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Smart system to generate the optimal authorized bounding volume
- Source :
- Open House International, Open House International, Open House International Association, 2021, 46 (3), pp.432-443. ⟨10.1108/OHI-02-2021-0039⟩
- Publication Year :
- 2021
- Publisher :
- HAL CCSD, 2021.
-
Abstract
- PurposeThe overall functioning of this system is based on two approaches: construction and supervision. The first is conducted entirely by the machine, and the second requires the intervention of the designer to collaborate with the machine. The morphological translation of urban rules is sometimes contradictory and may require additional external relevance to urban rules. Designer arbitration assists the artificial intelligence (AI) in accomplishing this task and solving the problem.Design/methodology/approachThis paper provides a method of computational design in generating the optimal authorized bounding volume which uses the best target values of morphological urban rules. It examines an intelligent system, adopting the multi-agent approach, which aims to control and increase urban densification by optimizing morphological urban rules. The process of the system is interactive and iterative. It allows collaboration and exchange between the machine and the designer. This paper is adopting and developing a new approach to resolve the distributed constraint optimization problem in generating the authorized bounding volume. The resolution is not limited to an automatic volume generation from urban rules, but also involves the production of multiple optimal-solutions conditioned both by urban constraints and relevance chosen by the designer. The overall functioning of this system is based on two approaches: construction and supervision. The first is conducted entirely by the machine and the second requires the intervention of the designer to collaborate with the machine. The morphological translation of urban rules is sometimes contradictory and may require additional external relevance to urban rules. Designer arbitration assists the AI in accomplishing this task and solving the problem. The human-computer collaboration is achieved at the appropriate time and relies on the degree of constraint satisfaction. This paper shows and analyses interactions with the machine during the building generation process. It presents different cases of application and discusses the relationship between relevance and constraints satisfaction. This topic can inform a chosen urban densification strategy by assisting a typology of the optimal authorized bounding volume.FindingsThe human-computer collaboration is achieved at the appropriate time and relies on the degree of constraint satisfaction with fitness function.Originality/valueThe resolution of the distributed constraint optimization problem is not limited to an automatic generation of urban rules, but involves also the production of multiple optimal ABV conditioned both by urban constraints as well as relevance, chosen by the designer.
- Subjects :
- Artificial intelligence
Computer science
Distributed computing
Distributed constraint optimization
Geography, Planning and Development
0211 other engineering and technologies
02 engineering and technology
Authorized Bounding Volume
Morphological urban rules
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
021105 building & construction
Architecture
[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]
Built environment tectonics and technologies
Smart system
[SHS.ARCHI]Humanities and Social Sciences/Architecture, space management
[SDE.IE]Environmental Sciences/Environmental Engineering
Multi-agent system
021107 urban & regional planning
[SDE.ES]Environmental Sciences/Environmental and Society
Human-computer interaction
Urban Studies
Bounding volume
[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]
Subjects
Details
- Language :
- English
- ISSN :
- 01682601
- Database :
- OpenAIRE
- Journal :
- Open House International, Open House International, Open House International Association, 2021, 46 (3), pp.432-443. ⟨10.1108/OHI-02-2021-0039⟩
- Accession number :
- edsair.doi.dedup.....86b334ad527aed8108e81407447c6fd7