DocumentCode
2221894
Title
A comparison of direct and model-based reinforcement learning
Author
Atkeson, Christopher G. ; Santamaría, Juan Carlos
Author_Institution
Coll. of Comput., Georgia Inst. of Technol., Atlanta, GA, USA
Volume
4
fYear
1997
fDate
20-25 Apr 1997
Firstpage
3557
Abstract
This paper compares direct reinforcement learning (no explicit model) and model-based reinforcement learning on a simple task: pendulum swing up. We find that in this task model-based approaches support reinforcement learning from smaller amounts of training data and efficient handling of changing goals
Keywords
learning (artificial intelligence); model reference adaptive control systems; nonlinear control systems; robots; acrobot; direct reinforcement learning; model-based reinforcement learning; pendulum swing-up; Computational modeling; Control system synthesis; Control systems; Educational institutions; Force control; Jacobian matrices; Learning; Robots; State-space methods; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation, 1997. Proceedings., 1997 IEEE International Conference on
Conference_Location
Albuquerque, NM
Print_ISBN
0-7803-3612-7
Type
conf
DOI
10.1109/ROBOT.1997.606886
Filename
606886
Link To Document