{"type":"ScholarlyArticle","title":"Unit Selection Based on Counterfactual Logic","authors":[{"name":"Ang Li","slug":"ang-li","given":"Ang","family":"Li","affiliation":"Cognitive Systems Laboratory , University of California , Los Angeles"},{"name":"Judea Pearl","slug":"judea-pearl","given":"Judea","family":"Pearl","affiliation":"Cognitive Systems Laboratory , University of California , Los Angeles"}],"abstract":"The unit selection problem aims to identify a set of individuals who are most likely to exhibit a desired mode of behavior, which is defined in counterfactual terms. A typical example is that of selecting individuals who would respond one way if encouraged and a different way if not encouraged. Unlike previous works on this problem, which rely on ad-hoc heuristics, we approach this problem formally, using counterfactual logic, to properly capture the nature of the desired behavior. This formalism enables us to derive an informative selection criterion which integrates experimental and observational data. We demonstrate the superiority of this criterion over A/B-test-based approaches.","doi":"10.24963/ijcai.2019/248","url":"https://ijcai.org/proceedings/2019/248","pdf":"https://ijcai.org/proceedings/2019/0248.pdf","markdown":"https://ijcai.org/proceedings/2019/248.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/248","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Knowledge Representation and Reasoning","track":"Main track","number":248,"pages":{"first":1793,"last":1799},"keywords":["Knowledge Representation and Reasoning: Knowledge Representation and Decision ; Utility Theory","Knowledge Representation and Reasoning: Action, Change and Causality"],"videos":[],"references":[{"position":1,"raw":"[Angrist et al., 1996] Joshua D Angrist, Guido W Imbens, and Donald B Rubin. 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