Counterexample-guided control

  • Authors:

  • Thomas A. Henzinger;Ranjit Jhala;Rupak Majumdar

  • Affiliations:

  • EECS Department, University of California, Berkeley;EECS Department, University of California, Berkeley;EECS Department, University of California, Berkeley

  • Venue:
  • ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
  • Year:
  • 2003

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Abstract

A major hurdle in the algorithmic verification and control of systems is the need to find suitable abstract models, which omit enough details to overcome the state-explosion problem, but retain enough details to exhibit satisfaction or controllability with respect to the specification. The paradigm of counterexample-guided abstraction refinement suggests a fully automatic way of finding suitable abstract models: one starts with a coarse abstraction, attempts to verify or control the abstract model, and if this attempt fails and the abstract counterexample does not correspond to a concrete counterexample, then one uses the spurious counterexample to guide the refinement of the abstract model. We present a counterexample-guided refinement algorithm for solving ω-regular control objectives. The main difficulty is that in control, unlike in verification, counterexamples are strategies in a game between system and controller. In the case that the controller has no choices, our scheme subsumes known counterexample-guided refinement algorithms for the verification of ω-regular specifications. Our algorithm is useful in all situations where ω-regular games need to be solved, such as supervisory control, sequential and program synthesis, and modular verification. The algorithm is fully symbolic, and therefore applicable also to infinite-state systems.