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Title: Unit Selection Based on Counterfactual Logic

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.

Authors:
;
Award ID(s):
1704932
Publication Date:
NSF-PAR ID:
10180278
Journal Name:
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
Page Range or eLocation-ID:
1793 to 1799
Sponsoring Org:
National Science Foundation
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