Representing actions and state constraints in model-based diagnosis

  • Authors:

  • Sheila A. McIlraith

  • Affiliations:

  • Xerox Palo Alto Research Center, Palo Alto, CA and Knowledge Systems Laboratory, Stanford University, Stanford, CA

  • Venue:
  • AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
  • Year:
  • 1997

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Abstract

In this paper we examine an important set of representation issues which have not been addressed by the model-based diagnosis community. In particular, we examine the problem of integrating a model-based diagnosis system description, SD, with a theory of action to parsimoniously represent the effect of actions on a system and the effects of system state on performing actions in the world. We employ the situation calculus, a first-order language, as our representation language. In the context of the situation calculus, SD presents an, often complex, set of state constraints. These state constraints implicitly define indirect effects of actions as well as indirectly imposing further preconditions on the performance of actions. As a consequence, SD presents further complications to addressing the frame, ramification and qualification problems. For the purposes of this paper, we examine a syntactically restricted SD, which commonly occurs in the axiomatization of model-based diagnosis domains. The contributions of this paper include: 1) a framework for integrating SD and a theory of action. 2) a procedure for compiling SD into a set of successor state axioms. These axioms capture the intended interpretation of SD, while providing a closed-form solution to the frame and ramification problems.