Improving DreamerV2 by Identifying Irrelevant Environmental Features
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2022-06-20
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en
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Abstract
This thesis introduces DreamerV3. A modified version of the model-based reinforcement learning
algorithm DreamerV2. The thesis outlines the shortcomings of DreamerV2 and motivates the proposed
solution. The performance of DreamerV3 is tested on the Atari Video Pinball environment and a
modified Atari Pong environment. A significant performance increase over DreamerV2 is demonstrated
in the modified Pong environment, but no performance increase is attained for the Video Pinball
environment.
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Faculteit der Sociale Wetenschappen