Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning: Prompts by@heuristicsearch
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Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning: Prompts
by Aiding in the focused exploration of potential solutions.April 18th, 2024
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In this paper we study how the “semantic guesswork” produced by language models can be utilized as a guiding heuristic for planning algorithms.
This is paper is available on arxiv under CC 4.0 DEED license.
Authors:
(1) Dhruv Shah, UC Berkeley and he contributed equally;
(2) Michael Equi, UC Berkeley and he contributed equally;
(3) Blazej Osinski, University of Warsaw;
(4) Fei Xia, Google DeepMind;
(5) Brian Ichter, Google DeepMind;
(6) Sergey Levine, UC Berkeley and Google DeepMind.
Table of Links
- Abstract & Introduction
- Related Work
- Problem Formulation and Overview
- LFG: Scoring Subgoals by Polling LLMs
- LLM Heuristics for Goal-Directed Exploration
- System Evaluation
- Discussion and References
- A. Implementation Details
- B. Prompts
B Prompts
B.1 Positive Prompt
B.2 Negative Prompt
L O A D I N G
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