Reinforcement learning (wikipedia) enables agents to learn how to best interact with their environments, resulting in intelligent behaviors of agents, and is a central research topic in artificial intelligence.

AWRL aims at boosting the development of reinforcement learning from foundamental research to industrial applications. While sitting in Asia-Pacific Rim, AWRL intends to be an exciting platform for researchers and practitioners worldwide for exchanging ideas, sharing insights, and initializing cooperations, in the domain of reinforcement learning. We invite reinforcement learning researchers and practitioners to participate in this world-class gathering.


5. AWRL 2020

AWRL 2020 was in conjunction with DAI 2020, in Nanjing, China, 25 Oct. 
URL: https://awrl2020.github.io

4. AWRL 2019

AWRL 2019 was in conjunction with DAI 2019, in Beijing, China, 13 Oct. 
URL: https://awrl.cc/2019.html

3. AWRL 2018

AWRL 2018 was in conjunction with ACML 2018, in Beijing, China, 14 Nov. 
URL: https://awrl.cc/2018.html

2. AWRL 2017

AWRL 2017 was in conjunction with ACML 2017, in Seoul, Korea, 15 Nov.
URL: http://lamda.nju.edu.cn/conf/awrl17/

1. AWRL 2016

AWRL 2016 was the first workshop. It was in conjunction with ACML 2016 in Hamilton, New Zealand, 16 Nov.
URL: https://weng.fr/AWRL2016/