LLM-Guided Task- and Affordance-Level Exploration in Reinforcement Learning

Name: LLM-Guided Task- and Affordance-Level Exploration in Reinforcement Learning
Uploaded: 2026-10-07T11:31:17.915190+00:00
Duration: 641 s
Description: LLM-TALE uses Large Language Models to improve reinforcement learning for robotic manipulation by guiding exploration toward meaningful states. It generates task-level plans and affordance-level action candidates, allowing the agent to learn more efficiently. This method successfully achieved high success rates in real-world tasks with zero-shot sim-to-real transfer.

LLM-TALE uses Large Language Models to improve reinforcement learning for robotic manipulation by guiding exploration toward meaningful states. It generates task-level plans and affordance-level action candidates, allowing the agent to learn more efficiently. This method successfully achieved high success rates in real-world tasks with zero-shot sim-to-real transfer.

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