Optimizing Agent Behavior in the MiniGrid Environment Using Reinforcement Learning Based on Large Language Models

Reinforcement learning is one of the most prominent research areas in the field of artificial intelligence, playing a crucial role in developing agents that autonomously make decisions in complex environments. This study proposes a method to optimize agent behavior in the MiniGrid-Empty-5x5-v0 envir...

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Principais autores:	Byeong-Ju Park, Sung-Jung Yong, Hyun-Seo Hwang, Il-Young Moon
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2025-02-01
Series:	Applied Sciences
Assuntos:	reinforcement learning artificial intelligence large language models natural language processing agent behavior optimization
Acceso en liña:	https://www.mdpi.com/2076-3417/15/4/1860
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