Uplift modeling aims to directly model the incremental impact of a treatment on an individual response. In this work, we address the problem from a new angle and reformulate it as a Markov Decision Process (MDP). We conducted extensive experiments on both a synthetic dataset and real-world scenarios, and showed that our method can achieve significant improvement over previous methods.
@article{arxiv.1811.10158,
title = {Reinforcement Learning for Uplift Modeling},
author = {Chenchen Li and Xiang Yan and Xiaotie Deng and Yuan Qi and Wei Chu and Le Song and Junlong Qiao and Jianshan He and Junwu Xiong},
journal= {arXiv preprint arXiv:1811.10158},
year = {2019}
}