Innovations in Design & Decision Support Systems in Architecture and Urban Planning

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Bignon, G. Bi, B. On the Notion of Level in Architecture; M. Bax, H. Geographical Information Systems. Rodrigues, L. Souza, J. Higuchi, A. Author Index. Du kanske gillar. Permanent Record Edward Snowden Inbunden. Year of the Monkey Patti Smith Inbunden.

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Chanel Daniele Bott Inbunden. Inbunden Engelska, Spara som favorit. Skickas inom vardagar. As editors of this volume we would like to express our gratitude to the contributing authors who have delivered these highly relevant and inspiring chapters and to the international scientific committee for their help in the review and editing. Special thanks go to our colleagues Mandy van de Sande, Marlyn Aretz, and Leo van Veghel, who were great in organising the conference and took care of everything that made it a pleasant and comfortable event.

Passar bra ihop. Ladda ned. The five chapters in the third section are also on multi-agent systems, but relate to processes of urban development.

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Part two, on design support systems, starts with a section containing five chapters on the management and deployment of design knowledge. The second section contains three chapters discussing tools and strategies for urban decision-making. The first three chapters in section three discuss the possibilities to allow designer interaction with systems that automate design; the fourth chapter presents a solution for the exchange of building information models.

The final section is on virtual environments, with one chapter focusing on urban environments and another on design environments.


The following paragraphs provide a brief summary of the two parts and the seven sections of this volume. The nature of these tools and systems and their stage of development largely reflect more general trends in science. The first generation of models and systems was often based on statistical input-output relations, weak in terms of behav- ioural principles, large scale, and implicitly or explicitly based on the assumption of perfect and full information in the sense that uncertainty was rarely addressed.

Next, with the increasing popularity of chaos theory, the often complex models were replaced with simple or even simplistic models, based on the belief that simple rules and principles are sufficient to generate complex emerging patterns.

Decision Support Systems in Urban Planning

Cellular automata models constitute a good example. More recently, realizing that urban developments but also plans are the result of interactive or even strategic choices of actors involved in the process, scholars started to work on multi-agent systems, some still based on simple, primarily data-driven principles, other trying to significantly improve the behavioural foundations of the models.

These approaches should not be viewed as successions, but rather are still further developed and applied and still constitute frameworks within which different groups are making progress.

This is also reflected in the papers on design and decision support systems in urban planning that were selected for the first part of this volume. In terms of its key features, it is a conventional approach, put into a new jacket. The authors argue that the system has proven its usefulness.

This is also illustrated by another paper on the same model system. A series of sustainability indicators is derived from the model, allowing the user to evaluate alternative plans in terms of these indicators. In addition, a cost-benefit analysis is conducted. This is illustrated by the model itself, but also by experiences gained in the application that is described in this chapter. In addition, they provide a useful overview of a few existing methods for deriving these rules from empirical data or for eliciting expert knowledge. In particular, arguing that transition probabilities are required at the level of building lots and assuming raster data are available, they develop an improved method to estimate such transition probabilities and propose a method to estimate time series changes in the land use transition probabilities, based on the concept of land use utility.

Interpretation and correct judgement of the qualities of a landscape on the basis of two-dimensional land use maps is a difficult task, even for experienced professionals. Particularly the implications of changes to land use cannot easily be perceived from maps.

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They describe two approaches. One is to insert 3D iconic exemplary representations of new land uses into the land use model.


The other is to use 3D components of GIS tools to represent existing land use features. The combination of both approaches seems to lead to promising results, but to achieve them technically on a large scale still proofs to be very challenging. Multi-Agent Models for Movement Simulation Multi-agent models are potentially relevant to simulate movement. Models of pedestrian movement have recently regained considerable interest, especially due to safety, crowding and feasibility issues.

The advantage of their approach is that both interactions between pedestrians and the interaction between pedestrians and their environment can be easily incorporated in the model. Good examples of 3D visualization to portray simulation dynamics are also presented.

The system is illustrated using an underground station as an example. It could be argued that the behavioural mechanisms underlying pedestrian behaviour in this context are relatively simple in the sense that pedestrians probably wish to leave the station as quickly as possible or go to the train in a convenient way. Behavioural principles in large-scale retail environments are considerably more complex.

Pedestrians may be utilitarian or hedonic, some may behave in rational ways, others in satisfying ways, reflecting bounded rationality. There will also be significant heterogeneity in terms of shopping aims, agendas, environmental knowledge, etc.

The approach goes beyond genetic programming in that not only parameters are fitted but also the best functional form of the model can in principle be derived. A potential limitation of the suggested approach is that it requires parallel computing, especially for large- large-scale applications.


Their system, called SCALE, is a platform supporting digital data and a media suitable for advertising and city guide information. Space-tags are virtual objects that can be accessed only within a limited area and for a limited time. The functionality of the system is described and illustrated using a small sample. Another type of movement is traffic. Their multi-agent system is divided into three subsystems: i one is concerned urban traffic simulation, with agents representing vehicles, bicycles, pede- strians, etc; ii another is with the information system service behaviours, with agents modelling employees and the computing system of the information system itself, and iii the third one is dedicated to the decision support objective of the system.

Traveller behaviour is modelled using questionnaire data based on Taguchi experimental designs, while belief theory is employed to identifying preference distributions of transport modes. An example involving students illustrates the potential of the system. Their contribution is exceptional and extends the typical application area of multi-agent models and traffic simulation.

Multi-Agent Models for Urban Development Multi-agent models have not only become of interest to simulate movement patterns, such as for example pedestrians, but also to simulate urban change processes. A few such examples are included in this volume. Different agents represent the actors in this process homeowners, landlords, tenants and developers. Hitaka, M. Murakami et al. Borsboom-van Beurden, R. Hoogerwerf, A. Crowd Modeling and Simulation.

Scale A street case library for environmental design with agent interfaces. Jean-Marie Boussier, P.

Table of contents

Estraillier, D. Sarramia, M. Gentrification Waves in the Inner-City of Milan. Zhou, A. Kondo, A. Cartagena Gordillo, K. Decision-Making on Olympic Urban Development. Usage of Planning Support Systems. Sieving Pebbles and Growing Profiles. Concept Formation in a Design Optimization Tool.