policy
FYP-Using-LLMs-to-Generate-Reward-Functions-from-Natural-Language-in-RL-Environments
SamPlayz6 · PyTorch
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Overview
Name
FYP-Using-LLMs-to-Generate-Reward-Functions-from-Natural-Language-in-RL-Environments
Author
SamPlayz6
Framework
PyTorch
License
unknown
Skill type
other
Evidence level
untested
Task description
This research uses Large Language Models to generate reward functions from natural language in reinforcement learning. A flexible testbed evaluates these functions' accuracy, consistency, and robustness across various tasks and inputs, aiming to create an intuitive method for specifying RL rewards.
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
3+17 mentioned but not in catalog yetCompatible environments
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Datasets that reference this policy
0No datasets reference FYP-Using-LLMs-to-Generate-Reward-Functions-from-Natural-Language-in-RL-Environments yet.