Exploring large language model based intelligent agents: Definitions, methods, and prospects
Intelligent agents stand out as a potential path toward artificial general intelligence (AGI).
Thus, researchers have dedicated significant effort to diverse implementations for them …
Thus, researchers have dedicated significant effort to diverse implementations for them …
A survey on enhancing reinforcement learning in complex environments: Insights from human and llm feedback
Reinforcement learning (RL) is one of the active fields in machine learning, demonstrating
remarkable potential in tackling real-world challenges. Despite its promising prospects, this …
remarkable potential in tackling real-world challenges. Despite its promising prospects, this …
LLM-empowered state representation for reinforcement learning
Conventional state representations in reinforcement learning often omit critical task-related
details, presenting a significant challenge for value networks in establishing accurate …
details, presenting a significant challenge for value networks in establishing accurate …
Improving Sample Efficiency of Reinforcement Learning with Background Knowledge from Large Language Models
Low sample efficiency is an enduring challenge of reinforcement learning (RL). With the
advent of versatile large language models (LLMs), recent works impart common-sense …
advent of versatile large language models (LLMs), recent works impart common-sense …
[PDF][PDF] Position: Towards LLM-in-the-Loop Machine Learning for Future Applications
M Hong, W Ng, Y Wang, D Jiang, Y Song, CJ Zhang… - researchgate.net
Building on the success of human-in-the-loop, where human wisdom is integrated into the
development of machine learning algorithms, we take the initiative to envision an innovative …
development of machine learning algorithms, we take the initiative to envision an innovative …