(untitled) (Collection of scientific works «Scientific Problems of Architecture and Urban Planning» | ODABA, 2026)
The article presents an information–algorithmic axis of classification for architectural AI tools and shows how AI-driven systems, platforms, and workflows can be systematically organised by two parameters: the information dimension (types and sources of data used and produced) and the algorithmic dimension (families of AI/algorithmic methods). On the information side, the framework distinguishes geometric and spatial data, environmental and performance data, programmatic and regulatory information, user- and sensor-derived streams, and higher-level domain knowledge. On the algorithmic side, it spans rule-based and parametric approaches, evolutionary optimisation, agent-based models, classical machine learning, deep neural networks, generative models, reinforcement learning, and large foundation models. Using a matrix of I–A pairings, the article maps a set of contemporary tools and research prototypes in architecture and urbanism, covering generative design platforms, performanceoriented surrogates, code-compliance assistants, immersive evaluation workflows, structural design agents, and city-scale GeoAI systems. The analysis reveals dense clusters such as geometry-driven generative design and performance prediction, as well as under-explored combinations, including context-aware reinforcement learning and programme-to-geometry generative pipelines. The discussion highlights typical trade-offs between data requirements, algorithmic complexity, interpretability, and the role of human oversight. The information–algorithmic axis complements functional and lifecycle classifications and provides a practical lens for understanding data needs and computational behaviour of architectural AI tools. It can inform the selection and chaining of tools in digital workflows, the design of curricula that prepare architects to work with data and algorithms, and the identification of promising gaps for future research and development.