENDORFER, Tobias, SAFAVI, Roodabeh, ZIKELIC, Dorde
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Markov Chains; Cores; Complexity; Software Engineering; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/9059; https://ink.library.smu.edu.sg/context/sis_research/article/10062/viewcontent/Algorithms_and_Hardness_Results.pdf
• Institution: Singapore Management University

Given a Markov chain M = (V,v0,δ), with state space V and a starting state v0, and a probability threshold ϵ, an ϵ-core is a subset C of states that is left with probability at most ϵ. More formally, C ⊆V is an ϵ-core, iff P reach(V\C) ≤ ϵ. Cores have been applied in a wide variety of verification p...