Base Belief Change and Optimized Recovery

  • Authors:
  • Frances Johnson;Stuart C. Shapiro

  • Affiliations:
  • University at Buffalo, CSE Dept., Buffalo, NY, USA, flj|shapiro@cse.buffalo.edu;University at Buffalo, CSE Dept., Buffalo, NY, USA, flj|shapiro@cse.buffalo.edu

  • Venue:
  • Proceedings of the 2006 conference on STAIRS 2006: Proceedings of the Third Starting AI Researchers' Symposium
  • Year:
  • 2006

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Abstract

Optimized Recovery (OR) adds belief base optimization to the traditional Recovery postulate---improving Recovery adherence without sacrificing adherence to the more accepted postulates or to the foundations approach. Reconsideration and belief liberation systems both optimize a knowledge base through consolidation of a chain of base beliefs; and recovered base beliefs are returned to the base. The effects match an iterated revision axiom and show benefits for pre-orders, as well. Any system that can resolve an inconsistent belief base can produce these results.