@inproceedings{ChirkinKoenig,
  author    = {Chirkin, Artem and K{\"o}nig, Reinhard},
  title     = {Concept of Interactive Machine Learning in Urban Design Problems : proceedings},
  publisher = {ACM New York, NY, USA},
  address   = {San Jose, CA, USA},
  doi       = {10.25643/bauhaus-universitaet.2600},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20160622-26000},
  pages     = {10 -- 13},
  abstract  = {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.},
  subject      = {Stadtgestaltung},
  language  = {en}
}