Bayesian knowledge fusion

Eugene Santos, John T. Wilkinson, Eunice E. Santos

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

Abstract

We address the problem of information fusion in uncertain environments. Imagine there are multiple experts building probabilistic models of the same situation and we wish to aggregate the information they provide. There are several problems we may run into by naively merging the information from each. For example, the experts may disagree on the probability of a certain event or they may disagree on the direction of causility between two events (e.g., one thinks A causes B while another thinks B causes A). They may even disagree on the entire structure of dependencies among a set of variables in a probabilistic network. In our proposed solution to this problem, we represent the probabilistic models as Bayesian Knowledge Bases (BKBs) and propose an algorithm called Bayesian knowledge fusion that allows the fusion of multiple BKBs into a single BKB that retains the information from all input sources. This allows for easy aggregation and de-aggregation of information from multiple expert sources and facilitates multi-expert decision making by providing a framework in which all opinions can be preserved and reasoned over.

Original languageEnglish (US)
Title of host publicationProceedings of the 22nd International Florida Artificial Intelligence Research Society Conference, FLAIRS-22
Pages559-564
Number of pages6
StatePublished - Nov 4 2009
Externally publishedYes
Event22nd International Florida Artificial Intelligence Research Society Conference, FLAIRS-22 - Sanibel Island, FL, United States
Duration: Mar 19 2009Mar 21 2009

Publication series

NameProceedings of the 22nd International Florida Artificial Intelligence Research Society Conference, FLAIRS-22

Conference

Conference22nd International Florida Artificial Intelligence Research Society Conference, FLAIRS-22
CountryUnited States
CitySanibel Island, FL
Period3/19/093/21/09

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

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