Motivated learning as an extension of reinforcement learning

Author

Janusz STARZYK
Pawel RAIF
Ah-hwee TAN, Singapore Management UniversityFollow

Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

1-2010

Abstract

We have developed a unified framework to conduct computational experiments with both learning systems: Motivated learning based on Goal Creation System, and reinforcedment learning using RL Q-Learning Algorithm. Future work includes combining motivated learning to set abstract motivations and manage goals with reinforcement learning to learn proper actions. This will allow testing of motivated learning on typical reinforcement learning benchmarks with large dimensionality of the state/action spaces.

Keywords

Learning systems, motivated learning, reinforcement learning

Discipline

Artificial Intelligence and Robotics | Theory and Algorithms

Research Areas

Data Science and Engineering

Publication

4th International Conference on Cognitive Systems, CogSys 2010: January 27-28, Zurich: Proceedings

First Page

1

Last Page

1

Publisher

ETH Zurich

City or Country

Zurich

Citation

STARZYK, Janusz; RAIF, Pawel; and TAN, Ah-hwee. Motivated learning as an extension of reinforcement learning. (2010). 4th International Conference on Cognitive Systems, CogSys 2010: January 27-28, Zurich: Proceedings. 1-1.
Available at: https://ink.library.smu.edu.sg/sis_research/6573

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.