Combining Experts’ Causal Judgments

Dalal Alrajeh, Hana Chockler, Joseph Y. Halpern

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

4 Citations (Scopus)
156 Downloads (Pure)

Abstract

Consider a policymaker who wants to decide which intervention to perform in order to change a currently undesirable situation. The policymaker has at her disposal a team of experts, each with their own understanding of the causal dependencies between different factors contributing to the outcome. The policymaker has varying degrees of confidence in the experts’ opinions. She wants to combine their opinions in order to decide on the most effective intervention. We formally define the notion of an effective intervention, and then consider how experts’ causal judgments can be combined in order to determine the most effective intervention. We define a notion of two causal models being compatible, and show how compatible causal models can be combined. We then use it as the basis for combining experts causal judgments. We illustrate our approach on a number of real-life examples.
Original languageEnglish
Title of host publicationProceedings of the Thirty-Second AAAI Conference on Artificial Intelligence
PublisherAAAI Press
Pages6311-6318
Number of pages9
Publication statusPublished - 2 Feb 2018
EventThirty-Second AAAI Conference on Artificial Intelligence - New Orleans, Lousiana, United States
Duration: 2 Feb 20187 Feb 2018
https://aaai.org/Conferences/AAAI-18/

Conference

ConferenceThirty-Second AAAI Conference on Artificial Intelligence
Abbreviated titleAAAI-18
Country/TerritoryUnited States
CityNew Orleans, Lousiana
Period2/02/20187/02/2018
Internet address

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