Optimizing Reinforcement Learning Using a Generative Action-Translator Transformer

Optimizing Reinforcement Learning Using a Generative Action-Translator Transformer

In recent years, with the rapid advancements in Natural Language Processing (NLP) technologies, large models have become widespread. Traditional reinforcement learning algorithms have also started experimenting with language models to optimize training. However, they still fundamentally rely on the...

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Bibliographic Details
Main Authors: Jiaming Li, Ning Xie, Tingting Zhao
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Algorithms
Subjects:
machine learning
reinforcement learning
Transformer
action prediction
Action-Translator Transformer
Online Access:https://www.mdpi.com/1999-4893/17/1/37

Internet

https://www.mdpi.com/1999-4893/17/1/37

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