An approach to Lifelong Reinforcement Learning through Multiple Environments

By Fumihide Tanaka, Masayuki Yamamura. 1998

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Bing Liu
2. Zhiyuan Chen
3. B. Liu
4. Shuai Wang
5. Zixuan Ke
6. Lei Shu
7. Qiang Yang
8. Hu Xu

Citations in the corpus

• Lifelong machine learning: a paradigm for continuous learning (2017, methodology): “Tanaka and Yamamura [14] proposed an LRL method that treats each environment as a task.”
• Lifelong Machine Learning Systems: Beyond Learning Algorithms (2013, background): “Tanaka and Yamamura proposed a lifelong reinforcement learning method for autonomous-robots by treating multiple environments as multiple-tasks (Tanaka and Yamamura 1999).”