Predicting human decisions with behavioral theories and machine learning

arXiv:1904.06866v2 Announce Type: replace-cross
Abstract: Predicting human decision-making under risk and uncertainty represents a quintessential challenge that spans economics, psychology, and related disciplines. Despite decades of research effort, no model can be said to accurately describe and predict human choice even for the most stylized tasks like choice between lotteries. Here, we introduce BEAST Gradient Boosting (BEAST-GB), a novel hybrid model that synergizes behavioral theories, specifically the model BEAST, with machine learning techniques. First, we show the effectiveness of BEAST-GB …

abstract arxiv challenge cs.ai cs.gt cs.lg decision decisions economics human machine machine learning making psychology research risk said tasks type uncertainty