Linear time and space algorithm for computing all the fagin-halpern conditional beliefs generated from consonant belief functions

Lalintha G. Polpitiya, Kamal Premaratne, Manohar N. Murthi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a highly efficient exact dynamic programming algorithm for computing all the conditionals generated from consonant belief functions. The time and space complexities of this novel algorithm are linear for computing all the conditional beliefs, and hence it significantly outperforms the exponential time and space complexity requirements of the brute force approach and the currently available conditional computation strategies. We provide a thorough analysis and experimental validation of the utility, efficiency, and implementation of the proposed algorithm for carrying out the Fagin-Halpern conditional. A new computational library is developed and harnessed in the simulations.

Original languageEnglish (US)
Title of host publicationProceedings of the 32nd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2019
EditorsRoman Bartak, Keith Brawner
PublisherThe AAAI Press
Pages482-487
Number of pages6
ISBN (Electronic)9781577358053
StatePublished - 2019
Externally publishedYes
Event32nd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2019 - Sarasota, United States
Duration: May 19 2019May 22 2019

Publication series

NameProceedings of the 32nd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2019

Conference

Conference32nd International Florida Artificial Intelligence Research Society Conference, FLAIRS 2019
CountryUnited States
CitySarasota
Period5/19/195/22/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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