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
fDate :
7/1/2015 12:00:00 AM
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"
Conference_Titel :
Neural Networks (IJCNN), 2015 International Joint Conference on
Electronic_ISBN :
2161-4407
DOI :
10.1109/IJCNN.2015.7280723