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- Title: Translating Natural Language to Planning Goals With LLM
- Author: Yaqi Xie et. al.
- Publish Year: 10 Feb 2023
- Review Date: Mon, May 22, 2023
- url: https://arxiv.org/pdf/2302.05128.pdf
Summary of paper
Motivation
- Unfortunately, recent work has also shown that LLMs are unable to perform accurate reasoning nor solve planning problem
- LLM can act as a natural interface between the planner and human users
- Our empirical results on GPT 3.5 variants show that LLMs are much better suited towards translation rather than planning.
Contribution
- We find that LLMs are able to leverage commonsense knowledge and reasoning to furnish missing details from under-specified goals (as is often the case in natural language)
Some key terms
Architecture
Potential future work
- the experiment is only about generating PDDL goal from the PDDL texts
- however, in ALFRED environment, PDDL problem file will not be provided during testing.