TY  - CHAP
A1  - Chirkin, Artem
A1  - König, Reinhard
T1  - Concept of Interactive Machine Learning in Urban Design Problems : proceedings
N2  - 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.
KW  - MCDM
KW  - interactive machine learning
KW  - urban design
KW  - multiple-criteria optimization
KW  - Stadtgestaltung
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-26000
UR  - http://dl.acm.org/citation.cfm?id=2898365
SP  - 10
EP  - 13
PB  - ACM New York, NY, USA
CY  - San Jose, CA, USA
ER  -