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supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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id caadria2013_034
authors Arenas, Ubaldo and José Manuel Falcón
year 2013
title ALOPS Constructive Systems – Towards the Design and Fabrication of Unsupervised Learning Construction Systems
source Open Systems: Proceedings of the 18th International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2013) / Singapore 15-18 May 2013, pp. 905-914
doi https://doi.org/10.52842/conf.caadria.2013.905
summary In this paper we explore the concept and design guidelines for an Autonomous Learning Oriented Proto System (ALOPS), a construction system designed to enhance its own performance through time. Our research has been focused on the fabrication of a prototype for a porous wall system which reacts to light intensities by closing or opening its apertures. Taking that aim, we used a combination of robotics, programing, and material behaviour to endow the system with the capacity to record reactions towards encountered sets of conditions during its active energy periods, allowing the system to use this knowledge database to evolve autonomously by feeding this information back into the computation process. This approach in construction systems opens up the architectural design processes to address the creation of digital memory structures rather than complex algorithms in order to operate specific functions. With this development, the architect could think of architectures constantly evolving by learning from their environments as well as of users forming symbiotic and behavioural bonds with the emergent spatial personalities, thus affecting the underpinning relationships between architecture, user and context.  
wos WOS:000351496100093
keywords erformance architecture, Unsupervised learning, Machine learning 
series CAADRIA
email
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