Prompt Engineering Guidance for Conceptual Agent-based Model Extraction using Large Language Models
Year: 2024
Type: preprint
Abstract: This document contains detailed information about the prompts used in the experimental process discussed in the paper "Toward Automating Agent-based Model Generation: A Benchmark for Model Extraction using Question-Answering Techniques". The paper aims to utilize Question-answering (QA) models to extract the necessary information to implement Agent-based Modeling (ABM) from conceptual models. It presents the extracted information in formats that can be read by both humans and computers (i.e., JavaScript Object Notation (JSON)), enabling manual use by humans and auto-code generation by Large Language Models (LLM).
Source: arXiv (Cornell University)
Authors: Khatami, Siamak, Frantz, Christopher
Institution: Norwegian University of Science and Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4405094940