Implementing Bounded Revision via Lexicographic Revision and C-revision


  • Meliha Sezgin TU Dortmund University
  • Gabriele Kern-Isberner TU Dortmund University



KRR: Belief Change, KRR: Nonmonotonic Reasoning, KRR: Preferences, KRR: Qualitative Reasoning, KRR: Reasoning with Beliefs


New information in the context of real life settings usually is accompanied by some kind of supplementary information that indicates context, reliability, or expertise of the information's source. Bounded Revision (BR) displays an iterated belief revision mechanism that takes as input a new information accompanied by a reference sentence acting as supplementary information, which specifies the depth with which the new input shall be integrated in the posterior belief state. The reference sentence specifies which worlds in the prior belief state are affected by the change mechanism. We show that Bounded Revision can be characterized by three simple, yet elegant postulates and corresponds to a special case of a lexicographic revision, which inherits all relevant features of BR. Furthermore, we present methodological implementations of BR including conditional revision with c-revisions, making it directly usable for conditional revision tools.




How to Cite

Sezgin, M., & Kern-Isberner, G. (2023). Implementing Bounded Revision via Lexicographic Revision and C-revision. Proceedings of the AAAI Conference on Artificial Intelligence, 37(5), 6525-6532.



AAAI Technical Track on Knowledge Representation and Reasoning