ZJLAB-AMMI / LLM4Teach

Python code to implement LLM4Teach, a policy distillation approach for teaching reinforcement learning agents with Large Language Model

Date Created 2023-11-29 (about a year ago)

Commits 14 (last one 10 months ago)

Stargazers 32 (2 this week)

Watchers 1 (0 this week)

Forks 14

License unknown

Ranking

RepositoryStats indexes 622,366 repositories, of these ZJLAB-AMMI/LLM4Teach is ranked #591,905 (5th percentile) for total stargazers, and #560,851 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #118,932/126,222.

ZJLAB-AMMI/LLM4Teach is also tagged with popular topics, for these it's ranked: llm (#3,043/3351), reinforcement-learning (#1,351/1411), agents (#337/358)

Other Information

ZJLAB-AMMI/LLM4Teach has 1 open pull request on Github, 0 pull requests have been merged over the lifetime of the repository.

Github issues are enabled, there are 2 open issues and 1 closed issue.

Homepage URL: https://arxiv.org/abs/2311.13373

All Topics

llm agents minigrid distillation decison-making embodied-agent reinforcement-learning

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14 commits on the default branch (main) since jan '22

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The only known language in this repository is Python

updated: 2025-03-03 @ 05:18pm, id: 724958191 / R_kgDOKzX77w