Multi-agent framework for schema-guided reasoning and tool-augmented interaction with IFC models

Gao, Yan, Hu, Fuji, Chai, Chengzhang ORCID: https://orcid.org/0000-0001-6911-8048, Weng, Yiwei and Li, Haijiang ORCID: https://orcid.org/0000-0001-6326-8133 2026. Multi-agent framework for schema-guided reasoning and tool-augmented interaction with IFC models. Automation in Construction 186 , 106888. 10.1016/j.autcon.2026.106888

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Abstract

Despite recent advances in large language model (LLM)-based agents, their applications to schema-guided reasoning and interaction with Building Information Modelling (BIM) data remain limited. This paper presents IFC-Agent, a tool-augmented multi-agent framework that enables natural language querying, reasoning, and modification of Industry Foundation Classes (IFC) models. The framework integrates schema-guided traversal with LLM-driven dynamic tool composition to achieve interpretable and scalable reasoning workflows. An adaptive dual-mode execution strategy combines asynchronous parallel execution with exploration–aggregation reasoning, while a dual-memory mechanism ensures operational efficiency and semantic consistency. A prototype system was developed using LangChain and validated on benchmark IFC queries. Case studies demonstrate strong performance in field querying, multi-hop reasoning, coordinate transformation, and IFC graph construction. Comparative evaluation with recent graph-based and LLM-assisted BIM frameworks highlights IFC-Agent's advantages in schema-guided reasoning and natural language interaction, establishing a practical foundation for explainable and automated BIM workflows.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Engineering
Publisher:	Elsevier
ISSN:	0926-5805
Date of First Compliant Deposit:	27 March 2026
Date of Acceptance:	11 March 2026
Last Modified:	27 Mar 2026 11:00
URI:	https://orca.cardiff.ac.uk/id/eprint/186047

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