Reinforcement Learning Applications

2019/08/19 by Yuxi Li, Li, Yuxi
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics #Scheduling and Optimization Algorithms

paper · pdf · doi:10.48550/arxiv.1908.06973

openalex publication_date 2019/08/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

Citations

• Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
• Artificial intelligence: a modern approach
• DeepStack: Expert-level artificial intelligence in heads-up no-limit poker
• Attention, Learn to Solve Routing Problems!
• Coloring Big Graphs with AlphaGoZero
• Learning dexterous in-hand manipulation

Related

• Reinforcement Learning in Practice: Opportunities and Challenges
• Deep Reinforcement Learning
• Introduction to Reinforcement Learning
• Reinforcement Learning: An Overview
• Deep Reinforcement Learning: An Overview