@article{Birkholz,
  author    = {Birkholz, Marie Luise},
  title     = {M{\"a}chtiger Boden. Essay {\"u}ber den Versuch, einen Staatsapparat zu erlaufen},
  series = {sub\urban. Zeitschrift f{\"u}r Kritische Stadtforschung},
  volume    = {2015},
  journal   = {sub\urban. Zeitschrift f{\"u}r Kritische Stadtforschung},
  number    = {Band 3, Heft 2},
  publisher = {ub\urban e.V.},
  address   = {Berlin},
  doi       = {10.36900/suburban.v3i2.200},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220112-45591},
  pages     = {141 -- 154},
  abstract  = {Der Text folgt in essayistischer Form einem Spaziergang durch das politische Zentrum Bras{\´i}lias in Brasilien. Die Konzentration liegt auf der Gestaltung des Bodens. Wie ist die Planhauptstadt „vom Reißbrett" in der Horizontalen gestaltet? Wie sehen repr{\"a}sentative Pl{\"a}tze einer Stadt aus, die vor allem f{\"u}r Autos gebaut worden ist? Der forschende Blick liegt auf dem erlebten Ist-Zustand und wird assoziativ mit Ergebnissen der Forschungsarbeit aus Deutschland reflektiert. „M{\"a}chtiger Boden" entstand als Satellit zur aktuellen Forschung der Autorin im Rahmen eines Aufenthalts in Brasilien.},
  subject      = {Brasilia},
  language  = {de}
}
@article{KleinKoenig,
  author    = {Klein, Bernhard and K{\"o}nig, Reinhard},
  title     = {Computational Urban Planning: Using the Value Lab as Control Center},
  series = {FCL Magazine, Special Issue Simulation Platform},
  journal   = {FCL Magazine, Special Issue Simulation Platform},
  doi       = {10.25643/bauhaus-universitaet.2601},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20160622-26011},
  pages     = {38 -- 45},
  abstract  = {Urban planning involves many aspects and various disciplines, demanding an asynchronous planning approach. The level of complexity rises with each aspect to be considered and makes it difficult to find universally satisfactory solutions. To improve this situation we propose a new approach, which complement traditional design methods with a computational urban plan- ning method that can fulfil formalizable design requirements automatically. Based on this approach we present a design space exploration framework for complex urban planning projects. For a better understanding of the idea of design space exploration, we introduce the concept of a digital scout which guides planners through the design space and assists them in their creative explorations. The scout can support planners during manual design by informing them about potential im- pacts or by suggesting different solutions that fulfill predefined quality requirements. The planner can change flexibly between a manually controlled and a completely automated design process. The developed system is presented using an exemplary urban planning scenario on two levels from the street layout to the placement of building volumes. Based on Self-Organizing Maps we implemented a method which makes it possible to visualize the multi-dimensional solution space in an easily analysable and comprehensible form.},
  subject      = {Stadtgestaltung},
  language  = {en}
}
@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}
}