The Need for Improved Reinforcement Learning Techniques in Intelligent Agents

Author

Donald C. Wunsch, Missouri University of Science and TechnologyFollow

Abstract

Reinforcement learning is an integral part of intelligent agent research. The development of this field, however, has been largely independent of the latest developments in neural networks. As a result, the most popular designs for intelligent agents utilize neural network architectures from several years ago. The article recommends newer, proven designs for reinforcement learning. The recommended designs share historical roots with the most popular architectures in place today, allowing improved performance without radical redesign of existing agents.

Recommended Citation

D. C. Wunsch, "The Need for Improved Reinforcement Learning Techniques in Intelligent Agents," Systems, Man, and Cybernetics, 1997. IEEE International Conference on Computational Cybernetics and Simulation, vol. 4, pp. 3073 - 3077, Institute of Electrical and Electronics Engineers (IEEE), Jan 1997.

The definitive version is available at https://doi.org/10.1109/ICSMC.1997.633059

Meeting Name

IEEE International Conference on Computational Cybernetics and Sumulation: Systems, Man and Cybernetics (1997: Oct. 12-15, Orlando, FL)

Department(s)

Electrical and Computer Engineering

International Standard Book Number (ISBN)

0000780340531

International Standard Serial Number (ISSN)

1062-922X

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 1997 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jan 1997