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CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
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_id	9384
authors	Burry, M., Datta, S. and Anson, S.
year	2000
title	Introductory Computer Programming as a Means for Extending Spatial and Temporal Understanding
doi	https://doi.org/10.52842/conf.acadia.2000.129
source	Eternity, Infinity and Virtuality in Architecture [Proceedings of the 22nd Annual Conference of the Association for Computer-Aided Design in Architecture / 1-880250-09-8] Washington D.C. 19-22 October 2000, pp. 129-135
summary	Should computer programming be taught within schools of architecture? Incorporating even low-level computer programming within architectural education curricula is a matter of debate but we have found it useful to do so for two reasons: as an introduction or at least a consolidation of the realm of descriptive geometry and in providing an environment for experimenting in morphological time-based change. Mathematics and descriptive geometry formed a significant proportion of architectural education until the end of the 19th century. This proportion has declined in contemporary curricula, possibly at some cost for despite major advances in automated manufacture, Cartesian measurement is still the principal ‘language’ with which to describe building for construction purposes. When computer programming is used as a platform for instruction in logic and spatial representation, the waning interest in mathematics as a basis for spatial description can be readdressed using a left-field approach. Students gain insights into topology, Cartesian space and morphology through programmatic form finding, as opposed to through direct manipulation. In this context, it matters to the architect-programmer how the program operates more than what it does. This paper describes an assignment where students are given a figurative conceptual space comprising the three Cartesian axes with a cube at its centre. Six Phileban solids mark the Cartesian axial limits to the space. Any point in this space represents a hybrid of one, two or three transformations from the central cube towards the various Phileban solids. Students are asked to predict the topological and morphological outcomes of the operations. Through programming, they become aware of morphogenesis and hybridisation. Here we articulate the hypothesis above and report on the outcome from a student group, whose work reveals wider learning opportunities for architecture students in computer programming than conventionally assumed.
series	ACADIA
email
last changed	2022/06/07 07:54

_id	ga0012
id	ga0012
authors	Galanter, Philip
year	2000
title	GA2: a Programming Environment for Abstract Generative Fine Art
source	International Conference on Generative Art
summary	Fine artists looking to use computers to create generative works, especially those artists inclined towards abstraction, often face an uncomfortable choice in the selection of software tools. On the one hand there are a number of commercial and shareware programs available which implement a few techniques in an easy to use GUI environment. Unfortunately such programs often impose a certain look or style and are not terribly versatile or expressive. The other choice seems to be writing code from scratch, in a language such as c or Java. This can be very time consuming as every new work seems to demand a new program, and the artist's ability to write code can seldom keep pace with his ability to imagine new visual ideas. This paper describes a software system created by the author called GA2 which has been implemented in the Matlab software environment. By layering GA2 over Matlab the artist can take advantage of a very mature programming environment which includes extensive mathematical libraries, simple graphics routines, GUI construction tools, built-in help facilities, and command line, batch mode, and GUI modes of interaction. In addition, GA2 is very portable and can run on Macintosh, Windows, and Unix systems with almost no incremental effort for multi-platform support. GA2 is a work in progress and an extension of the completed GA1 environment. It is medium independent, and can be used for all manner of image, animation, and sound production. GA1 includes a complete set of genetic algorithm operations for breeding families of graphical marks, a database function for managing and recalling various genes, a set of statistical operations for creating various distributions of marks on a canvas or animation frame, a unique Markov-chain-likeoperator for generating families of visually similar lines or paths, and a complete L-system implementation. GA2 extends GA1 by adding more generative techniques such as tiling and symmetry operations, Thom's cusp catastrophe, and mechanisms inspired by complexity science notions such as cellular automata, fractals, artificial life, and chaos. All of these techniques are encapulated in genetic representations. This paper is supplemented with examples from the authors art work, and comments on the philosophy behind this method of working, and its relation towards the reinvigoration of abstraction after post-modernism.
series	other
email
more	http://www.generativeart.com/
last changed	2003/08/07 17:25

_id	ga0009
id	ga0009
authors	Lewis, Matthew
year	2000
title	Aesthetic Evolutionary Design with Data Flow Networks
source	International Conference on Generative Art
summary	For a little over a decade, software has been created which allows for the design of visual content by aesthetic evolutionary design (AED) [3]. The great majority of these AED systems involve custom software intended for breeding entities within one fairly narrow problem domain, e.g., certain classes of buildings, cars, images, etc. [5]. Only a very few generic AED systems have been attempted, and extending them to a new design problem domain can require a significant amount of custom software development [6][8]. High end computer graphics software packages have in recent years become sufficiently robust to allow for flexible specification and construction of high level procedural models. These packages also provide extensibility, allowing for the creation of new software tools. One component of these systems which enables rapid development of new generative models and tools is the visual data flow network [1][2][7]. One of the first CG packages to employ this paradigm was Houdini. A system constructed within Houdini which allows for very fast generic specification of evolvable parametric prototypes is described [4]. The real-time nature of the software, when combined with the interlocking data networks, allows not only for vertical ancestor/child populations within the design space to be explored, but also allows for fast "horizontal" exploration of the potential population surface. Several example problem domains will be presented and discussed. References: [1] Alias \| Wavefront. Maya. 2000, http://www.aliaswavefront.com [2] Avid. SOFTIMAGE. 2000, http://www.softimage.com [3] Bentley, Peter J. Evolutionary Design by Computers. Morgan Kaufmann, 1999. [4] Lewis, Matthew. "Metavolve Home Page". 2000, http://www.cgrg.ohio-state.edu/~mlewis/AED/Metavolve/ [5] Lewis, Matthew. "Visual Aesthetic Evolutionary Design Links". 2000, http://www.cgrg.ohio-state.edu/~mlewis/aed.html [6] Rowley, Timothy. "A Toolkit for Visual Genetic Programming". Technical Report GCG-74, The Geometry Center, University of Minnesota, 1994. [7] Side Effects Software. Houdini. 2000, http://www.sidefx.com [8] Todd, Stephen and William Latham. "The Mutation and Growth of Art by Computers" in Evolutionary Design by Computers, Peter Bentley ed., pp. 221-250, Chapter 9, Morgan Kaufmann, 1999.
series	other
email
more	http://www.generativeart.com/
last changed	2003/08/07 17:25

_id	2ea9
authors	Miranda, Pablo and Coates, Paul
year	2000
title	Swarm modelling. The use of Swarm Intelligence to generate architectural form
source	4th International Conference on Generative Art, Politecnico di Milano University, Milan, Italy
summary	In general the paper discusses the morphogenetic properties of swarm behaviour, and presents an example of mapping trajectories in the space of forms onto 3d flocking boids. This allows the construction of a kind of analogue to the string writing genetic algorithms and Genetic programming that are more familiar, and which have been reported by CECA. Earlier work with autonomous agents at CECA were concerned with the behaviour of agents embedded in an environment, and interactions between perceptive agents and their surrounding form. As elaborated below, the work covered in this paper is a refinement and abstraction of those experiments. This places the swarm back where perhaps it should have belonged, into the realms of abstract computation, where the emergent behaviours (the familiar flocking effect, and other observable morphologies) are used to control any number of alternative lower level morphological parameters, and to search the space of all possible variants in a directed and parallel way.
keywords	Swarm Intelligence; Autonomous agents; Enactive Perception; Structural Coupling; Sensory-motor Perception; Stigmergy
series	other
email
last changed	2003/03/24 15:46

_id	39c6
authors	Miranda, Pablo and Coates, Paul
year	2000
title	Swarm modelling. The use of Swarm Intelligence to generate architectural form
source	3th International Conference on Generative Art, Politecnico di Milano University, Milan, Italy
summary	In general the paper discusses the morphogenetic properties of swarm behaviour, and presents an example of mapping trajectories in the space of forms onto 3d flocking boids. This allows the construction of a kind of analogue to the string writing genetic algorithms and Genetic programming that are more familiar, and which have been reported by CECA. Earlier work with autonomous agents at CECA were concerned with the behaviour of agents embedded in an environment, and interactions between perceptive agents and their surrounding form. As elaborated below, the work covered in this paper is a refinement and abstraction of those experiments. This places the swarm back where perhaps it should have belonged, into the realms of abstract computation, where the emergent behaviours (the familiar flocking effect, and other observable morphologies) are used to control any number of alternative lower level morphological parameters, and to search the space of all possible variants in a directed and parallel way.
keywords	Swarm Intelligence; Autonomous agents; Enactive Perception; Structural Coupling; Sensory-motor Perception; Stigmergy
series	other
email
last changed	2003/03/24 17:13

_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	a337
authors	Testa, P., O’Reilly, U.-M. and Greenwold, S.
year	2000
title	AGENCY GP: Genetic Programming for Architectural Design
doi	https://doi.org/10.52842/conf.acadia.2000.227
source	Eternity, Infinity and Virtuality in Architecture [Proceedings of the 22nd Annual Conference of the Association for Computer-Aided Design in Architecture / 1-880250-09-8] Washington D.C. 19-22 October 2000, pp. 227-231
summary	AGENCY GP is a prototype for a system using genetic programming (GP) for architectural design exploration. Its software structure is noteworthy for its integration into a high-end three-dimensional modeling environment, its allowance for direct user interruption of evolution and reintegration of phenotypically modified individuals, and its agent-based evaluation of fitness.
series	ACADIA
last changed	2022/06/07 07:58

_id	ga0022
id	ga0022
authors	Tokui, Nao and Iba, Hitoshi
year	2000
title	Music Composition with Interactive Evolutionary Computation
source	International Conference on Generative Art
summary	Interactive Evolutionary Computation (IEC), i.e., Evolutionary Computation whose fitness function is provided by a user his/herself, has been applied to esthetic areas, such as art, design and music. We cannot necessarily define fitness functions explicitly in these areas. With IEC, however, we can embed the user's implicit preference into the optimization system. This paper describes a new approach to music composition, more precisely the composition of rhythms, by means of IEC. The main feature of our method is to combine Genetic Algorithms (GA) and Genetic Programming (GP). In our system, GA individuals represent short pieces of rhythmic patterns, while GP individuals express how these patterns are arranged in terms of their functions. Both populations are evolved interactively through the user's evaluation. The integration of interactive GA and GP makes it possible to search for musical structures effectively in the vast search space. In this paper, we show how successfully our proposed method can generate attractive musical rhythms. The effectiveness of our system is demonstrated by the evolved rhythm phrases, which are available from our web site as sound files.
series	other
more	http://www.generativeart.com/
last changed	2003/08/07 17:25

_id	ga0013
id	ga0013
authors	Annunziato, Mauro and Pierucci, Piero
year	2000
title	Artificial Worlds, Virtual Generations
source	International Conference on Generative Art
summary	The progress in the scientific understanding/simulation of the evolution mechanisms and the first technological realizations (artificial life environments, robots, intelligent toys, self reproducing machines, agents on the web) are creating the base of a new age: the coming of the artificial beings and artificial societies. Although this aspect could seems a technological conquest, by our point of view it represent the foundation of a new step in the human evolution. The anticipation of this change is the development of a new cultural paradigm inherited from the theories of evolution and complexity: a new way to think to the culture, aesthetics and intelligence seen as emergent self-organizing qualities of a collectivity evolved along the time through genetic and language evolution. For these reasons artificial life is going to be an anticipatory and incredibly creative area for the artistic expression and imagination. In this paper we try to correlate some elements of the present research in the field of artificial life, art and technological grow up in order to trace a path of development for the creation of digital worlds where the artificial beings are able to evolve own culture, language and aesthetics and they are able to interact con the human people.Finally we report our experience in the realization of an interactive audio-visual art installation based on two connected virtual worlds realized with artificial life environments. In these worlds,the digital individuals can interact, reproduce and evolve through the mechanisms of genetic mutations. The real people can interact with the artificial individuals creating an hybrid ecosystem and generating emergent shapes, colors, sound architectures and metaphors for imaginary societies, virtual reflections of the real worlds.
series	other
email
more	http://www.generativeart.com/
last changed	2003/08/07 17:25

_id	sigradi2006_e183a
id	sigradi2006_e183a
authors	Costa Couceiro, Mauro
year	2006
title	La Arquitectura como Extensión Fenotípica Humana - Un Acercamiento Basado en Análisis Computacionales [Architecture as human phenotypic extension – An approach based on computational explorations]
source	SIGraDi 2006 - [Proceedings of the 10th Iberoamerican Congress of Digital Graphics] Santiago de Chile - Chile 21-23 November 2006, pp. 56-60
summary	The study describes some of the aspects tackled within a current Ph.D. research where architectural applications of constructive, structural and organization processes existing in biological systems are considered. The present information processing capacity of computers and the specific software development have allowed creating a bridge between two holistic nature disciplines: architecture and biology. The crossover between those disciplines entails a methodological paradigm change towards a new one based on the dynamical aspects of forms and compositions. Recent studies about artificial-natural intelligence (Hawkins, 2004) and developmental-evolutionary biology (Maturana, 2004) have added fundamental knowledge about the role of the analogy in the creative process and the relationship between forms and functions. The dimensions and restrictions of the Evo-Devo concepts are analyzed, developed and tested by software that combines parametric geometries, L-systems (Lindenmayer, 1990), shape-grammars (Stiny and Gips, 1971) and evolutionary algorithms (Holland, 1975) as a way of testing new architectural solutions within computable environments. It is pondered Lamarck´s (1744-1829) and Weismann (1834-1914) theoretical approaches to evolution where can be found significant opposing views. Lamarck´s theory assumes that an individual effort towards a specific evolutionary goal can cause change to descendents. On the other hand, Weismann defended that the germ cells are not affected by anything the body learns or any ability it acquires during its life, and cannot pass this information on to the next generation; this is called the Weismann barrier. Lamarck’s widely rejected theory has recently found a new place in artificial and natural intelligence researches as a valid explanation to some aspects of the human knowledge evolution phenomena, that is, the deliberate change of paradigms in the intentional research of solutions. As well as the analogy between genetics and architecture (Estévez and Shu, 2000) is useful in order to understand and program emergent complexity phenomena (Hopfield, 1982) for architectural solutions, also the consideration of architecture as a product of a human extended phenotype can help us to understand better its cultural dimension.
keywords	evolutionary computation; genetic architectures; artificial/natural intelligence
series	SIGRADI
email
last changed	2016/03/10 09:49

_id	ga0027
id	ga0027
authors	E. Bilotta, P. Pantano and V. Talarico
year	2000
title	Music Generation through Cellular Automata
source	International Conference on Generative Art
summary	Cellular automata (CA), like every other dynamical system, can be used to generate music. In fact, starting from any initial state and applying to them simple transition rules, such models are able to produce numerical sequences that can be successively associated to typically musical physical parameters. This approach is interesting because, maintaining fixed the set of rules and varying the initial data, many different, though correlated, numerical sequences can be originated (this recalls the genotype-phenotype dualism). Later on a musification (rendering) process can tie one or more physical parameters typical of music to various mathematical functions: as soon as the generative algorithm produces a numerical sequence this process modifies the physical parameter thus composing a sequence of sounds whose characteristic varies during the course of time. Many so obtained musical sequences can be selected by a genetic algorithm (CA) that promotes their evolution and refinement. The aim of this paper is to illustrate a series of musical pieces generated by CA. In the first part attention is focused on the effects coming from the application of various rendering processes to one dimensional multi state CA; typical behaviours of automata belonging to each of the four families discovered by Wolfram have been studied: CA evolving to a uniform state, CA evolving to a steady cycle, chaotic and complex CA. In order to make this part of the study Musical Dreams, a system for the simulation and musical rendering of one dimensional CA, has been used. In the second phase various CA obtained both by random generation and deriving from those studied in the first part are organised into families and, successively, made evolve through a genetic algorithm. This phase has been accomplished by using Harmony Seeker, a system for the generation of evolutionary music based on GA. The obtained results vary depending on the rendering systems used but, in general, automata belonging to the first family seem more indicated for the production of rhythmical patterns, while elements belonging to the second and fourth family seem to produce better harmonic patterns. Chaotic systems have been seen to produce good results only in presence of simple initial states. Experiments made in the second part have produced good harmonic results starting mainly from CA belonging to the second family.
series	other
more	http://www.generativeart.com/
last changed	2003/08/07 17:25

_id	5007
authors	Elezkurtaj, Tomor and Franck, Georg
year	1999
title	Genetic Algorithms in Support of Creative Architectural Design
doi	https://doi.org/10.52842/conf.ecaade.1999.645
source	Architectural Computing from Turing to 2000 [eCAADe Conference Proceedings / ISBN 0-9523687-5-7] Liverpool (UK) 15-17 September 1999, pp. 645-651
summary	The functions supported by commercial CAAD software are drawing, construction and presentation. Up to now few programs supporting the creative part of architectural problem solving have become available. The grand hopes of symbolic AI to program creative architectural design have been disappointing. In the meantime, methods called referred to as New AI have become available. Such methods includegenetic algorithms (GA). But GA, though successfully applied in other fields of engineering, still waits to be applied broadly in architectural design. A main problem lies in defining function in architecture. It is much harder to define the function of a building than that of a machine. Without specifying the function of the artifact, the fitness function of the design variants participating in the survival game of artificial evolution remains undetermined. It is impossible to fully specify the fitness function of architecture. The approach presented is one of circumventing a full specification through dividing labor between the GA software and its user. The fitness function of architectural ground plans is typically defined in terms only of the proportions of the room to be accommodated and certain topological relations between them. The rest is left to the human designer who interactively intervenes in the evolution game as displayed on the screen.
keywords	Genetic Algorithms, Creative Architectural Design
series	eCAADe
email
last changed	2022/06/07 07:55

_id	f91f
authors	Elezkurtaj, Tomor and Franck, Georg
year	2000
title	Geometry and Topology. A User-Interface to Artificial Evolution in Architectural Design
doi	https://doi.org/10.52842/conf.ecaade.2000.309
source	Promise and Reality: State of the Art versus State of Practice in Computing for the Design and Planning Process [18th eCAADe Conference Proceedings / ISBN 0-9523687-6-5] Weimar (Germany) 22-24 June 2000, pp. 309-312
summary	The paper presents a system that supports architectural floor plan design interactively. The method of problem solving implemented is a combination of an evolutionary strategy (ES) and a genetic algorithm (GA). The problem to be solved consists of fitting a number of rooms (n) into an outline by observing functional requirements. The rooms themselves are specified concerning size, function and preferred proportion. The functional requirements entering the fitness functions are expressed in terms of the proportions of the rooms and the neighbourhood relations between them. The system is designed to deal with one of the core problems of computer supported creativity in architecture. For architecture, form not only, but also function is relevant. Without specifying the function that a piece of architecture is supposed to fulfil, it is hard to support its design by computerised methods of problem solving and optimisation. In architecture, however, function relates to comfort, easiness of use, and aesthetics as well. Since it is extraordinary hard, if not impossible, to operationalise aesthetics, computer aided support of creative architectural design is still in its infancy.
keywords	New AI, Genetic Algorithms, Artificial Evolution, creative Architectural Design, Interactive Design, Topology
series	eCAADe
email
more	http://www.uni-weimar.de/ecaade/
last changed	2022/06/07 07:55

_id	dba1
authors	Hirschberg, Urs and Wenz, Florian
year	2000
title	Phase(x) - memetic engineering for architecture
source	Automation in Construction 9 (4) (2000) pp. 387-392
summary	Phase(x) was a successful teaching experiment we made in our entry level CAAD course in the Wintersemester 1996/1997. The course was entirely organized by means of a central database that managed all the students' works through different learning phases. This set-up allowed that the results of one phase and one author be taken as the starting point for the work in the next phase by a different author. As students could choose which model they wanted to work with, the whole of Phase(x) could be viewed as an organism where, as in a genetic system, only the "fittest" works survived. While some discussion of the technical set-up is necessary as a background, the main topics addressed in this paper will be the structuring in phases of the course, the experiences we had with collective authorship, and the observations we made about the memes2 that developed and spread in the students' works. Finally we'll draw some conclusions in how far Phase(x) is relevant also in a larger context, which is not limited to teaching CAAD. Since this paper was first published in 1997, we have continued to explore the issues described here in various projects3 together with a growing number of other interested institutions worldwide. While leaving the paper essentially in its original form, we added a section at the end, in which we outline some of these recent developments.
series	journal paper
more	http://www.elsevier.com/locate/autcon
last changed	2003/05/15 21:22

_id	dcb9
authors	Kolarevic, Branko
year	2000
title	Digital Architectures
doi	https://doi.org/10.52842/conf.acadia.2000.251
source	Eternity, Infinity and Virtuality in Architecture [Proceedings of the 22nd Annual Conference of the Association for Computer-Aided Design in Architecture / 1-880250-09-8] Washington D.C. 19-22 October 2000, pp. 251-256
summary	This paper surveys different approaches in contemporary architectural design in which digital media is used not as a representational tool for visualization but as a generative tool for the derivation of form and its transformation. Such approaches are referred to as digital architectures – the computationally based processes of form origination and transformations. The paper examines the digital generative processes based on concepts such as topological space, motion dynamics, parametric design and genetic algorithms. It emphasizes the possibilities for the “finding of form,” which the emergence of various digitally based generative techniques seem to bring about.
series	ACADIA
email
last changed	2022/06/07 07:51

_id	4077
authors	Kolarevic, Branko
year	2000
title	Digital Morphogenesis and Computational Architectures
source	SIGraDi’2000 - Construindo (n)o espacio digital (constructing the digital Space) [4th SIGRADI Conference Proceedings / ISBN 85-88027-02-X] Rio de Janeiro (Brazil) 25-28 september 2000, pp. 98-103
summary	This paper examines methods in which digital media is employed not as a representational tool for visualization but as a generative tool for the derivation of form and its transformation - the digital morphogenesis. It explores the possibilities for the “finding of form”, which the emergence of various digitally based generative techniques seem to bring about. It surveys the digital generative processes - the computational architectures - based on concepts such as topological space, isomorphic surfaces, kinematics and dynamics, keyshape animation, parametric design, and genetic algorithms.
series	SIGRADI
email
last changed	2016/03/10 09:54

_id	1b04
authors	Leu, S.-S., Yang, C.-H. and Huang, J.-C.
year	2000
title	Resource leveling in construction by genetic algorithm-based optimization and its decision support system application
source	Automation in Construction 10 (1) (2000) pp. 27-41
summary	Traditional analytical and heuristic approaches are inefficient and inflexible when solving construction resource leveling problems. A computational optimization technique, genetic algorithms (GAs), was employed in this study to overcome drawbacks of traditional construction resource leveling algorithms. The proposed algorithm can effectively provide the optimal or near-optimal combination of multiple construction resources, as well as starting and finishing dates of activities subjected to the objective of resource leveling. Furthermore, a prototype of a decision support system (DSS) for construction resource leveling was also developed. Construction planners can interact with the system to carry out ad hoc analysis through "what-if" queries.
series	journal paper
more	http://www.elsevier.com/locate/autcon
last changed	2003/05/15 21:22

_id	96a7
authors	Li, Heng and Love, Peter E.D.
year	2000
title	Genetic search for solving construction site-level unequal-area facility layout problems
source	Automation in Construction 9 (2) (2000) pp. 217-226
summary	A construction site represents a conflux of concerns, constantly calling for a broad and multi-criteria approach to solving problems related to site planning and design. As an important part of site planning and design, the objective of site-level facility layout is to allocate appropriate locations and areas for accommodating temporary site-level facilities such as warehouses, job offices, workshops and batch plants. Depending on the size, location and nature of the project, the required temporary facilities may vary. The layout of facilities can influence on the production time and cost in projects. In this paper, a construction site-level facility layout problem is described as allocating a set of predetermined facilities into a set of predetermined places, while satisfying layout constraints and requirements. A genetic algorithm system, which is a computational model of Darwinian evolution theory, is employed to solve the facilities layout problem. A case study is presented to demonstrate the efficiency of the genetic algorithm system in solving the construction site-level facility layout problems.
series	journal paper
more	http://www.elsevier.com/locate/autcon
last changed	2003/05/15 21:22

_id	ga0014
id	ga0014
authors	McGuire, Kevin
year	2000
title	Controlling Chaos: a Simple Deterministic System for Creating Complex Organic Shapes
source	International Conference on Generative Art
summary	It is difficult and frustrating to create complex organic shapes using the current set of computer graphic programs. One reason is because the geometry of nature is different from that of our tools. Its self-similarity and fine detail are derived from growth processes that are very different from the working process imposed by drawing programs. This mismatch makesit difficult to create natural looking artifacts. Drawing programs provide a palette of shapes that may be manipulated in a variety ways, but the palette is limited and based on a cold Euclidean geometry. Clouds, rivers, and rocks are not lines or circles. Paint programs provide interesting filters and effects, but require great skill and effort. Always, the details must be arduously managed by the artist. This limits the artist's expressive power. Fractals have stunning visual richness, but the artist's techniques are limited to those of choosing colours and searching the fractal space. Genetic algorithms provide a powerful means for exploring a space of variations, but the artist's skill is limited by the very difficult ability to arrive at the correct fitness function. It is hard to get the picture you wanted. Ideally, the artist should have macroscopic control over the creation while leaving the computer to manage the microscopic details. For the result to feel organic, the details should be rich, consistent and varied, cohesive but not repetitious. For the results to be reproducible, the system should be deterministic. For it to be expressive there should be a cause-effect relationship between the actions in the program and change in the resulting picture. Finally, it would be interesting if the way we drew was more closely related to the way things grew. We present a simple drawing program which provides this mixture of macroscopic control with free microscopic detail. Through use of an accretion growth model, the artist controls large scale structure while varied details emerge naturally from senstive dependence in the system. Its algorithms are simple and deterministic, so its results are predictable and reproducible. The overall resulting structure can be anticipated, but it can also surprise. Despite its simplicity, it has been used to generate a surprisingly rich assortment of complex organic looking pictures.
series	other
more	http://www.generativeart.com/
last changed	2003/08/07 17:25

_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

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