Cumincad : CUMINCAD Papers : Search Results

CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

PDF papers
References

Hits 1 to 20 of 3609

Reformat results as: short short into frame detailed detailed into frame

_id	c54a
authors	Welch, W. and Witkin, A.
year	1992
title	Variational surface modeling
source	Computer Graphics, 26, Proceedings, SIGGRAPH 92
summary	We present a newapproach to interactivemodeling of freeform surfaces. Instead of a fixed mesh of control points, the model presented to the user is that of an infinitely malleable surface, with no fixed controls. The user is free to apply control points and curves which are then available as handles for direct manipulation. The complexity of the surface's shape may be increased by adding more control points and curves, without apparent limit. Within the constraints imposed by the controls, the shape of the surface is fully determined by one or more simple criteria, such as smoothness. Our method for solving the resulting constrained variational optimization problems rests on a surface representation scheme allowing nonuniform subdivision of B-spline surfaces. Automatic subdivision is used to ensure that constraints are met, and to enforce error bounds. Efficient numerical solutions are obtained by exploiting linearities in the problem formulation and the representation.
series	journal paper
last changed	2003/04/23 15:50

_id	ga0007
id	ga0007
authors	Coates, Paul and Miranda, Pablo
year	2000
title	Swarm modelling. The use of Swarm Intelligence to generate architectural form
source	International Conference on Generative Art
summary	.neither the human purposes nor the architect's method are fully known in advance. Consequently, if this interpretation of the architectural problem situation is accepted, any problem-solving technique that relies on explicit problem definition, on distinct goal orientation, on data collection, or even on non-adaptive algorithms will distort the design process and the human purposes involved.' Stanford Anderson, "Problem-Solving and Problem-Worrying". The works concentrates in the use of the computer as a perceptive device, a sort of virtual hand or "sense", capable of prompting an environment. From a set of data that conforms the environment (in this case the geometrical representation of the form of the site) this perceptive device is capable of differentiating and generating distinct patterns in its behavior, patterns that an observer has to interpret as meaningful information. As Nicholas Negroponte explains referring to the project GROPE in his Architecture Machine: 'In contrast to describing criteria and asking the machine to generate physical form, this exercise focuses on generating criteria from physical form.' 'The onlooking human or architecture machine observes what is "interesting" by observing GROPE's behavior rather than by receiving the testimony that this or that is "interesting".' The swarm as a learning device. In this case the work implements a Swarm as a perceptive device. Swarms constitute a paradigm of parallel systems: a multitude of simple individuals aggregate in colonies or groups, giving rise to collaborative behaviors. The individual sensors can't learn, but the swarm as a system can evolve in to more stable states. These states generate distinct patterns, a result of the inner mechanics of the swarm and of the particularities of the environment. The dynamics of the system allows it to learn and adapt to the environment; information is stored in the speed of the sensors (the more collisions, the slower) that acts as a memory. The speed increases in the absence of collisions and so providing the system with the ability to forget, indispensable for differentiation of information and emergence of patterns. The swarm is both a perceptive and a spatial phenomenon. For being able to Interact with an environment an observer requires some sort of embodiment. In the case of the swarm, its algorithms for moving, collision detection, and swarm mechanics conform its perceptive body. The way this body interacts with its environment in the process of learning and differentiation of spatial patterns constitutes also a spatial phenomenon. The enactive space of the Swarm. Enaction, a concept developed by Maturana and Varela for the description of perception in biological terms, is the understanding of perception as the result of the structural coupling of an environment and an observer. Enaction does not address cognition in the currently conventional sense as an internal manipulation of extrinsic 'information' or 'signals', but as the relation between environment and observer and the blurring of their identities. Thus, the space generated by the swarm is an enactive space, a space without explicit description, and an invention of the swarm-environment structural coupling. If we consider a gestalt as 'Some property -such as roundness- common to a set of sense data and appreciated by organisms or artefacts' (Gordon Pask), the swarm is also able to differentiate space 'gestalts' or spaces of some characteristics, such as 'narrowness', or 'fluidness' etc. Implicit surfaces and the wrapping algorithm. One of the many ways of describing this space is through the use of implicit surfaces. An implicit surface may be imagined as an infinitesimally thin band of some measurable quantity such as color, density, temperature, pressure, etc. Thus, an implicit surface consists of those points in three-space that satisfy some particular requirement. This allows as to wrap the regions of space where a difference of quantity has been produced, enclosing the spaces in which some particular events in the history of the Swarm have occurred. The wrapping method allows complex topologies, such as manifoldness in one continuous surface. It is possible to transform the information generated by the swarm in to a landscape that is the result of the particular reading of the site by the swarm. Working in real time. Because of the complex nature of the machine, the only possible way to evaluate the resulting behavior is in real time. For this purpose specific applications had to be developed, using OpenGL for the Windows programming environment. The package consisted on translators from DXF format to a specific format used by these applications and viceversa, the Swarm "engine", a simulated parallel environment, and the Wrapping programs, to generate the implicit surfaces. Different versions of each had been produced, in different stages of development of the work.
series	other
email
more	http://www.generativeart.com/
last changed	2003/08/07 17:25

_id	78ca
authors	Friedland, P. (Ed.)
year	1985
title	Special Section on Architectures for Knowledge-Based Systems
source	CACM (28), 9, September
summary	A fundamental shift in the preferred approach to building applied artificial intelligence (AI) systems has taken place since the late 1960s. Previous work focused on the construction of general-purpose intelligent systems; the emphasis was on powerful inference methods that could function efficiently even when the available domain-specific knowledge was relatively meager. Today the emphasis is on the role of specific and detailed knowledge, rather than on reasoning methods.The first successful application of this method, which goes by the name of knowledge-based or expert-system research, was the DENDRAL program at Stanford, a long-term collaboration between chemists and computer scientists for automating the determination of molecular structure from empirical formulas and mass spectral data. The key idea is that knowledge is power, for experts, be they human or machine, are often those who know more facts and heuristics about a domain than lesser problem solvers. The task of building an expert system, therefore, is predominantly one of teaching" a system enough of these facts and heuristics to enable it to perform competently in a particular problem-solving context. Such a collection of facts and heuristics is commonly called a knowledge base. Knowledge-based systems are still dependent on inference methods that perform reasoning on the knowledge base, but experience has shown that simple inference methods like generate and test, backward-chaining, and forward-chaining are very effective in a wide variety of problem domains when they are coupled with powerful knowledge bases. If this methodology remains preeminent, then the task of constructing knowledge bases becomes the rate-limiting factor in expert-system development. Indeed, a major portion of the applied AI research in the last decade has been directed at developing techniques and tools for knowledge representation. We are now in the third generation of such efforts. The first generation was marked by the development of enhanced AI languages like Interlisp and PROLOG. The second generation saw the development of knowledge representation tools at AI research institutions; Stanford, for instance, produced EMYCIN, The Unit System, and MRS. The third generation is now producing fully supported commercial tools like KEE and S.1. Each generation has seen a substantial decrease in the amount of time needed to build significant expert systems. Ten years ago prototype systems commonly took on the order of two years to show proof of concept; today such systems are routinely built in a few months. Three basic methodologies-frames, rules, and logic-have emerged to support the complex task of storing human knowledge in an expert system. Each of the articles in this Special Section describes and illustrates one of these methodologies. "The Role of Frame-Based Representation in Reasoning," by Richard Fikes and Tom Kehler, describes an object-centered view of knowledge representation, whereby all knowldge is partitioned into discrete structures (frames) having individual properties (slots). Frames can be used to represent broad concepts, classes of objects, or individual instances or components of objects. They are joined together in an inheritance hierarchy that provides for the transmission of common properties among the frames without multiple specification of those properties. The authors use the KEE knowledge representation and manipulation tool to illustrate the characteristics of frame-based representation for a variety of domain examples. They also show how frame-based systems can be used to incorporate a range of inference methods common to both logic and rule-based systems.""Rule-Based Systems," by Frederick Hayes-Roth, chronicles the history and describes the implementation of production rules as a framework for knowledge representation. In essence, production rules use IF conditions THEN conclusions and IF conditions THEN actions structures to construct a knowledge base. The autor catalogs a wide range of applications for which this methodology has proved natural and (at least partially) successful for replicating intelligent behavior. The article also surveys some already-available computational tools for facilitating the construction of rule-based knowledge bases and discusses the inference methods (particularly backward- and forward-chaining) that are provided as part of these tools. The article concludes with a consideration of the future improvement and expansion of such tools.The third article, "Logic Programming, " by Michael Genesereth and Matthew Ginsberg, provides a tutorial introduction to the formal method of programming by description in the predicate calculus. Unlike traditional programming, which emphasizes how computations are to be performed, logic programming focuses on the what of objects and their behavior. The article illustrates the ease with which incremental additions can be made to a logic-oriented knowledge base, as well as the automatic facilities for inference (through theorem proving) and explanation that result from such formal descriptions. A practical example of diagnosis of digital device malfunctions is used to show how significantand complex problems can be represented in the formalism.A note to the reader who may infer that the AI community is being split into competing camps by these three methodologies: Although each provides advantages in certain specific domains (logic where the domain can be readily axiomatized and where complete causal models are available, rules where most of the knowledge can be conveniently expressed as experiential heuristics, and frames where complex structural descriptions are necessary to adequately describe the domain), the current view is one of synthesis rather than exclusivity. Both logic and rule-based systems commonly incorporate frame-like structures to facilitate the representation of large amounts of factual information, and frame-based systems like KEE allow both production rules and predicate calculus statements to be stored within and activated from frames to do inference. The next generation of knowledge representation tools may even help users to select appropriate methodologies for each particular class of knowledge, and then automatically integrate the various methodologies so selected into a consistent framework for knowledge. "
series	journal paper
last changed	2003/04/23 15:14

_id	ga0010
id	ga0010
authors	Moroni, A., Zuben, F. Von and Manzolli, J.
year	2000
title	ArTbitrariness in Music
source	International Conference on Generative Art
summary	Evolution is now considered not only powerful enough to bring about the biological entities as complex as humans and conciousness, but also useful in simulation to create algorithms and structures of higher levels of complexity than could easily be built by design. In the context of artistic domains, the process of human-machine interaction is analyzed as a good framework to explore creativity and to produce results that could not be obtained without this interaction. When evolutionary computation and other computational intelligence methodologies are involved, every attempt to improve aesthetic judgement we denote as ArTbitrariness, and is interpreted as an interactive iterative optimization process. ArTbitrariness is also suggested as an effective way to produce art through an efficient manipulation of information and a proper use of computational creativity to increase the complexity of the results without neglecting the aesthetic aspects [Moroni et al., 2000]. Our emphasis will be in an approach to interactive music composition. The problem of computer generation of musical material has received extensive attention and a subclass of the field of algorithmic composition includes those applications which use the computer as something in between an instrument, in which a user "plays" through the application's interface, and a compositional aid, which a user experiments with in order to generate stimulating and varying musical material. This approach was adopted in Vox Populi, a hybrid made up of an instrument and a compositional environment. Differently from other systems found in genetic algorithms or evolutionary computation, in which people have to listen to and judge the musical items, Vox Populi uses the computer and the mouse as real-time music controllers, acting as a new interactive computer-based musical instrument. The interface is designed to be flexible for the user to modify the music being generated. It explores evolutionary computation in the context of algorithmic composition and provides a graphical interface that allows to modify the tonal center and the voice range, changing the evolution of the music by using the mouse[Moroni et al., 1999]. A piece of music consists of several sets of musical material manipulated and exposed to the listener, for example pitches, harmonies, rhythms, timbres, etc. They are composed of a finite number of elements and basically, the aim of a composer is to organize those elements in an esthetic way. Modeling a piece as a dynamic system implies a view in which the composer draws trajectories or orbits using the elements of each set [Manzolli, 1991]. Nonlinear iterative mappings are associated with interface controls. In the next page two examples of nonlinear iterative mappings with their resulting musical pieces are shown.The mappings may give rise to attractors, defined as geometric figures that represent the set of stationary states of a non-linear dynamic system, or simply trajectories to which the system is attracted. The relevance of this approach goes beyond music applications per se. Computer music systems that are built on the basis of a solid theory can be coherently embedded into multimedia environments. The richness and specialty of the music domain are likely to initiate new thinking and ideas, which will have an impact on areas such as knowledge representation and planning, and on the design of visual formalisms and human-computer interfaces in general. Above and bellow, Vox Populi interface is depicted, showing two nonlinear iterative mappings with their resulting musical pieces. References [Manzolli, 1991] J. Manzolli. Harmonic Strange Attractors, CEM BULLETIN, Vol. 2, No. 2, 4 -- 7, 1991. [Moroni et al., 1999] Moroni, J. Manzolli, F. Von Zuben, R. Gudwin. Evolutionary Computation applied to Algorithmic Composition, Proceedings of CEC99 - IEEE International Conference on Evolutionary Computation, Washington D. C., p. 807 -- 811,1999. [Moroni et al., 2000] Moroni, A., Von Zuben, F. and Manzolli, J. ArTbitration, Las Vegas, USA: Proceedings of the 2000 Genetic and Evolutionary Computation Conference Workshop Program – GECCO, 143 -- 145, 2000.
series	other
email
more	http://www.generativeart.com/
last changed	2003/08/07 17:25

_id	ga0026
id	ga0026
authors	Ransen, Owen F.
year	2000
title	Possible Futures in Computer Art Generation
source	International Conference on Generative Art
summary	Years of trying to create an "Image Idea Generator" program have convinced me that the perfect solution would be to have an artificial artistic person, a design slave. This paper describes how I came to that conclusion, realistic alternatives, and briefly, how it could possibly happen. 1. The history of Repligator and Gliftic 1.1 Repligator In 1996 I had the idea of creating an “image idea generator”. I wanted something which would create images out of nothing, but guided by the user. The biggest conceptual problem I had was “out of nothing”. What does that mean? So I put aside that problem and forced the user to give the program a starting image. This program eventually turned into Repligator, commercially described as an “easy to use graphical effects program”, but actually, to my mind, an Image Idea Generator. The first release came out in October 1997. In December 1998 I described Repligator V4 [1] and how I thought it could be developed away from simply being an effects program. In July 1999 Repligator V4 won the Shareware Industry Awards Foundation prize for "Best Graphics Program of 1999". Prize winners are never told why they won, but I am sure that it was because of two things: 1) Easy of use 2) Ease of experimentation "Ease of experimentation" means that Repligator does in fact come up with new graphics ideas. Once you have input your original image you can generate new versions of that image simply by pushing a single key. Repligator is currently at version 6, but, apart from adding many new effects and a few new features, is basically the same program as version 4. Following on from the ideas in [1] I started to develop Gliftic, which is closer to my original thoughts of an image idea generator which "starts from nothing". The Gliftic model of images was that they are composed of three components: 1. Layout or form, for example the outline of a mandala is a form. 2. Color scheme, for example colors selected from autumn leaves from an oak tree. 3. Interpretation, for example Van Gogh would paint a mandala with oak tree colors in a different way to Andy Warhol. There is a Van Gogh interpretation and an Andy Warhol interpretation. Further I wanted to be able to genetically breed images, for example crossing two layouts to produce a child layout. And the same with interpretations and color schemes. If I could achieve this then the program would be very powerful. 1.2 Getting to Gliftic Programming has an amazing way of crystalising ideas. If you want to put an idea into practice via a computer program you really have to understand the idea not only globally, but just as importantly, in detail. You have to make hard design decisions, there can be no vagueness, and so implementing what I had decribed above turned out to be a considerable challenge. I soon found out that the hardest thing to do would be the breeding of forms. What are the "genes" of a form? What are the genes of a circle, say, and how do they compare to the genes of the outline of the UK? I wanted the genotype representation (inside the computer program's data) to be directly linked to the phenotype representation (on the computer screen). This seemed to be the best way of making sure that bred-forms would bare some visual relationship to their parents. I also wanted symmetry to be preserved. For example if two symmetrical objects were bred then their children should be symmetrical. I decided to represent shapes as simply closed polygonal shapes, and the "genes" of these shapes were simply the list of points defining the polygon. Thus a circle would have to be represented by a regular polygon of, say, 100 sides. The outline of the UK could easily be represented as a list of points every 10 Kilometers along the coast line. Now for the important question: what do you get when you cross a circle with the outline of the UK? I tried various ways of combining the "genes" (i.e. coordinates) of the shapes, but none of them really ended up producing interesting shapes. And of the methods I used, many of them, applied over several "generations" simply resulted in amorphous blobs, with no distinct family characteristics. Or rather maybe I should say that no single method of breeding shapes gave decent results for all types of images. Figure 1 shows an example of breeding a mandala with 6 regular polygons: Figure 1 Mandala bred with array of regular polygons I did not try out all my ideas, and maybe in the future I will return to the problem, but it was clear to me that it is a non-trivial problem. And if the breeding of shapes is a non-trivial problem, then what about the breeding of interpretations? I abandoned the genetic (breeding) model of generating designs but retained the idea of the three components (form, color scheme, interpretation). 1.3 Gliftic today Gliftic Version 1.0 was released in May 2000. It allows the user to change a form, a color scheme and an interpretation. The user can experiment with combining different components together and can thus home in on an personally pleasing image. Just as in Repligator, pushing the F7 key make the program choose all the options. Unlike Repligator however the user can also easily experiment with the form (only) by pushing F4, the color scheme (only) by pushing F5 and the interpretation (only) by pushing F6. Figures 2, 3 and 4 show some example images created by Gliftic. Figure 2 Mandala interpreted with arabesques Figure 3 Trellis interpreted with "graphic ivy" Figure 4 Regular dots interpreted as "sparks" 1.4 Forms in Gliftic V1 Forms are simply collections of graphics primitives (points, lines, ellipses and polygons). The program generates these collections according to the user's instructions. Currently the forms are: Mandala, Regular Polygon, Random Dots, Random Sticks, Random Shapes, Grid Of Polygons, Trellis, Flying Leap, Sticks And Waves, Spoked Wheel, Biological Growth, Chequer Squares, Regular Dots, Single Line, Paisley, Random Circles, Chevrons. 1.5 Color Schemes in Gliftic V1 When combining a form with an interpretation (described later) the program needs to know what colors it can use. The range of colors is called a color scheme. Gliftic has three color scheme types: 1. Random colors: Colors for the various parts of the image are chosen purely at random. 2. Hue Saturation Value (HSV) colors: The user can choose the main hue (e.g. red or yellow), the saturation (purity) of the color scheme and the value (brightness/darkness) . The user also has to choose how much variation is allowed in the color scheme. A wide variation allows the various colors of the final image to depart a long way from the HSV settings. A smaller variation results in the final image using almost a single color. 3. Colors chosen from an image: The user can choose an image (for example a JPG file of a famous painting, or a digital photograph he took while on holiday in Greece) and Gliftic will select colors from that image. Only colors from the selected image will appear in the output image. 1.6 Interpretations in Gliftic V1 Interpretation in Gliftic is best decribed with a few examples. A pure geometric line could be interpreted as: 1) the branch of a tree 2) a long thin arabesque 3) a sequence of disks 4) a chain, 5) a row of diamonds. An pure geometric ellipse could be interpreted as 1) a lake, 2) a planet, 3) an eye. Gliftic V1 has the following interpretations: Standard, Circles, Flying Leap, Graphic Ivy, Diamond Bar, Sparkz, Ess Disk, Ribbons, George Haite, Arabesque, ZigZag. 1.7 Applications of Gliftic Currently Gliftic is mostly used for creating WEB graphics, often backgrounds as it has an option to enable "tiling" of the generated images. There is also a possibility that it will be used in the custom textile business sometime within the next year or two. The real application of Gliftic is that of generating new graphics ideas, and I suspect that, like Repligator, many users will only understand this later. 2. The future of Gliftic, 3 possibilties Completing Gliftic V1 gave me the experience to understand what problems and opportunities there will be in future development of the program. Here I divide my many ideas into three oversimplified possibilities, and the real result may be a mix of two or all three of them. 2.1 Continue the current development "linearly" Gliftic could grow simply by the addition of more forms and interpretations. In fact I am sure that initially it will grow like this. However this limits the possibilities to what is inside the program itself. These limits can be mitigated by allowing the user to add forms (as vector files). The user can already add color schemes (as images). The biggest problem with leaving the program in its current state is that there is no easy way to add interpretations. 2.2 Allow the artist to program Gliftic It would be interesting to add a language to Gliftic which allows the user to program his own form generators and interpreters. In this way Gliftic becomes a "platform" for the development of dynamic graphics styles by the artist. The advantage of not having to deal with the complexities of Windows programming could attract the more adventurous artists and designers. The choice of programming language of course needs to take into account the fact that the "programmer" is probably not be an expert computer scientist. I have seen how LISP (an not exactly easy artificial intelligence language) has become very popular among non programming users of AutoCAD. If, to complete a job which you do manually and repeatedly, you can write a LISP macro of only 5 lines, then you may be tempted to learn enough LISP to write those 5 lines. Imagine also the ability to publish (and/or sell) "style generators". An artist could develop a particular interpretation function, it creates images of a given character which others find appealing. The interpretation (which runs inside Gliftic as a routine) could be offered to interior designers (for example) to unify carpets, wallpaper, furniture coverings for single projects. As Adrian Ward [3] says on his WEB site: "Programming is no less an artform than painting is a technical process." Learning a computer language to create a single image is overkill and impractical. Learning a computer language to create your own artistic style which generates an infinite series of images in that style may well be attractive. 2.3 Add an artificial conciousness to Gliftic This is a wild science fiction idea which comes into my head regularly. Gliftic manages to surprise the users with the images it makes, but, currently, is limited by what gets programmed into it or by pure chance. How about adding a real artifical conciousness to the program? Creating an intelligent artificial designer? According to Igor Aleksander [1] conciousness is required for programs (computers) to really become usefully intelligent. Aleksander thinks that "the line has been drawn under the philosophical discussion of conciousness, and the way is open to sound scientific investigation". Without going into the details, and with great over-simplification, there are roughly two sorts of artificial intelligence: 1) Programmed intelligence, where, to all intents and purposes, the programmer is the "intelligence". The program may perform well (but often, in practice, doesn't) and any learning which is done is simply statistical and pre-programmed. There is no way that this type of program could become concious. 2) Neural network intelligence, where the programs are based roughly on a simple model of the brain, and the network learns how to do specific tasks. It is this sort of program which, according to Aleksander, could, in the future, become concious, and thus usefully intelligent. What could the advantages of an artificial artist be? 1) There would be no need for programming. Presumbably the human artist would dialog with the artificial artist, directing its development. 2) The artificial artist could be used as an apprentice, doing the "drudge" work of art, which needs intelligence, but is, anyway, monotonous for the human artist. 3) The human artist imagines "concepts", the artificial artist makes them concrete. 4) An concious artificial artist may come up with ideas of its own. Is this science fiction? Arthur C. Clarke's 1st Law: "If a famous scientist says that something can be done, then he is in all probability correct. If a famous scientist says that something cannot be done, then he is in all probability wrong". Arthur C Clarke's 2nd Law: "Only by trying to go beyond the current limits can you find out what the real limits are." One of Bertrand Russell's 10 commandments: "Do not fear to be eccentric in opinion, for every opinion now accepted was once eccentric" 3. References 1. "From Ramon Llull to Image Idea Generation". Ransen, Owen. Proceedings of the 1998 Milan First International Conference on Generative Art. 2. "How To Build A Mind" Aleksander, Igor. Wiedenfeld and Nicolson, 1999 3. "How I Drew One of My Pictures: or, The Authorship of Generative Art" by Adrian Ward and Geof Cox. Proceedings of the 1999 Milan 2nd International Conference on Generative Art.
series	other
email
more	http://www.generativeart.com/
last changed	2003/08/07 17:25

_id	cc51
authors	Schnier, T. and Gero, J.S
year	1997
title	Dominant and recessive genes in evolutionary systems applied to spatial reasoning
source	A. Sattar (Ed.), Advanced Topics in Artificial Intelligence: 10th Australian Joint Conference on Artificial Intelligence AI97 Proceedings, Springer, Heidelberg, pp. 127-136
summary	Learning genetic representation has been shown to be a useful tool in evolutionary computation. It can reduce the time required to find solutions and it allows the search process to be biased towards more desirable solutions. Learn-ing genetic representation involves the bottom-up creation of evolved genes from either original (basic) genes or from other evolved genes and the introduction of those into the population. The evolved genes effectively protect combinations of genes that have been found useful from being disturbed by the genetic operations (cross-over, mutation). However, this protection can rapidly lead to situations where evolved genes in-terlock in such a way that few or no genetic operations are possible on some genotypes. To prevent the interlocking previous implementations only allow the creation of evolved genes from genes that are direct neighbours on the genotype and therefore form continuous blocks. In this paper it is shown that the notion of dominant and recessive genes can be used to remove this limitation. Using more than one gene at a single location makes it possible to construct genetic operations that can separate interlocking evolved genes. This allows the use of non-continuous evolved genes with only minimal violations of the protection of evolved genes from those operations. As an example, this paper shows how evolved genes with dominant and re-cessive genes can be used to learn features from a set of Mondrian paintings. The representation can then be used to create new designs that contain features of the examples. The Mondrian paintings can be coded as a tree, where every node represents a rectangle division, with values for direction, position, line-width and colour. The modified evolutionary operations allow the system to cre-ate non-continuous evolved genes, for example associate two divisions with thin lines, without specifying other values. Analysis of the behaviour of the system shows that about one in ten genes is a dominant/recessive gene pair. This shows that while dominant and recessive genes are important to allow the use of non-continuous evolved genes, they do not occur often enough to seriously violate the protection of evolved genes from genetic operations.
keywords	Evolutionary Systems, Genetic Representations
series	other
email
last changed	2003/04/06 07:24

_id	ascaad2023_055
id	ascaad2023_055
authors	Yildiz, Berfin; Çagdaº, Gülen; Zincir, lbrahim
year	2023
title	Deep Architectural Floor Plan Generation: An Approach for Open-Planned Residential Spaces
source	C+++: Computation, Culture, and Context – Proceedings of the 11th International Conference of the Arab Society for Computation in Architecture, Art and Design (ASCAAD), University of Petra, Amman, Jordan [Hybrid Conference] 7-9 November 2023, pp. 685-705.
summary	This research investigates the collaborative potential of artificial intelligence and deep learning in architectural design, focusing on comprehending and synthesizing the complex relationships within architectural floor plans. The primary question addressed is whether deep learning algorithms can effectively generate residential floor plans characterized by open-planned architectural spaces. To address this, the study introduces a novel model employing generative adversarial networks (GANs) to create open-planned layouts within residential floor plans. Open-planned spaces refers to a design approach in which interior spaces within a structure are intentionally devoid of traditional partitioning elements such as walls and doors. The layout typically features interconnected and visually continuous spaces that flow seamlessly from one area to another. The research contributes by addressing a gap in the literature through the exploration of functional space differentiations within residences characterized by open plan arrangement without walls as a separating element. Furthermore, the study extends this investigation by applying the proposed methodology to angular and circular plans as well as orthogonal plan sets. In the generative model created with GAN, the space functions are defined and labelled with the RGB color codes assigned to them. For the RGB label representation of the open-plan layout, gradient coloring prepared. By using this method, it was investigated whether the generation of the plans was realized with an open-plan structure by examining the gradient generation results. In the generative model, the footprint of the plan is given as an input for the algorithm to produce by adhering to an outer boundary. Accordingly, it is aimed to learn how the network can be arranged within the given boundaries. The Pix2pix method was used for this generative model, which is defined as the problem of obtaining images from images. The model results advance the AI-driven understanding of architectural design by providing architects with an innovative tool to explore open-plan spatial solutions.
series	ASCAAD
email
last changed	2024/02/13 14:34

_id	328d
authors	Bassanino, May Nahab and Brown, Andre
year	1999
title	Computer Generated Architectural Images: A Comparative Study
doi	https://doi.org/10.52842/conf.ecaade.1999.552
source	Architectural Computing from Turing to 2000 [eCAADe Conference Proceedings / ISBN 0-9523687-5-7] Liverpool (UK) 15-17 September 1999, pp. 552-556
summary	This work is part of a long term research programme (Brown and Horton, 1992; Brown and Nahab, 1996; Bassanino, 1999) in which tests and studies have been carried out on various groups of people to investigate their reaction to, and interpretation of different forms of architectural representation. In the work described here a range of architectural schemes were presented using particular representational techniques and media. An experiment was then undertaken on two different groups; architects and lay people. They were presented with a number of schemes displayed using the various techniques and media. The responses are summarised and some comments are made on the effect of computers on perceiving architecture and on communicating architectural ideas arising from an analysis of the responses.
keywords	Subject, Image Type, Presentation Technique, Medium, SD Scales, Factors
series	eCAADe
email
last changed	2022/06/07 07:54

_id	898a
authors	Bay, J.H.
year	2002
title	Cognitive Biases and Precedent Knowledge in Human and Computer-Aided Design Thinking
doi	https://doi.org/10.52842/conf.caadria.2002.213
source	CAADRIA 2002 [Proceedings of the 7th International Conference on Computer Aided Architectural Design Research in Asia / ISBN 983-2473-42-X] Cyberjaya (Malaysia) 18–20 April 2002, pp. 213-220
summary	Cognitive biases (illusions) and potential errors can occur when using precedent knowledge for analogical, pre-parametric and qualitative design thinking. This paper refers largely to part of a completed research (Bay 2001) on how heuristic biases, discussed by Tversky and Kahneman (1982) in cognitive psychology, can affect judgement and learning of facts from precedents in architectural design, made explicit using a kernel of conceptual system (Tzonis et. al., 1978) and a framework of architectural representation (Tzonis 1992). These are used here to consider how such illusions and errors may be transferred to computer aided design thinking.
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	eabb
authors	Boeykens, St. Geebelen, B. and Neuckermans, H.
year	2002
title	Design phase transitions in object-oriented modeling of architecture
doi	https://doi.org/10.52842/conf.ecaade.2002.310
source	Connecting the Real and the Virtual - design e-ducation [20th eCAADe Conference Proceedings / ISBN 0-9541183-0-8] Warsaw (Poland) 18-20 September 2002, pp. 310-313
summary	The project IDEA+ aims to develop an “Integrated Design Environment for Architecture”. Its goal is providing a tool for the designer-architect that can be of assistance in the early-design phases. It should provide the possibility to perform tests (like heat or cost calculations) and simple simulations in the different (early) design phases, without the need for a fully detailed design or remodeling in a different application. The test for daylighting is already in development (Geebelen, to be published). The conceptual foundation for this design environment has been laid out in a scheme in which different design phases and scales are defined, together with appropriate tests at the different levels (Neuckermans, 1992). It is a translation of the “designerly” way of thinking of the architect (Cross, 1982). This conceptual model has been translated into a “Core Object Model” (Hendricx, 2000), which defines a structured object model to describe the necessary building model. These developments form the theoretical basis for the implementation of IDEA+ (both the data structure & prototype software), which is currently in progress. The research project addresses some issues, which are at the forefront of the architect’s interest while designing with CAAD. These are treated from the point of view of a practicing architect.
series	eCAADe
email
last changed	2022/06/07 07:52

_id	cf5c
authors	Carpenter, B.
year	1992
title	The logic of typed feature structures with applications to unificationgrammars, logic programs and constraint resolution
source	Cambridge Tracts in Theoretical Computer Science, Cambridge University Press
summary	This book develops the theory of typed feature structures, a new form of data structure that generalizes both the first-order terms of logic programs and feature-structures of unification-based grammars to include inheritance, typing, inequality, cycles and intensionality. It presents a synthesis of many existing ideas into a uniform framework, which serves as a logical foundation for grammars, logic programming and constraint-based reasoning systems. Throughout the text, a logical perspective is adopted that employs an attribute-value description language along with complete equational axiomatizations of the various systems of feature structures. Efficiency concerns are discussed and complexity and representability results are provided. The application of feature structures to phrase structure grammars is described and completeness results are shown for standard evaluation strategies. Definite clause logic programs are treated as a special case of phrase structure grammars. Constraint systems are introduced and an enumeration technique is given for solving arbitrary attribute-value logic constraints. This book with its innovative approach to data structures will be essential reading for researchers in computational linguistics, logic programming and knowledge representation. Its self-contained presentation makes it flexible enough to serve as both a research tool and a textbook.
series	other
last changed	2003/04/23 15:14

_id	2312
authors	Carrara, G., Kalay Y.E. and Novembri, G.
year	1992
title	Multi-modal Representation of Design Knowledge
doi	https://doi.org/10.52842/conf.ecaade.1992.055
source	CAAD Instruction: The New Teaching of an Architect? [eCAADe Conference Proceedings] Barcelona (Spain) 12-14 November 1992, pp. 55-66
summary	Explicit representation of design knowledge is needed if scientific methods are to be applied in design research, and if computers are to be used in the aid of design education and practice. The representation of knowledge in general, and design knowledge in particular, have been the subject matter of computer science, design methods, and computer-aided design research for quite some time. Several models of design knowledge representation have been developed over the last 30 years, addressing specific aspects of the problem. This paper describes a different approach to design knowledge representation that recognizes the multimodal nature of design knowledge. It uses a variety of computational tools to encode different kinds of design knowledge, including the descriptive (objects), the prescriptive (goals) and the operational (methods) kinds. The representation is intended to form a parsimonious, communicable and presentable knowledge-base that can be used as a tool for design research and education as well as for CAAD.
keywords	Design Methods, Design Process Goals, Knowledge Representation, Semantic Networks
series	eCAADe
email
last changed	2022/06/07 07:55

_id	6ef4
authors	Carrara, Gianfranco and Kalay, Yehuda E.
year	1992
title	Multi-Model Representation of Design Knowledge
doi	https://doi.org/10.52842/conf.acadia.1992.077
source	Mission - Method - Madness [ACADIA Conference Proceedings / ISBN 1-880250-01-2] 1992, pp. 77-88
summary	Explicit representation of design knowledge is needed if scientific methods are to be applied in design research, and if comPuters are to be used in the aid of design education and practice. The representation of knowledge in general, and design knowledge in particular, have been the subject matter of computer science, design methods, and computer- aided design research for quite some time. Several models of design knowledge representation have been developed over the last 30 years, addressing specific aspects of the problem. This paper describes a different approach to design knowledge representation that recognizes the Multi-modal nature of design knowledge. It uses a variety of computational tools to encode different kinds of design knowledge, including the descriptive (objects), the prescriptive (goals) and the operational (methods) kinds. The representation is intended to form a parsimonious, communicable and presentable knowledge-base that can be used as a tool for design research and education as well as for CAAD.
keywords	Design Methods, Design Process, Goals, Knowledge Representation, Semantic Networks
series	ACADIA
email
last changed	2022/06/07 07:55

_id	ddss9209
id	ddss9209
authors	De Gelder, J.T. and Lucardie, G.L.
year	1993
title	Knowledge and data modelling in cad/cam applications
source	Timmermans, Harry (Ed.), Design and Decision Support Systems in Architecture (Proceedings of a conference held in Mierlo, the Netherlands in July 1992), ISBN 0-7923-2444-7
summary	Modelling knowledge and data in CAD/CAM applications is complex because different goals and contexts have to be taken into account. This complexity makes particular demands upon representation formalisms. Today many modelling tools are based on record structures. By analyzing the requirements for a product model of a portal structure in steel, this paper shows that in many situations record structures are not well suited as a representation formalism for storing knowledge and data in CAD/CAM applications. This is illustrated by performing a knowledge-level analysis of the knowledge and data generated in the design and manufacturing process of a portal structure in steel.
series	DDSS
last changed	2003/08/07 16:36

_id	e51d
authors	Fazio, P., Bedard, C. and Gowri, K.
year	1992
title	Constraints for Generating Building Envelope Design Alternatives
source	New York: John Wiley & Sons, 1992. pp. 145-155 : charts. includes bibliography
summary	The building envelope design process involves selecting materials and constructional types for envelope components. Many different materials need to be combined together for wall and roof assemblies to meet the various performance requirements such as thermal efficiency, cost, acoustic and fire resistances. The number of performance attributes to be considered in the design process is large. Lack of information, time limitations and the large number of feasible design alternatives generally force the designer to rely on past experience and practical judgement to make rapid design decisions. Current work at the Centre for Buildings Studies focuses on the development of knowledge-based synthesis and evaluation techniques for reducing the problems of information handling and decision making in building envelope design. The generation of design alternatives is viewed as a search process that identifies feasible combinations of building envelope components satisfying a set of performance requirements, material compatibility, practicality of design, etc. This paper discusses knowledge acquisition and representation issues involved in the definition of constraints to guide the generation of feasible combinations of envelope components
keywords	envelope, knowledge base, knowledge acquisition, representation, performance, design, structures, architecture, evaluation
series	CADline
last changed	2003/06/02 14:41

_id	83f7
authors	Fenves, Stephen J., Flemming, Ulrich and Hendrickson, Craig (et al)
year	1992
title	Performance Evaluation in an Integrated Software Environment for Building Design and Construction Planning
source	New York: John Wiley & Sons, 1992. pp. 159-169 : ill. includes bibliography
summary	In this paper the authors describe the role of performance evaluation in the Integrated Software Environment for Building Design and Construction Planning (IBDE), which is a testbed for examining integration issues in the same domain. Various processes in IBDE deal with the spatial configuration, structural design, and construction planning of high-rise office buildings. Performance evaluations occur within these processes based on different representation schemes and control mechanisms for the handling of performance knowledge. Within this multiprocess environment, opportunities also exist for performance evaluation across disciplines through design critics
keywords	evaluation, performance, integration, systems, building, design, construction, architecture, planning, structures, representation, control
series	CADline
email
last changed	2003/06/02 10:24

_id	ecaade03_473_175_flanagan_neu
id	ecaade03_473_175_flanagan_neu
authors	Flanagan, Robert H.
year	2003
title	Generative Logic in Digital Design
doi	https://doi.org/10.52842/conf.ecaade.2003.473
source	Digital Design [21th eCAADe Conference Proceedings / ISBN 0-9541183-1-6] Graz (Austria) 17-20 September 2003, pp. 473-484
summary	This exploration of early-stage, architectural design pedagogy is in essence, a record of an ongoing transformation underway in architecture, from its practice in the art of geometry of space to its practice in the art of geometry of space-time. A selected series of student experiments, from 1992 to the present, illustrate a progression in architectural theory, from Pythagorean concepts of mathematics and geometry, to the symbolic representation of space and non-linear time in film. The dimensional expansion of space, from xyz to xyz+t (time), represents a tactical and strategic opportunity to incorporate multisensory design variables in architectural practice, as well as in its pedagogy.
keywords	Generative; process; derivative; logic; systemic
series	eCAADe
email
last changed	2022/06/07 07:51

_id	68c8
authors	Flemming, U., Coyne, R. and Fenves, S. (et al.)
year	1994
title	SEED: A Software Environment to Support the Early Phases in Building Design
source	Proceeding of IKM '94, Weimar, Germany, pp. 5-10
summary	The SEED project intends to develop a software environment that supports the early phases in building design (Flemming et al., 1993). The goal is to provide support, in principle, for the preliminary design of buildings in all aspects that can gain from computer support. This includes using the computer not only for analysis and evaluation, but also more actively for the generation of designs, or more accurately, for the rapid generation of design representations. A major motivation for the development of SEED is to bring the results of two multi-generational research efforts focusing on `generative' design systems closer to practice: 1. LOOS/ABLOOS, a generative system for the synthesis of layouts of rectangles (Flemming et al., 1988; Flemming, 1989; Coyne and Flemming, 1990; Coyne, 1991); 2. GENESIS, a rule-based system that supports the generation of assemblies of 3-dimensional solids (Heisserman, 1991; Heisserman and Woodbury, 1993). The rapid generation of design representations can take advantage of special opportunities when it deals with a recurring building type, that is, a building type dealt with frequently by the users of the system. Design firms - from housing manufacturers to government agencies - accumulate considerable experience with recurring building types. But current CAD systems capture this experience and support its reuse only marginally. SEED intends to provide systematic support for the storing and retrieval of past solutions and their adaptation to similar problem situations. This motivation aligns aspects of SEED closely with current work in Artificial Intelligence that focuses on case-based design (see, for example, Kolodner, 1991; Domeshek and Kolodner, 1992; Hua et al., 1992).
series	other
email
last changed	2003/04/23 15:14

_id	7ce5
authors	Gal, Shahaf
year	1992
title	Computers and Design Activities: Their Mediating Role in Engineering Education
source	Sociomedia, ed. Edward Barret. MIT Press
summary	Sociomedia: With all the new words used to describe electronic communication (multimedia, hypertext, cyberspace, etc.), do we need another one? Edward Barrett thinks we do; hence, he coins the term "sociomedia." It is meant to displace a computing economy in which technicity is hypostasized over sociality. Sociomedia, a compilation of twenty-five articles on the theory, design and practice of educational multimedia and hypermedia, attempts to re-value the communicational face of computing. Value, of course, is "ultimately a social construct." As such, it has everything to do with knowledge, power, education and technology. The projects discussed in this book represent the leading edge of electronic knowledge production in academia (not to mention major funding) and are determining the future of educational media. For these reasons, Sociomedia warrants close inspection. Barrett's introduction sets the tone. For him, designing computer media involves hardwiring a mechanism for the social construction of knowledge (1). He links computing to a process of social and communicative interactivity for constructing and desseminating knowledge. Through a mechanistic mapping of the university as hypercontext (a huge network that includes classrooms as well as services and offices), Barrett models intellectual work in such a way as to avoid "limiting definitions of human nature or human development." Education, then, can remain "where it should be--in the human domain (public and private) of sharing ideas and information through the medium of language." By leaving education in a virtual realm (where we can continue to disagree about its meaning and execution), it remains viral, mutating and contaminating in an intellectually healthy way. He concludes that his mechanistic model, by means of its reductionist approach, preserves value (7). This "value" is the social construction of knowledge. While I support the social orientation of Barrett's argument, discussions of value are related to power. I am not referring to the traditional teacher-student power structure that is supposedly dismantled through cooperative and constructivist learning strategies. The power to be reckoned with in the educational arena is foundational, that which (pre)determines value and the circulation of knowledge. "Since each of you reading this paragraph has a different perspective on the meaning of 'education' or 'learning,' and on the processes involved in 'getting an education,' think of the hybris in trying to capture education in a programmable function, in a displayable object, in a 'teaching machine'" (7). Actually, we must think about that hybris because it is, precisely, what informs teaching machines. Moreover, the basic epistemological premises that give rise to such productions are too often assumed. In the case of instructional design, the episteme of cognitive sciences are often taken for granted. It is ironic that many of the "postmodernists" who support electronic hypertextuality seem to have missed Jacques Derrida's and Michel Foucault's "deconstructions" of the epistemology underpinning cognitive sciences (if not of epistemology itself). Perhaps it is the glitz of the technology that blinds some users (qua developers) to the belief systems operating beneath the surface. Barrett is not guilty of reactionary thinking or politics; he is, in fact, quite in line with much American deconstructive and postmodern thinking. The problem arises in that he leaves open the definitions of "education," "learning" and "getting an education." One cannot engage in the production of new knowledge without orienting its design, production and dissemination, and without negotiating with others' orientations, especially where largescale funding is involved. Notions of human nature and development are structural, even infrastructural, whatever the medium of the teaching machine. Although he addresses some dynamics of power, money and politics when he talks about the recession and its effects on the conference, they are readily visible dynamics of power (3-4). Where does the critical factor of value determination, of power, of who gets what and why, get mapped onto a mechanistic model of learning institutions? Perhaps a mapping of contributors' institutions, of the funding sources for the projects showcased and for participation in the conference, and of the disciplines receiving funding for these sorts of projects would help visualize the configurations of power operative in the rising field of educational multimedia. Questions of power and money notwithstanding, Barrett's introduction sets the social and textual thematics for the collection of essays. His stress on interactivity, on communal knowledge production, on the society of texts, and on media producers and users is carried foward through the other essays, two of which I will discuss. Section I of the book, "Perspectives...," highlights the foundations, uses and possible consequences of multimedia and hypertextuality. The second essay in this section, "Is There a Class in This Text?," plays on the robust exchange surrounding Stanley Fish's book, Is There a Text in This Class?, which presents an attack on authority in reading. The author, John Slatin, has introduced electronic hypertextuality and interaction into his courses. His article maps the transformations in "the content and nature of work, and the workplace itself"-- which, in this case, is not industry but an English poetry class (25). Slatin discovered an increase of productive and cooperative learning in his electronically- mediated classroom. For him, creating knowledge in the electronic classroom involves interaction between students, instructors and course materials through the medium of interactive written discourse. These interactions lead to a new and persistent understanding of the course materials and of the participants' relation to the materials and to one another. The work of the course is to build relationships that, in my view, constitute not only the meaning of individual poems, but poetry itself. The class carries out its work in the continual and usually interactive production of text (31). While I applaud his strategies which dismantle traditional hierarchical structures in academia, the evidence does not convince me that the students know enough to ask important questions or to form a self-directing, learning community. Stanley Fish has not relinquished professing, though he, too, espouses the indeterminancy of the sign. By the fourth week of his course, Slatin's input is, by his own reckoning, reduced to 4% (39). In the transcript of the "controversial" Week 6 exchange on Gertrude Stein--the most disliked poet they were discussing at the time (40)--we see the blind leading the blind. One student parodies Stein for three lines and sums up his input with "I like it." Another, finds Stein's poetry "almost completey [sic] lacking in emotion or any artistic merit" (emphasis added). On what grounds has this student become an arbiter of "artistic merit"? Another student, after admitting being "lost" during the Wallace Steven discussion, talks of having more "respect for Stevens' work than Stein's" and adds that Stein's poetry lacks "conceptual significance[, s]omething which people of varied opinion can intelligently discuss without feeling like total dimwits...." This student has progressed from admitted incomprehension of Stevens' work to imposing her (groundless) respect for his work over Stein's. Then, she exposes her real dislike for Stein's poetry: that she (the student) missed the "conceptual significance" and hence cannot, being a person "of varied opinion," intelligently discuss it "without feeling like [a] total dimwit." Slatin's comment is frightening: "...by this point in the semester students have come to feel increasingly free to challenge the instructor" (41). The students that I have cited are neither thinking critically nor are their preconceptions challenged by student-governed interaction. Thanks to the class format, one student feels self-righteous in her ignorance, and empowered to censure. I believe strongly in student empowerment in the classroom, but only once students have accrued enough knowledge to make informed judgments. Admittedly, Slatin's essay presents only partial data (there are six hundred pages of course transcripts!); still, I wonder how much valuable knowledge and metaknowledge was gained by the students. I also question the extent to which authority and professorial dictature were addressed in this course format. The power structures that make it possible for a college to require such a course, and the choice of texts and pedagogy, were not "on the table." The traditional professorial position may have been displaced, but what took its place?--the authority of consensus with its unidentifiable strong arm, and the faceless reign of software design? Despite Slatin's claim that the students learned about the learning process, there is no evidence (in the article) that the students considered where their attitudes came from, how consensus operates in the construction of knowledge, how power is established and what relationship they have to bureaucratic insitutions. How do we, as teaching professionals, negotiate a balance between an enlightened despotism in education and student-created knowledge? Slatin, and other authors in this book, bring this fundamental question to the fore. There is no definitive answer because the factors involved are ultimately social, and hence, always shifting and reconfiguring. Slatin ends his article with the caveat that computerization can bring about greater estrangement between students, faculty and administration through greater regimentation and control. Of course, it can also "distribute authority and power more widely" (50). Power or authority without a specific face, however, is not necessarily good or just. Shahaf Gal's "Computers and Design Activities: Their Mediating Role in Engineering Education" is found in the second half of the volume, and does not allow for a theory/praxis dichotomy. Gal recounts a brief history of engineering education up to the introduction of Growltiger (GT), a computer-assisted learning aid for design. He demonstrates GT's potential to impact the learning of engineering design by tracking its use by four students in a bridge-building contest. What his text demonstrates clearly is that computers are "inscribing and imaging devices" that add another viewpoint to an on-going dialogue between student, teacher, earlier coursework, and other teaching/learning tools. The less proficient students made a serious error by relying too heavily on the technology, or treating it as a "blueprint provider." They "interacted with GT in a way that trusted the data to represent reality. They did not see their interaction with GT as a negotiation between two knowledge systems" (495). Students who were more thoroughly informed in engineering discourses knew to use the technology as one voice among others--they knew enough not simply to accept the input of the computer as authoritative. The less-advanced students learned a valuable lesson from the competition itself: the fact that their designs were not able to hold up under pressure (literally) brought the fact of their insufficient knowledge crashing down on them (and their bridges). They also had, post factum, several other designs to study, especially the winning one. Although competition and comparison are not good pedagogical strategies for everyone (in this case the competitors had volunteered), at some point what we think we know has to be challenged within the society of discourses to which it belongs. Students need critique in order to learn to push their learning into auto-critique. This is what is lacking in Slatin's discussion and in the writings of other avatars of constructivist, collaborative and computer-mediated pedagogies. Obviously there are differences between instrumental types of knowledge acquisition and discoursive knowledge accumulation. Indeed, I do not promote the teaching of reading, thinking and writing as "skills" per se (then again, Gal's teaching of design is quite discursive, if not dialogic). Nevertheless, the "soft" sciences might benefit from "bridge-building" competitions or the re-institution of some forms of agonia. Not everything agonistic is inhuman agony--the joy of confronting or creating a sound argument supported by defensible evidence, for example. Students need to know that soundbites are not sound arguments despite predictions that electronic writing will be aphoristic rather than periodic. Just because writing and learning can be conceived of hypertextually does not mean that rigor goes the way of the dinosaur. Rigor and hypertextuality are not mutually incompatible. Nor is rigorous thinking and hard intellectual work unpleasurable, although American anti-intellectualism, especially in the mass media, would make it so. At a time when the spurious dogmatics of a Rush Limbaugh and Holocaust revisionist historians circulate "aphoristically" in cyberspace, and at a time when knowledge is becoming increasingly textualized, the role of critical thinking in education will ultimately determine the value(s) of socially constructed knowledge. This volume affords the reader an opportunity to reconsider knowledge, power, and new communications technologies with respect to social dynamics and power relationships.
series	other
last changed	2003/04/23 15:14

_id	1076
authors	Gero, John S. and Saunders, Robert
year	2000
title	Constructed Representations and Their Functions in Computational Models of Designing
doi	https://doi.org/10.52842/conf.caadria.2000.215
source	CAADRIA 2000 [Proceedings of the Fifth Conference on Computer Aided Architectural Design Research in Asia / ISBN 981-04-2491-4] Singapore 18-19 May 2000, pp. 215-224
summary	This paper re-examines the conclusions made by Schön and Wiggins in 1992 that computers were unable to reproduce processes crucial to designing. We propose that recent developments in artificial intelligence and design computing put us in a position where we can begin to computationally model designing as conceived by Schön and Wiggins. We present a computational model of designing using situated processes that construct representations. We show how constructed representations support computational processes that model the different kinds of seeing reported in designing. We also present recently developed computational processes that can identify unexpected consequences of design actions using adaptive novelty detection.
series	CAADRIA
email
last changed	2022/06/07 07:51

For more results click below: