Home /Research /Reinforcement Learning Applications
LEARNING

Reinforcement Learning Applications

Yuxi Li

Year
2019
Access
Open access

Abstract

We start with a brief introduction to reinforcement learning (RL), about its successful stories, basics, an example, issues, the ICML 2019 Workshop on RL for Real Life, how to use it, study material and an outlook. Then we discuss a selection of RL applications, including recommender systems, computer systems, energy, finance, healthcare, robotics, and transportation.

Keywords

cs.LGcs.AI

Related papers

Browse all LEARNING papers