| id |
caadria2025_684 |
| authors |
Boim, Anna, Kalnitz, Paul R. and Sprecher, Aaron |
| year |
2025 |
| title |
From Emergence to Complexity: Simulating evolution of self-generated urban road network |
| source |
Dagmar Reinhardt, Christiane M. Herr, Anastasia Globa, Jielin Chen, Taro ?Narahara, Nicolas Rogeau (eds.), ARCHITECTURAL INFORMATICS - Proceedings of the 30th CAADRIA Conference, Tokyo, 22-29 March 2025, Volume 4, pp. 141–150 |
| summary |
This study explores the use of evolutionary algorithms to uncover the developmental pathways that shape the form of non-planned settlements over time. By teaching eNEAT, an evolutionary model, to learn self-organization patterns, the research aims to capture the evolution of urban landscapes as interconnected processes within a dynamic system, addressing the limitations of prior methods. The ongoing experiment presented in this paper applies eNEAT to simulate the growth of a non-planned road network, demonstrating its potential to model urban patterns through iterative generations. Preliminary results showed improvement in convergence rate over time, indicating that while further development is needed to achieve higher consistency with the ground truth, eNEAT offers a promising framework for understanding and predicting the evolution of non-planned urban fabrics, with the ability to adapt and integrate additional data layers. Leveraging the potential of evolutionary algorithms, this research reimagines urban design in the digital age, integrating computational models to navigate the coexistence of planned and emergent urban forms. |
| keywords |
Evolutionary algorithms, machine learning, non-planned settlements, temporal simulations, urban networks |
| series |
CAADRIA |
| full text |
 file.pdf (1,198,995 bytes) |
| references |
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