Predicting human decisions with behavioral theories and machine learning

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1 Predicting human decisions with behavioral theories and machine learning Plonsky, Ori1a; Apel, Reuta; Ert, Eyalb; Tennenholtz, Moshea; Bourgin, Davidc; Peterson , Joshua , C.c; Reichman, Danielc; Griffiths , Thomas L.c; Russell , Stuart , J.d; Carter, Evan, C.e; Cavanagh , James , F.f; Erev, Idoa a Technion - Israel Institute of Technology ; b The Hebrew University of Jerusalem ; c Princeton University ; d University of California, Berkeley ; e United States Army Research Laboratory ; f The University of New Mexico . Abstract Behavioral decision theories aim to explain human behavior. Can they help predict it? An open tournament for prediction of human choices in fundamental economic decision tasks is presented. The results suggest that integration of certain behavioral theorie s as features in machine learning systems provides the best predictions. Surprisingly, the most useful theories for prediction build on basic properties of human and animal lea...

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• [1] https://arxiv.org/abs/1904.06866