Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
7-2015
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
motivated learning, reinforcement learning, goal creation, pain signals, desired resources
Discipline
Databases and Information Systems | Theory and Algorithms
Research Areas
Data Science and Engineering
Publication
Proceedings of 2015 International Joint Conference on Neural Networks, Killarney, Ireland, July 12-17
Volume
2015
First Page
1
Last Page
8
Identifier
10.1109/IJCNN.2015.7280723
Publisher
IEEE
City or Country
New York
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/IJCNN.2015.7280723