DocumentCode
3661410
Title
A comparative study between motivated learning and reinforcement learning
Author
J. Graham;J. A. Starzyk;Z. Ni;H. He;T.-H. Teng;A.-H. Tan
Author_Institution
School of EECS, Ohio Univ., Athens, USA
fYear
2015
fDate
7/1/2015 12:00:00 AM
Firstpage
1
Lastpage
8
Abstract
This paper analyzes advanced reinforcement learning techniques and compares some of them to motivated learning. Motivated learning is briefly discussed indicating its relation to reinforcement learning. A black box scenario for comparative analysis of learning efficiency in autonomous agents is developed and described. This is used to analyze selected algorithms. Reported results demonstrate that in the selected category of problems, motivated learning outperformed all reinforcement learning algorithms we compared with.
Keywords
"Robot kinematics","Planning"
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), 2015 International Joint Conference on
Electronic_ISBN
2161-4407
Type
conf
DOI
10.1109/IJCNN.2015.7280723
Filename
7280723
Link To Document