Syntactic computation of Fagin-Halpern conditioning in possibility theory

Omar Ettarguy; Ahlame Begdouri; Salem Benferhat; Carole Delenne

doi:10.29007/9pjn

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Syntactic computation of Fagin-Halpern conditioning in possibility theory

17 pages•Published: June 3, 2023

Omar Ettarguy, Ahlame Begdouri, Salem Benferhat and Carole Delenne

Abstract

Conditioning plays an important role in revising uncertain information in light of new evidence. This work focuses on the study of Fagin and Halpern (FH-)conditioning in the context where uncertain information is represented by weighted or possibilistic belief bases. Weighted belief bases are extensions of classical logic belief bases where a weight or degree of belief is associated with each propositional logic formula. This paper proposes a characterization of a syntactic computation of the revision of weighted belief bases (in the light of new information) which is in full agreement with the semantics of the FH- conditioning of possibilistic distributions. We show that the size of the revised belief base is linear with respect to the size of the initial base and that the computational complexity amounts to performing O(log2(n)) calls to the propositional logic satisfiability tests, where n is the number of different degrees of certainty used in the initial belief base.

Keyphrases: conditioning, possibility theory, weighted knowledge bases

In: Ruzica Piskac and Andrei Voronkov (editors). Proceedings of 24th International Conference on Logic for Programming, Artificial Intelligence and Reasoning, vol 94, pages 164--180

Links:	https://easychair.org/publications/paper/6LgH
	https://doi.org/10.29007/9pjn

BibTeX entry

@inproceedings{LPAR2023:Syntactic_computation_of_Fagin_Halpern,
  author    = {Omar Ettarguy and Ahlame Begdouri and Salem Benferhat and Carole Delenne},
  title     = {Syntactic computation of Fagin-Halpern conditioning in possibility theory},
  booktitle = {Proceedings of 24th International Conference on Logic for Programming, Artificial Intelligence and Reasoning},
  editor    = {Ruzica Piskac and Andrei Voronkov},
  series    = {EPiC Series in Computing},
  volume    = {94},
  pages     = {164--180},
  year      = {2023},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/6LgH},
  doi       = {10.29007/9pjn}}

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