Deep Reinforcement Learning for Recommender Systems

Courses on Deep Reinforcement Learning (DRL) and DRL papers for recommender system

Courses

UCL Course on RL

http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html

CS 294-112 at UC Berkeley

http://rail.eecs.berkeley.edu/deeprlcourse/

Stanford CS234: Reinforcement Learning

http://web.stanford.edu/class/cs234/index.html

Book

1. Reinforcement Learning: An Introduction (Second Edition). Richard S. Sutton and Andrew G. Barto. book

Papers

Survey Papers

1. A Brief Survey of Deep Reinforcement Learning. Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, Anil Anthony Bharath. 2017. paper
2. Deep Reinforcement Learing: An Overview. Yuxi Li. 2017. paper

Conference Papers

1. An MDP-Based Recommender System. Guy Shani, David Heckerman, Ronen I. Brafman. JMLR 2005. paper
2. Usage-Based Web Recommendations: A Reinforcement Learning Approach. Nima Taghipour, Ahmad Kardan, Saeed Shiry Ghidary. Recsys 2007. paper
3. Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning. Jun Feng, Heng Li, Minlie Huang, Shichen Liu, Wenwu Ou, Zhirong Wang, Xiaoyan Zhu. WWW 2018. paper
4. Reinforcement Mechanism Design for e-commerce. Qingpeng Cai, Aris Filos-Ratsikas, Pingzhong Tang, Yiwei Zhang. WWW 2018. paper
5. DRN: A Deep Reinforcement Learning Framework for News Recommendation. Guanjie Zheng, Fuzheng Zhang, Zihan Zheng, Yang Xiang, Nicholas Jing Yuan, Xing Xie, Zhenhui Li. WWW 2018. paper
6. Deep Reinforcement Learning for Page-wise Recommendations. Xiangyu Zhao, Long Xia, Liang Zhang, Zhuoye Ding, Dawei Yin, Jiliang Tang. RecSys 2018. paper
7. Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning. Xiangyu Zhao, Liang Zhang, Zhuoye Ding, Long Xia, Jiliang Tang, Dawei Yin. KDD 2018. paper
8. Stabilizing Reinforcement Learning in Dynamic Environment with Application to Online Recommendation. Shi-Yong Chen, Yang Yu, Qing Da, Jun Tan, Hai-Kuan Huang, Hai-Hong Tang. KDD 2018 paper
9. Reinforcement Learning based Recommender System using Biclustering Technique. Sungwoon Choi, Heonseok Ha, Uiwon Hwang, Chanju Kim, Jung-Woo Ha, Sungroh Yoon. arxiv 2018. paper
10. Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling. Feng Liu, Ruiming Tang, Xutao Li, Weinan Zhang, Yunming Ye, Haokun Chen, Huifeng Guo, Yuzhou Zhang. arxiv 2018. paper
11. Model-Based Reinforcement Learning for Whole-Chain Recommendations. Xiangyu Zhao, Long Xia, Yihong Zhao, Dawei Yin, Jiliang Tang. arxiv 2019. paper
12. Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems. Lixin Zou, Long Xia, Zhuoye Ding, Jiaxing Song, Weidong Liu, Dawei Yin. arxiv 2019. paper