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Institut
- Junior-Professur Computational Architecture (7) (entfernen)
Schlagworte
- Stadtgestaltung (2)
- Architektur (1)
- CAD (1)
- Cognitive design computing (1)
- Computational Urban Design (1)
- Computational urban planning (1)
- Design-simulation-loop (1)
- Distributed computing (1)
- Emotion (1)
- GIS (1)
Erscheinungsjahr
- 2016 (7) (entfernen)
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.