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Concept of Interactive Machine Learning in Urban Design Problems : proceedings

  • This work presents a concept of interactive machine learning in a human design process. An urban design problem is viewed as a multiple-criteria optimization problem. The outlined feature of an urban design problem is the dependence of a design goal on a context of the problem. We model the design goal as a randomized fitness measure that depends on the context. In terms of multiple-criteria decision analysis (MCDA), the defined measure corresponds to a subjective expected utility of a user. In the first stage of the proposed approach we let the algorithm explore a design space using clustering techniques. The second stage is an interactive design loop; the user makes a proposal, then the program optimizes it, gets the user’s feedback and returns back the control over the application interface.

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Document Type:Conference Proceeding
Author: Artem Chirkin, Prof. Dr. Reinhard KönigORCiDGND
DOI (Cite-Link):https://doi.org/10.25643/bauhaus-universitaet.2600Cite-Link
URN (Cite-Link):https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20160622-26000Cite-Link
Publisher:ACM New York, NY, USA
Place of publication:San Jose, CA, USA
Date of Publication (online):2016/06/21
Year of first Publication:2016
Release Date:2016/06/22
Institutes:Fakultät Architektur und Urbanistik [bis 2014 Fakultät Architektur] / Juniorprofessur Computational Architecture
First Page:10
Last Page:13
Tag:MCDM; interactive machine learning; multiple-criteria optimization; urban design
GND Keyword:Stadtgestaltung
Dewey Decimal Classification:000 Informatik, Informationswissenschaft, allgemeine Werke
BKL-Classification:54 Informatik
Licence (German):License Logo Creative Commons 4.0 - Namensnennung (CC BY 4.0)