Abductive Knowledge Base Updates for Contextual Reasoning

  • Authors:

  • Ahmed Guessoum

  • Affiliations:

  • College of Computer and Information Sciences, P.O. Box 51178, Riyadh 11543, Saudi Arabia. E-mail: guessoum@ccis.ksu.edu.sa

  • Venue:
  • Journal of Intelligent Information Systems
  • Year:
  • 1998

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Abstract

We show in this paper how procedures that update knowledge bases cannaturally be adapted to a number of problems related to contextualreasoning. The fact that the update procedures are abductive in nature isfavourably exploited to tackle problems related to human-computer dialoguesystems. We consider as examples aspects of pronoun resolution,goal formulation, and the problem ofrestoring the consistency of a knowledge base after some knowledge update iscarried out. We state these problems in terms of the update problem andabductive reasoning and show how procedures that update knowledge basesyield some interesting results. We also explain how these procedures cannaturally be used to model various forms of hypothetical reasoning such ashypothesizing inconsistencies and performing some “look ahead”form of reasoning.We do not claim thaT the problems presented here are solved entirelywithin the update framework. However, we believe that the flexibility of therepresentation and of the problem-solving approach suggest that the problemscould be solved by adding more details about each problem. What is mostinteresting in our understanding is that all the aforementioned problems areexpressed and tackled within the same framework.