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September 10, 2025Open Access

Machine Learning-Based Design Systems for Holistic Landscape Integration of Traditional Settlements: Evolutionary Models Applied at Vikos Gorge

Key Points

A machine learning-based design system enhances integration of traditional settlements with the environment.
The research highlights a shift from human-centered design to systems that continuously adapt based on environmental feedback.
The study examines the relationship between human elements and natural surroundings, focusing on innovation in urban architecture.
Developing computational tools for architecture can lead to a better balance between modern design and traditional culture.

Abstract

The advancement of technology implies a simultaneous evolution of design tools, particularly in architecture and in the field of urban design. A new challenge has emerged, enabling a more holistic approach that considers the balance between environmental conditions and anthropogenic factors influencing the design process. This shift, coupled with the integration of Machine Learning systems that are continuously receiving feedback, is reshaping core design principles, moving away from a human-centered focus. The purpose of this research is to explore the innovative perspectives that such technological advancements offer, analyzing the dynamic relationships between the human subject and the natural elements. The goal is to develop a design system that can adapt to respective fields of study and anticipate changes based on input data. The traditional architecture initiated a dialog with contemporary culture through the application of emerging computational tools.

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