ResearchResearch paperReasoning & Planning · Large Language Models · Robotics & Embodied AI1 source · Oct 19, 2026

Automated Brick Schema Knowledge Graph Completion Across Buildings

We observe that as Brick models are knowledge graphs, inferring missing relations is naturally posed as a knowledge graph completion problem.

The Brick schema represents building equipment, sensors, spaces, and the relationships between them as typed, multi-relational graphs, providing machine-readable metadata that supports generalizable control applications.
To the best of our knowledge, this is the first application of knowledge graph completion to Brick model generation.
We compare three methods, gradient-boosted trees, Pairwise Brick Relation Ranking, and CompGCN, on the relations feeds, hasPart, and hasPoint, which account for the majority of the schematic-reading work in building a Brick model by hand.
Models are evaluated on held-out MORTAR buildings and out-of-distribution Kaggle and Building Time Series data.

[1]Automated Brick Schema Knowledge Graph Completion Across Buildings
arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 10:06 PM
We observe that as Brick models are knowledge graphs, inferring missing relations is naturally posed as a knowledge graph completion problem.
The Brick schema represents building equipment, sensors, spaces, and the relationships between them as typed, multi-relational graphs, providing machine-readable metadata that supports generalizable control applications.

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