Reinforcement Learning for Uplift Modeling

2018/11/26 by Chenchen Li, Li, Chenchen, Xiang Yan +15
Computer Science · Mathematics · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics #Statistical Methods in Clinical Trials

paper · pdf · doi:10.48550/arxiv.1811.10158

openalex publication_date 2018/11/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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.

Citations

• Doubly Robust Policy Evaluation and Learning
• The central role of the propensity score in observational studies for causal effects

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