On a Notion of Resilience for Markov Decision Processes with Reachability Objectives

Xiaoming Duan, Nasim Baharisangari, Rui Yan, Zhe Xu, Melkior Ornik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose and study a notion of resilience for Markov decision processes (MDPs) with the almost-sure reachability objective to action losses. Given an MDP with an initial state and a set of target states, we define the resilience degree of the MDP as the minimum number of actions that must be removed so that the target states cannot be reached almost surely from the initial state. This notion measures the level of tolerance of an MDP to action losses under the reachability objective. We first preprocess the MDP to remove irrelevant states and actions and construct a reduced transition diagram. Then, we show that computing the resilience degree is an NP-hard problem and provide an exact solution based on the mixed-integer linear programming.

Original languageEnglish (US)
Title of host publicationIFAC-PapersOnLine
EditorsHideaki Ishii, Yoshio Ebihara, Jun-ichi Imura, Masaki Yamakita
PublisherElsevier B.V.
Pages11261-11266
Number of pages6
Edition2
ISBN (Electronic)9781713872344
DOIs
StatePublished - Jul 1 2023
Externally publishedYes
Event22nd IFAC World Congress - Yokohama, Japan
Duration: Jul 9 2023Jul 14 2023

Publication series

NameIFAC-PapersOnLine
Number2
Volume56
ISSN (Electronic)2405-8963

Conference

Conference22nd IFAC World Congress
Country/TerritoryJapan
CityYokohama
Period7/9/237/14/23

Keywords

  • decision making
  • Markov decision processes
  • reachability analysis
  • resilience

ASJC Scopus subject areas

  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'On a Notion of Resilience for Markov Decision Processes with Reachability Objectives'. Together they form a unique fingerprint.

Cite this