Evaluating Prompting Strategies for Spatial Planning in Mixed-Use Architecture: A Case Study of Kalkbreite, Zürich
Abstract
In this paper, we will explore how different prompts affect the performance of LLMs when it comes to creating spatial plans in architecture. There are four strategies used in this study: one-shot prompting, few-shot prompting, chain-of-thought prompting, and meta-prompting. These methods are tested by presenting the same example of a mixed-use building, which is graded according to efficiency, complexity, accuracy, and effort involved in each case. It has been found that all these methods can provide a reasonably accurate output, although the quality and efficiency vary. Meta-prompting and chain-of-thought prompting are found to be quite detailed, while one-shot prompting is quick yet lacks detail. Few-shot and chain-of-thought prompting enable users to control their outputs through an interactive process, but this method takes up considerable time and effort.
Keywords: Artificial Intelligence, Prompt Engineering, Computational Design, Spatial Planning
DOI: 10.54941/ahfe1008161
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