TY - CHAP A1 - König, Reinhard A1 - Bauriedel, Christian T1 - Computer-generated Urban Structures T2 - Proceedings of the Generative Art Conference N2 - How does it come to particular structure formations in the cities and which strengths play a role in this process? On which elements can the phenomena be reduced to find the respective combination rules? How do general principles have to be formulated to be able to describe the urban processes so that different structural qualities can be produced? With the aid of mathematic methods, models based on four basic levels are generated in the computer, through which the connections between the elements and the rules of their interaction can be examined. Conclusions on the function of developing processes and the further urban origin can be derived. KW - Computational Urban Design Y1 - 2004 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160623-26090 SP - 1 EP - 10 CY - Milan, Italy ER - TY - CHAP A1 - König, Reinhard A1 - Müller, Daniela T1 - Simulating the development of residential areas of the city of Vienna from 1888 to 2001 T2 - Compendium of Abstracts of the 8th International Conference on Urban Planning and Environment (UPE8) N2 - The structure and development of cities can be seen and evaluated from different points of view. By replicating the growth or shrinkage of a city using historical maps depicting different time states, we can obtain momentary snapshots of the dynamic mechanisms of the city. An examination of how these snapshots change over the course of time and a comparison of the different static time states reveals the various interdependencies of population density, technical infrastructure and the availability of public transport facilities. Urban infrastructure and facilities are not distributed evenly across the city – rather they are subject to different patterns and speeds of spread over the course of time and follow different spatial and temporal regularities. The reasons and underlying processes that cause the transition from one state to another result from the same recurring but varyingly pronounced hidden forces and their complex interactions. Such forces encompass a variety of economic, social, cultural and ecological conditions whose respective weighting defines the development of a city in general. Urban development is, however, not solely a product of the different spatial distribution of economic, legal or social indicators but also of the distribution of infrastructure. But to what extent is the development of a city affected by the changing provision of infrastructure? As KW - urban simulation KW - Simulation Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-26066 CY - Kaiserslautern, Germany ER - TY - CHAP A1 - König, Reinhard A1 - Treyer, Lukas A1 - Schmitt, Gerhard T1 - Graphical smalltalk with my optimization system for urban planning tasks T2 - 31st eCAADe Conference – Volume 2 N2 - Based on the description of a conceptual framework for the representation of planning problems on various scales, we introduce an evolutionary design optimization system. This system is exemplified by means of the generation of street networks with locally defined properties for centrality. We show three different scenarios for planning requirements and evaluate the resulting structures with respect to the requirements of our framework. Finally the potentials and challenges of the presented approach are discussed in detail. KW - Städtebau KW - Architektur KW - Design optimization KW - evolutionary multi-criteria optimization KW - generative system integration KW - interactive planning support system Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160121-25171 SP - 195 EP - 203 PB - TU Delft CY - Delft, Netherlands ER - TY - CHAP A1 - Hijazi, Ihab Hamzi A1 - Hussein, M. H. A1 - König, Reinhard T1 - Enabling geo-design: Evaluating the capacity of 3D city model to support thermal design in building T2 - 9th 3DGeoInfo Conference N2 - Enabling geo-design: Evaluating the capacity of 3D city model to support thermal design in building KW - Informatik KW - bim; cad; citygml; gbxml; thermal design Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160118-25089 CY - Dubai, UAE ER - TY - CHAP A1 - König, Reinhard A1 - Schneider, Sven A1 - Hijazi, Ihab Hamzi A1 - Li, Xin A1 - Bielik, Martin A1 - Schmitt, Gerhard A1 - Donath, Dirk T1 - Using geo statistical analysis to detect similarities in emotional responses of urban walkers to urban space T2 - Sixth International Conference on Design Computing and Cognition (DCC14) N2 - Using geo statistical analysis to detect similarities in emotional responses of urban walkers to urban space KW - Städtebau Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160121-25146 ER - TY - CHAP A1 - Treyer, Lukas A1 - Klein, Bernhard A1 - König, Reinhard A1 - Meixner, Christine T1 - Lightweight urban computation interchange (LUCI) system T2 - Proceedings N2 - In this paper we introduce LUCI, a Lightweight Urban Calculation Interchange system, designed to bring the advantages of a calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware. The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views. The described system architecture is accompanied by two exemplary use cases that have been used to test and further develop our concepts and implementations. KW - Luci KW - distributed computing KW - middleware Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-25982 UR - https://e-pub.uni-weimar.de/opus4/frontdoor/index/index/docId/2504 PB - FOSS4G CY - Seoul, South Korea ER - TY - CHAP A1 - König, Reinhard ED - Martens, Bob ED - Wurzer, G, Gabriel ED - Grasl, Tomas ED - Lorenz, Wolfgang ED - Schaffranek, Richard T1 - CPlan: An Open Source Library for Computational Analysis and Synthesis T2 - 33rd eCAADe Conference N2 - Some caad packages offer additional support for the optimization of spatial configurations, but the possibilities for applying optimization are usually limited either by the complexity of the data model or by the constraints of the underlying caad system. Since we missed a system that allows to experiment with optimization techniques for the synthesis of spatial configurations, we developed a collection of methods over the past years. This collection is now combined in the presented open source library for computational planning synthesis, called CPlan. The aim of the library is to provide an easy to use programming framework with a flat learning curve for people with basic programming knowledge. It offers an extensible structure that allows to add new customized parts for various purposes. In this paper the existing functionality of the CPlan library is described. KW - Architektur KW - Computer KW - CAAD KW - cplan KW - CAD Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160118-25037 SP - 245 EP - 250 PB - Vienna University of Technology CY - Vienna ER - TY - CHAP A1 - Treyer, Lukas A1 - Klein, Bernhard A1 - König, Reinhard A1 - Meixner, Christine T1 - Lightweight urban computation interchange (LUCI) system T2 - FOSS4G 2015 Conference N2 - In this paper we introduce LUCI, a Lightweight Urban Calculation Interchange system, designed to bring the advantages of a calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware. The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views. The described system architecture is accompanied by two exemplary use cases that have been used to test and further develop our concepts and implementations. KW - Architektur KW - Informatik KW - Geographie KW - Luci KW - distributed computing KW - middleware Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160118-25042 PB - FOSS4G CY - Seoul, South Korea ER - 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 - TY - CHAP A1 - König, Reinhard A1 - Schmitt, Gerhard ED - Szoboszlai, Mihály T1 - Backcasting and a new way of command in computational design : Proceedings T2 - CAADence in Architecture Conference N2 - It's not uncommon that analysis and simulation methods are used mainly to evaluate finished designs and to proof their quality. Whereas the potential of such methods is to lead or control a design process from the beginning on. Therefore, we introduce a design method that move away from a “what-if” forecasting philosophy and increase the focus on backcasting approaches. We use the power of computation by combining sophisticated methods to generate design with analysis methods to close the gap between analysis and synthesis of designs. For the development of a future-oriented computational design support we need to be aware of the human designer’s role. A productive combination of the excellence of human cognition with the power of modern computing technology is needed. We call this approach “cognitive design computing”. The computational part aim to mimic the way a designer’s brain works by combining state-of-the-art optimization and machine learning approaches with available simulation methods. The cognition part respects the complex nature of design problems by the provision of models for human-computation interaction. This means that a design problem is distributed between computer and designer. In the context of the conference slogan “back to command”, we ask how we may imagine the command over a cognitive design computing system. We expect that designers will need to let go control of some parts of the design process to machines, but in exchange they will get a new powerful command on complex computing processes. This means that designers have to explore the potentials of their role as commanders of partially automated design processes. In this contribution we describe an approach for the development of a future cognitive design computing system with the focus on urban design issues. The aim of this system is to enable an urban planner to treat a planning problem as a backcasting problem by defining what performance a design solution should achieve and to automatically query or generate a set of best possible solutions. This kind of computational planning process offers proof that the designer meets the original explicitly defined design requirements. A key way in which digital tools can support designers is by generating design proposals. Evolutionary multi-criteria optimization methods allow us to explore a multi-dimensional design space and provide a basis for the designer to evaluate contradicting requirements: a task urban planners are faced with frequently. We also reflect why designers will give more and more control to machines. Therefore, we investigate first approaches learn how designers use computational design support systems in combination with manual design strategies to deal with urban design problems by employing machine learning methods. By observing how designers work, it is possible to derive more complex artificial solution strategies that can help computers make better suggestions in the future. KW - Cognitive design computing KW - machine learning KW - backcasting KW - design synthesis KW - evolutionary optimization KW - CAD Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-25996 SP - 15 EP - 25 CY - Budapest ER - TY - CHAP A1 - König, Reinhard A1 - Varoudis, Tasos T1 - Spatial Optimizations: Merging depthmapX , spatial graph networks and evolutionary design in Grasshopper T2 - Proceedings of ecaade 34: Complexity & Simplicity N2 - In the Space Syntax community, the standard tool for computing all kinds of spatial graph network measures is depthmapX (Turner, 2004; Varoudis, 2012). The process of evaluating many design variants of networks is relatively complicated, since they need to be drawn in a separated CAD system, exported and imported in depthmapX via dxf file format. This procedure disables a continuous integration into a design process. Furthermore, the standalone character of depthmapX makes it impossible to use its network centrality calculation for optimization processes. To overcome this limitations, we present in this paper the first steps of experimenting with a Grasshopper component (reference omitted until final version) that can access the functions of depthmapX and integrate them into Grasshopper/Rhino3D. Here the component is implemented in a way that it can be used directly for an evolutionary algorithm (EA) implemented in a Python scripting component in Grasshopper KW - depthmapx KW - python KW - optimization KW - space syntax KW - grasshopper Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-26040 SP - 1 EP - 6 CY - Oulu, Finland ER -