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Decision-Theoretic Monitoring of Cyber-Physical Systems

  • Andrey Yavolovsky
  • Miloš ŽefranEmail author
  • A. Prasad Sistla
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10012)

Abstract

Runtime monitoring has been proposed as an alternative to formal verification for safety critical systems. This paper introduces a decision-theoretic view of runtime monitoring. We formulate the monitoring problem as a Partially Observable Markov Decision Process (POMDP). Furthermore, we adopt a Partially Observable Monte-Carlo Planning (POMCP) to compute an approximate optimal policy of the monitoring POMDP. We show how to construct the POMCP for the monitoring problem and demonstrate experimentally that it can be effectively applied even when some of the state-space variables are continuous, the case where many other POMDP solvers fail. Experimental results on a mobile robot system show the effectiveness of the proposed POMDP-monitor.

Keywords

Belief State Reward Function Partially Observable Markov Decision Process Runtime Monitoring Product Automaton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Andrey Yavolovsky
    • 1
  • Miloš Žefran
    • 1
    Email author
  • A. Prasad Sistla
    • 1
  1. 1.University of Illinois at ChicagoChicagoUSA

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