Iterated belief change in the situation calculus

  • Authors:

  • Steven Shapiro;Maurice Pagnucco;Yves Lespérance;Hector J. Levesque

  • Affiliations:

  • Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4, Canada;ARC Centre of Excellence for Autonomous Systems and National ICT Australia, School of Computer Science and Engineering, The University of New South Wales, Sydney, NSW 2052, Australia;Department of Computer Science and Engineering, York University, Toronto, ON M3J 1P3, Canada;Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4, Canada

  • Venue:
  • Artificial Intelligence
  • Year:
  • 2011

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Abstract

John McCarthy's situation calculus has left an enduring mark on artificial intelligence research. This simple yet elegant formalism for modelling and reasoning about dynamic systems is still in common use more than forty years since it was first proposed. The ability to reason about action and change has long been considered a necessary component for any intelligent system. The situation calculus and its numerous extensions as well as the many competing proposals that it has inspired deal with this problem to some extent. In this paper, we offer a new approach to belief change associated with performing actions that addresses some of the shortcomings of these approaches. In particular, our approach is based on a well-developed theory of action in the situation calculus extended to deal with belief. Moreover, by augmenting this approach with a notion of plausibility over situations, our account handles nested belief, belief introspection, mistaken belief, and handles belief revision and belief update together with iterated belief change.