Shareable and inheritable incremental compilation in iOOBN

Md Samiullah, Ann Nicholson, David Albrecht

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)

Abstract

Object-oriented Bayesian networks (OOBNs) allow modellers to construct compositional and hierarchical models, using an inheritance hierarchy of classes ad subclasses, enabling reuse and supporting maintenance. Reasoning with both ordinary Bayesian networks (BNs) and OOBNs requires the important computational task of inference, the computing of new posterior probability distributions given a set of evidence. A widely used inference technique in ordinary BNs involves compiling the BN into a so-called junction tree (JT) before performing the inference; the compilation step is only performed when the model changes. In current OOBN software, the OOBN is first transformed into the underlying BN, so-called flattening, then the standard inference is performed. Researchers have proposed methods for incremental compilation of BNs, rather than recompiling from scratch for each network modification; these can apply to OOBNs also after flattening. Here, we propose a new incremental compilation technique that reuses existing compiled JTs of both embedded components and superclasses, and does not require flattening. We demonstrate through experimental analysis that this can reduce compilation time, and produces compact JTs that are cost-effective for inference.

Original languageEnglish
Title of host publication20th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2023 Jakarta, Indonesia, November 15–19, 2023 Proceedings, Part II
EditorsFenrong Liu, Arun Anand Sadanandan, Duc Nghia Pham, Petrus Mursanto, Dickson Lukose
Place of PublicationSingapore Singapore
PublisherSpringer
Pages91-103
Number of pages13
ISBN (Electronic)9789819970223
ISBN (Print)9789819970216
DOIs
Publication statusPublished - 2024
EventPacific Rim International Conference on Artificial Intelligence 2023 - Jakarta, Indonesia
Duration: 15 Nov 202319 Nov 2023
Conference number: 20th
https://link.springer.com/book/10.1007/978-981-99-7022-3 (Proceedings)

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume14326
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferencePacific Rim International Conference on Artificial Intelligence 2023
Abbreviated titlePRICAI 2023
Country/TerritoryIndonesia
CityJakarta
Period15/11/2319/11/23
Internet address

Keywords

  • Graphical Models
  • Incremental Compilation
  • OOBN

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