RL4RS: A Real-World Dataset for Reinforcement Learning based Recommender System.
Kai WangZhene ZouMinghao ZhaoQilin DengYue ShangYile LiangRunze WuXudong ShenTangjie LyuChangjie FanPublished in: SIGIR (2023)
Keyphrases
- reinforcement learning
- recommender systems
- function approximation
- collaborative filtering
- recommendation algorithms
- reinforcement learning algorithms
- rl algorithms
- state space
- machine learning
- learning algorithm
- product recommendation
- control problems
- temporal difference
- model free
- markov decision processes
- optimal policy
- approximate dynamic programming
- optimal control
- learning problems
- action selection
- actor critic
- user preferences
- multi agent
- reinforcement learning methods
- learning process
- temporal difference learning
- partially observable domains
- user profiles
- complex domains
- partially observable
- user model
- implicit feedback
- markov decision problems
- agent learns
- exploration exploitation
- direct policy search