MATEC Web Conf.
Volume 370, 20222022 RAPDASA-RobMech-PRASA-CoSAAMI Conference - Digital Technology in Product Development - The 23rd Annual International RAPDASA Conference joined by RobMech, PRASA and CoSAAMI
|Number of page(s)||13|
|Published online||01 December 2022|
Improving Reinforcement Learning with Ensembles of Different Learners
1 Council for Scientific and Industrial Research, South Africa
2 School of Computer Science and Applied Mathematics, University of the Witwatersrand, South Africa
* Corresponding author: firstname.lastname@example.org
Different reinforcement learning (RL) methods exist to address the problem of combining multiple different learners to generate a superior learner. These existing methods usually assume that each learner uses the same algorithm and/or state representation. We propose an ensemble learner that combines a set of base learners and leverages the strengths of the different base learners online. We demonstrate the proposed ensemble learner’s ability to combine the strengths of multiple base learners and adapt to changes in base learner performance on various domains, including the Atari Breakout domain.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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