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

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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Bibliographic Details
Main Authors: Byeong-Ju Park, Sung-Jung Yong, Hyun-Seo Hwang, Il-Young Moon
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Applied Sciences
Subjects:
reinforcement learning
artificial intelligence
large language models
natural language processing
agent behavior optimization
Online Access:https://www.mdpi.com/2076-3417/15/4/1860

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https://www.mdpi.com/2076-3417/15/4/1860

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