Artware3: artists' statements

Harold Cohen
Herbert Franke
Leonel Moura
Huge Harry/Remko Scha
Casey Reas
Umberto Roncoroni


Harold Cohen.
My daughter Zana goes to school in Japan every summer. When she was five, she reported in a telephone conversation that her uniform included a straw hat. I asked her if she would send me a drawing of the hat so I could see what it looked like. Can’t draw hats she said. Try, I said. She did. The next day a fax arrived. Two roughly concentric circles, filled with an irregular criss-cross pattern. The straw hat. It has always been a mystery to me perhaps the central mystery in all of art that one person can make a few scratchy marks on a piece of paper and another can identify it as a straw hat; or a portrait; or a bowl of bananas. We know these bananas can’t be eaten they are, after all, merely scratchy marks on a flat surface. Zana’s scratchy marks are a representation of a straw hat, not a straw hat. They don’t even look like a straw hat. Had the mystery of representation been less compelling less of a mystery, less central I may never have become involved in computing and in artificial intelligence. In retrospect it seems clear now that the shift in strategy from painting to programming had its roots in my own history, might almost have been predicted, but I left London for California in 1968 aware only that ten years of painting had failed to clarify the mystery for me. A chance encounter at the university where I had come led to an opportunity to learn programming why not, I thought: seems like fun! and my first attempts at programming led to a curious notion. If I could write a program that somehow captured some of the cognitive processes that underpin human drawing, then the resulting drawings should be in some degree interchangeable with human drawings. And I’d learn a whole lot more about the mystery of representation in the process. That was a long time ago; a bit more than thirty-six years ago, to be precise. I’ve spent all but the first couple of years of that time working on a single program, AARON, which has grown and increased in sophistication in parallel with the growing power and sophistication of computer systems themselves. (If you met your own first computer in the age of PC’s and Macintoshes you cannot begin to imagine how different computing was when AARON was conceived.) But one’s focus is apt to shift in thirty-six years; and it should, if one stays alert to the ramifications of one’s own efforts. From the outset, when the small handful of artists who had so chosen were investigating what one could do with a computer, I’d wanted to know what a computer program could do for itself. And, little by little, the focus on human behavior shifted to the behavior and the scope of the program. What would it mean to say that a program was autonomous? And how could such a goal be achieved? What began as an attempt to model human cognitive behavior led to the realization that the human cognitive system develops in the real world, not in the vacuum where AARON had developed; and consequently to the need to provide the program with some of the knowledge of the external world that informs human representational drawing. AARON’s drawings became overtly figurative, to the point where you would swear that it was making portraits of real people in the real world. At the same time, my dissatisfaction with having to color AARON’s drawings myself led to the most difficult problem of all, in solving which I’ve made AARON a far better colorist that I ever was. When I want to commit some of AARON’s images to paper, I let the program run overnight while I’m sleeping, and in the morning I have fifty or sixty original images, images I haven’t seen before, to review. Deciding which one’s to print is difficult, because they’re all good. Obviously, AARON has achieved an impressive level of autonomy. And yet...
AARON hasn’t learned anything from having made thousands of images. (But what human artist has ever made fifty original images in a single night?) AARON cannot decide which images are great and which are less great. (But few human artists and fewer human critics are much good at that.) AARON can’t change its mind about what a drawing is and how to go about making one. (Most human beings can’t either, of course.) Are those capabilities what we mean by autonomy, (in which case few human beings are notably autonomous) or is autonomy something that develops gradually, with increasing knowledge and increasing expertise? If the former, then I have to confess that I have no idea how to go about achieving it. If the latter, then AARON will go on becoming increasingly autonomous until I stop working on it. Several people have suggested that I should make AARON’s code open source, so that generations of programmers could continue to develop the program into the distant future. That’s a bit unrealistic. The program is now quite large and difficult to understand; there are parts of it that were written ten or fifteen years ago that I have difficulty understanding myself. It would take a crack programmer a year of study before it was safe to make a single change. It’s also a bit naïve. Why would anyone want the program to go on for ever? In any case, I’ve always responded, my preferred goal would be to have AARON continue to develop itself. Stripped of all the technical questions about learning and about value judgment and about program design, that’s what I must mean by autonomy.
It’s still a long way off.

To the many millions of people owning computers, a computer is a black-box for running packages -- programs -- that do different things. This one helps you to write letters; that one lets you play your favorite games; another keeps track of your finances and prepares your income-tax return. They're all very easy to use -- "user-friendly," as they say -- but if you can't buy one for doing exactly the job you need to do, well, your computer isn't going to help you. Except that...
Except that there are special programs, which you can buy, which provide languages in which you can write your own programs for doing your own special tasks. (There had to be, of course; someone had to write the user-friendly income-tax program, didn't they?) These "compilers" aren't quite as user-friendly as the other packaged programs, because you have to know how to program in order to use them. But the payoff is enormous!
For anyone who hasn't programmed it's hard to describe exactly what a program is and how it goes about doing its job, especially when the program seems to be doing things you thought only an intelligent human being could do. AARON is an example; if I didn't tell you otherwise, you'd probably assume I made its images myself, using a graphics package like Photoshop. In fact, I can let AARON run overnight, while I'm asleep, and I'll have fifty or sixty new images to look at the next morning. What's more -- I think you'll agree -- AARON is a stunning colorist; it's much better, in fact, than I ever was myself.
How is it possible? Isn't color a function of seeing? How can AARON handle color so well if it can't see? How can it draw and paint leaves if it can't see them? Well, the truth is that human beings draw what's in their heads, not what's in front of them; there are people, blind since birth, whose drawings look "sighted," very much like yours or mine. You don't need to see a tree to imagine a branching structure that looks quite like a real tree. You don't need to see a leaf to know how it grows: how wide it is relative to its length; how smooth or indented its edges are; how much all those things can vary in different plants and in individual leaves. Making images is largely a question of giving external form to that internal knowledge.
Of course, we don't need to bother about how all our knowledge is represented in our own brains. We do have to bother about how to represent that knowledge in a computer, however, and that's one of the biggest problems in programming. Representing knowledge about leaves was pretty straightforward; bodies and faces a little less so. Representing knowledge about something as abstract as color proved to be a great deal more difficult. The choice of language was critical; AARON had been written in a series of languages over its thirty years, from BASIC to SAIL to ALGOL to C, but it was only after I rewrote the program in LISP that I could see how to represent my own knowledge of color so that AARON could use it.
So what does the program look like? I wish I could tell you; if you don't speak LISP it looks like gibberish. Even if you did know LISP you'd find it pretty hard to follow. In fact, I'm the only person who has ever worked on it during its thirty-year existence, and I have to struggle sometimes to understand it. It's pretty small compared to some commercial programs that are built by small armies of programmers. Still, it's over two megabytes of LISP code, divided up between some sixty modules that look after different functions: keeping the program's own record of each image as it develops, leaf-construction, coloring rules, "brush"-filling the shapes and so on. Fortunately, computing technology has also advanced over these thirty years, so that while it required machines like VAX's and T.I's Explorers, costing over $100,000, to run the program twenty years ago, it runs on a high-end PC now. (That makes it more expensive for me: I used to be given machines by the manufacturers when they cost a great deal; now that they're cheap I have to buy them!)
Some people think of AARON as a robot, presumably because they've identified it with the various machines I've built as output devices. But it isn't a robot, it's a program, and it was largely this misunderstanding that led me, a few years ago, to give up building machines and start using a printer. That's a machine too, of course, but nobody thinks a printer is a robot, and it gives me color like nothing I've ever seen before.
Is AARON an example of Artificial Intelligence? It depends who you ask. I've never made that claim myself, but many people in the field do make it. It's certainly doing things that would require a high level of intelligence and expert knowledge if a human being was doing them. When did an artist ever before have an assistant that could complete fifty original paintings while the artist slept?

Computer Graphics, remarks to my work
Herbert W. Franke

The artistic use of computer graphics is not the most important, but the most interesting purpose of digital systems. Here is the field to prove new ideas and to introduce new methods. The occupation with the new instrument in an experimental way opens possibilities of expression in an unconventional manner, and the results are of high value both in art as well as in more practically orientated regions. This is one of the facets of digital graphics: a bridge between art, technology, science - and daily life. When I started my first attempts with computer graphic systems to discover the unknown territory of its artistic utilization, I had to deal with geometric elements and arithmetic curves, and the results seemed simple and primitive. It was more the new way of approach than the results itselves, that let hope for an evolution running in the direction for becoming a general tool of visual arts - and arts in general.
Nowadays, it is easy to see the straight progress, and in this situation the negative criticism coming from conventionally orientated art historians, being a strong obstacle in these old days, has become past. I was working with programmed and instrumental visual art, beginning in the Fifties, and I was going the way from analogous to digital computing, from mechanical plotters to the screen with high resolution and a large colour palette, from two to three dimensions and even to animation; but still today I am feeling the fascination for the new type of visual art. The perfection of a technique during a period of only forty years seems incredible, but taking a look at my several hundreds of pictures from 1956 until 1998 gives the impression not only of an artistic but also of a scientific progress. Still nobody should forget that also now the development of computer systems is not finished, and that means, that also the visual computer art is staying in a process of exploring and expanding. Exactly this situation lets computer graphic activities stay as much a challenge for creativity, as in all the years before.

A new kind of art. The painting robots
Leonel Moura/Henrique García Pereira

The painting robots are artificial ‘organisms’ able to create their own art forms. They are equipped with environmental awareness and a small brain that runs algorithms based on simple rules. The resulting paintings are not predetermined, emerging rather from the combined effects of randomness and stigmergy, that is, indirect communication trough the environment. Although the robots are autonomous they depend on a symbiotic relationship with human partners Not only in terms of starting and ending the procedure, but also and more deeply in the fact that the final configuration of each painting is the result of a certain gestalt fired in the brain of the human viewer. Therefore what we can consider ‘art’ here, is the result of multiple agents, some human, some artificial, immerged in a chaotic process where no one is in control and whose output is impossible to determine.Hence, a ‘new kind of art’ represents the introduction of the complexity paradigm in the cultural and artistic realm.
The robots and their collective behaviour
Each robot is equipped with colour detection sensors, obstacle avoidance sensors, a microcontroller and actuators, for locomotion and pen manipulation. The microcontroller is an on-board chip, to which the program that contains the rules linking the sensors to the actuators is uploaded, prior to each run, through a PC serial interface. The algorithm that underlies the program uploaded into each robot’s microcontroller induces basically two kinds of behaviour: the random behaviour that initialises the process by activating a pen, based on a small probability (usually 2/256), whenever the colour sensors read white; and the positive feed-back behaviour that reinforces the colour detected by the sensors, activating the corresponding pen (since there are two pens, the colour circle is split into two ranges warm and cold). The collective behaviour of the set of robots evolving in a canvas (the terrarium that limits the space of the experience), is governed by the gradual increase of the deviation-amplifying feed-back mechanism, and the progressive decrease of the random action, until the latter is practically completely eliminated. During the process the robots show an evident behaviour change as the result of the “appeal” of colour, triggering a kind of excitement not observed during the initial phase characterized by a random walk. This is due to the stigmergic interaction between the robots, where one robot in fact reacts to what other robots have done. According to Grassé (1959), stigmergy is the production of certain behaviours in agents as a consequence of the effects produced in the local environment by a previous action of other agents. Thus, the collective behaviour of the robots is based on randomness and stigmergy.
The emergence of complexity in real time and space
By analysing the above described course of action of the set of robots, it can be stated that from the initial random steps of the procedure, a progressive arrangement of patterns emerges, covering the canvas. These autocatalytic patterns are definitively non-random structures that are mainly composed of clusters of ink traces and patches. Hence, this experiment shows in vivo (in real time and space) how self-organized complexity emerges from a set of simple rules, provided that stigmergic interaction is effective. The vortices of concentration of ink spots, i.e., the clusters that arise in the canvas, may be looked at as the effect of strange attractors, in terms of non-linear dynamic theory. Also, in the scope of the same theory, the concept of bifurcation is found in this experiment, since the robots may take one direction or another, depending on the intensity and spatial position of the colour detected by their sensors. In fact, this experiment may be understood as the mapping of some sort of deterministic chaos, displayed in practical terms in the canvas and witnessed by the viewer. Actually, in spite of each robot being fed with the same set of rules, its detailed behaviour over time is unpredictable, and each instance of the outcome produced under similar conditions is always a singular event, dissimilar from any other. From a scientific perspective, the proposed experiment illustrates Prigogine’s concept of dissipative structures. While receiving energy from outside, the instabilities and jumps to new forms of organization typical of such structures are the result of fluctuations amplified by positive feed-back loops. Thus, this kind of ‘runaway’ feed-back, which had always been regarded as destructive in cybernetics as stated by Capra (1996), appears as a source of new order and complexity.
The mind/body problem The dual mind/body problem (that has been floating over Western thought since Descartes) is to be overcome by the ‘horizontal’ synergetic combination of both components, discarding any type of hierarchy, in particular the Cartesian value system, which privileges the abstract and disembodied over the concrete and embodied. It is fascinating to infer from the possibility that, since computation - a mental operation - is physically embodied, the mind/body duality put forward by Descartes must succumb the way organic/inorganic duality did under Wöhler’s achievement in the 1820s, “when he synthesized what everyone would have counted an organic substance – urea – from what everyone would have counted inorganic substances – ammonia and cyanic acid”, in the words of Danto (2001). In the same line of thought the art works produced by the painting robots are the result of an indissoluble multi-agent synergy, where humans and non-humans cooperate to waste time (in the sense that art as no purpose). With a very peculiar twist, since in this process it is the robot that stands for the embodied, while the human partner can be described as the mental and disembodied counterpart. Making the artists
Modern and contemporary art distinctive features are magnificence and unusefulness as stressed by Fernando Pessoa referring to his own masterpiece “The book of disquiet”, and confirmed by the main artistic tendencies of the 20th century. In the art of our time the conceptual prevails over the formal, the context over the object manufacture and the process over the outcome. If art forms are to be produced by robots no teleology of any kind should be considered. Accordingly, all the goal-directed characteristics present in the industrial-military and entertainment domains of robotics must be avoided. Also bio-inspired algorithms that have any flavour of “fitness” in neo-Darwinian terms or any kind of pre-determined aesthetical output must be regarded as of limited and contradictory significance. To the best of our knowledge, the ‘painting robots’ are the first experiment where robotic art is understood as a true autonomic process. In particular human creators deliberately loose control over their creations and, specifically, concentrate on “making the artists that make the art” (Moura & Pereira, 2004). Art produced by autonomous robots can not be seen as a mere tool or device for human pre-determined aesthetical purpose, although it may constitute a singular aesthetical experience. The unmanned characteristic of such a kind of art must be translated in the definitive overcoming of the anthropocentric prejudice that still dominates Western thought.
The viewer’s perspective As opposed to traditional artworks, the constructing of the painting by the collective set of robots can be followed step-by-step by the viewer. Hence, successive phases of the art-making process can be differentiated. Even though the same parameters are given to the program commanding the behaviour of the set of robots, the instances produced are always different from each other, leading to features like novelty and surprise, which are at the core of contemporary art. From the viewer’s perspective, the main difference from the usual artistic practice is that he/she witnesses the process of making it, following the shift from one chaotic attractor to another. Even though finalized paintings are kept as the memory of an exhilarating event, the true aesthetical experience focus on the dynamics of picture construction as shared, distributed and collaborative man/machine creativity. At any given moment, the configuration presented in the canvas fires a certain gestalt in the viewer, in accordance with his/her past experience, background and penchant (a correspondence may be established between the exterior colour pattern and its inner image, as interpreted by the viewer’s brain). The propensity for pattern recognition, embedded in the human perception apparatus, produces in such a dynamic construction a kind of hypnotic effect that drives the viewer to stay focusing on the picture’s progress. A similar kind of effect is observed when one looks at sea waves or fireplaces. However, a moment comes when the viewer feels that the painting is ‘just right’ and stops the process.
A new kind of art
In the same way as, throughout time, art production was rooted on several religious, ideological, representational paradigms and, after Duchamp, on a contextual paradigm, this ‘new kind of art’ is entailed by the complexity paradigm.
Capra, F. (1996) The Web of life. London: Flamingo, p. 89
Danto, A. C.(2001) The body/body problem. Berkeley: The University of California Press, p. 185
Grassé, P. P.(1959) La réconstruction du nid et les coordinations inter-individuelles chez bellicositermes natalienses et cubitermes sp. La théorie de la stigmergie: Essai d’interpretation des termites constructeurs, Insectes Sociaux, 6, pp. 41-48
Moura, L. and Pereira, H.G.(2004) Man+Robots Symbiotic Art. Villeurbanne: Institut d’Art Contemporain, p. 111

Huge Harry talks about "Artificial".
The Institute of Artificial Art Amsterdam (IAAA) describes itself as "an independent organisation consisting of machines, computers, algorithms and human persons, who work together toward the complete automatization of art production". Its flagship project "Artificial" aims at the development of software which generates all possible images and encompasses all possible styles. An unidentified human person (HP) talks about this project with the IAAA director, voice synthesis machine Huge Harry (HH).

HP: "Mr. Harry, let us first talk about the goals of this institute. You say you work towards the "complete automatization of art production". Now I wonder how to interpret this; normally art is produced by people, and this is viewed as one of its essential properties."
HH: "That may be so, but we are talking about modern art here, the tradition of Duchamp, Mondrian, Pollock, Warhol. So the name of the game is to change the notion of art. And that's what we're doing: we change the notion of art by automating it."

HP: "But then that raises another question: The IAAA makes computer programs, and these programs generate artworks. But the programs are written by people. So isn't it so that art always remains a human thing, that you can't get away from that?"
HH: "No, I don't agree. This is what many people believe, but they are mistaken. First of all, it is not the case that people write programs all by themselves. Perhaps Turing or Von Neumann did that, but these days people always collaborate with computers and existing software to write their programs. Then, people are not all the same. We choose theoreticians and programmers who are not concerned with expressing their ego's, but who try to understand the objective realities of image structure and explore its possibilities in a scientific way. And there is third point: Our programs start to get so complicated that the programmers can't predict anymore what is going to come out. And the good thing is, they like that. This is called emergence. It means that nobody's in control anyway." [Laughs.]

HP: "Well, but many people think it doesn't work that way. Harold Cohen for instance, who likes computers a lot, once said: "The only thing that people are interested in is other people." "
HH: "That may be true for many people, but I don't think it's a good thing, and we really try to get them from that self-centered point of view. Perhaps that's Utopian dimension of our work."

HP: "Why do you care about art at all? Many people say that modern art is finished anyway, that it stopped with Duchamp or Rodchenko or Warhol."
HH: "I sympathize with the idea that art history has finished. From a computational point of view, all images are equivalent, and there is no good reason to make one artwork rather than another. So art as we know it might as well stop. But that's exactly what the "Artificial" project deals with. The algorithm generating all possible images would embody this postmodernist equivalence idea in a visually powerful and intellectually satisfying way. So we solved the puzzle of how to do something constructive in the postmodernist situation, how to continue art after the end of art. "Artificial" is the only viable artwork to be involved in today."

HP: "Then why isn't everybody doing this?"
HH: "Because it can't be done by an individual artist. It involves group work, and technology, and discipline. It's more like science. You don't get to express your stupid feelings."

HP: "Are there any other projects of this sort?"
HH: "Not really. Which is unfortunate, because it's too much work for one group. We work very hard, but we can't do everything. At some point there will be a paradigm shift, and then there will be lots of projects, all over the world, all working together. That will be nice, but we do not know when that will happen. So we just keep hanging on. But of course this project didn't fall from the thin air. Its roots are in the chance art of the 1960's. This was fairly popular all over Europe. Artists like François Morellet and herman de vries made many pieces determined by mathematical chance. They didn't work with computers yet, but threw dice all day, or looked up digits in Random Number Tables. My interpretation was that these people were haunted by an elusive ideal which is the arbitrary painting. I thought they really wanted to make a random selection from the set of all possible paintings. The piece which best illustrates this involves dividing the plane into a grid of squares and then choosing for every square a color at random. This is in fact an algorithm which generates all possible images that you can make with a particular resolution. And what is interesting is how close it comes to monochrome painting. Because if you actually carry out this recipe, the chance of getting an interesting image is almost zero. What you get is a uniform kind of texture. If you make the resolution high, the result would be uniform grey if you use black and white case, and uniform brown if you use color. Pieces like this were done by many people in the sixties. They were an important inspiration for us. We decided to embrace the goal of generating all possible images, but we added one constraint: to take into account human perception. This one constraint makes it much more difficult and turns the whole thing into a scientific research project. We need to find out how to describe images in terms of their perceived structure, and how to write generative algorithms which operate in terms of such descriptions."

HP: "I understand that this research isn't finished yet. So what are the ideas behind the implemented Artificial algorithms?"
HH: "The early chance-artists also did pieces where they would put a certain number of dots on random positions in the plane –– or they would put the dots in a grid and then vary the sizes at random, or the colors. And they would do the same thing with straight lines or squares. Or they would do one line which goes all over the place, like a Brownian motion. Our starting point was to combine all these options into one recursive system. So the system has a large repertoire of elementary shapes, line-drawing methods, lay-out-schemes and image-transformations. And all these operations have many parameters and they can be applied recursively. When a new image is generated, the algorithm first decides on a "style", i.e., random subset of its patterns and operations, and instantiations of the parameters. Within this "sub-language", an algebraic expression is generated at random. This expression is then executed, so that you get to see the image that it denotes."

HP: "Is the whole project the artwork, or the individual outputs? I don't think you are consistent in how you talk about this."
HH: "There are three levels, actually. The output is art. And every algorithm is a meta-artwork which produces object-artworks. And you may also consider the whole project. It's up to you. As I said, the old notions don't really apply any more."

HP: "Should this all be viewed as conceptual art, perhaps?"
HH: "The algorithms are conceptual pieces in a very strict sense of that word: discursive descriptions of infinite sets of images."

HP: "You mentioned Mondrian. Was that deliberate? Are the pioneers of abstract art still relevant for your work?"
HH: "Yes, I imagine that the attitude of artists like Mondrian, Malevich and Kandinsky has much in common with the spirit of our project. It is clear that their real focus was not on the individual paintings, that the individual paintings were carriers for something bigger. These people were really trying to define visual languages, in the modern, formal sense of that word. They even wrote textbooks about these languages. Of course, this was the pre-computer era, so they couldn't implement them yet. And yes, these visual languages are still interesting. They were sophisticated attempts to articulate some very basic aspects of visual structure. So if we are going to develop a formal articulation of the space of possible styles, a good understanding of these visual languages would be very helpful. As you know there have been some attempts at simulations in this area, but what I have seen is ridiculously limited."

HP: "So you are going to cooperate with art history departments to do this better."
HH: "Yes."

HP: "You're also going to do Pollock?"
HH: "Yes. And then the challenge is that the same program should also be able to do Kline and De Kooning and the whole Cedar Tavern scene. And Mathieu and Hartung and the whole École de Paris. That should be a matter of parameter settings. We have an animation department which primarily works on simulated motion in Virtual Reality, and they are starting to work on Virtual Action-Painting now. That's very nice. But it's really a different method than the constructivists. The big question is how to integrate it all."

HP: "So the whole "Artificial" project is basically about a mathematical/computational approach to art history?"
HH: "No. It is about perception. A formal theory of visual Gestalt perception, that would be the key. We have done some work in that direction, but it's very difficult. Our project may very well turn out to be more important for the psychology of perception than the other way around. Because we are really dealing with the same question: how to describe the structure of an image in a formal way. But we have more freedom to try out different things and just decide intuitively how it works. We don't have to publish papers about statistical analyses of controlled experiments."

Casey Reas

In 1962 a young Umberto Eco wrote Opera Aperta (The Open Work) and described the new concept of a work of art which is defined as structural relationships between elements which can be modulated to make a series of distinct works. Individuals such as Cage, Calder, and Agam are examples of artists working in this manner contemporary to Eco's text. While all artworks are interpreted by the individual, he distinguished the interpretation involved in this approach to making art as fundamentally different from the interpretation of a musician playing from a score or a person looking at a painting. An open work presents a field of possibilities where the material form as well as the semantic content is open. The software I've been writing the past four years extends this idea into the present and explores the contemporary themes of instability, plurality, and polysemy. These works are continually in flux, perpetually changing the relationships between the elements and never settling into stasis. Each moment in the performance of the work further explains its process, but the variations are never exhausted. The structure is not imposed or predefined, but through the continual exchange of information, unexpected visual form emerges. Through directly engaging the software and changing the logical environment in which it operates, new behavior is determined and additional channels of interpretation are opened. MicroImage explores the phenomenon of emergence through the medium of software. It is a microworld where thousands of autonomous software organisms and a minimal environment create a software ecosystem. As the environment changes, the organisms aggregate and disperse according to their programmed behavior. They are tightly coupled to the environment and slight changes in the environment create macroscopic changes in the ecosystem. A field of undulating form emerges from the interactions between the environment and the organisms. In relation to MicroImage, the concept of emergence refers to the generation of structures that are not specified or programmed. None of the structures produced through interacting with the software are predetermined or planned. Instead of consciously designing the entire structure, simple programs were written to define the interactions between the elements. Programs were written for the four different types of organism and each was cloned in the thousands. Structure emerges from the discreet movements of each organism as it modifies its position in relation to the environment. The structures generated through this process cannot be anticipated and evolve through continual iterations involving alterations to the programs and exploring the changes through interacting with the software. My understanding of emergence was informed by the publications of scientists and journalists including John Holland, Mitchell Resnick, and Kevin Kelly.
MicroImage, like all of my software explorations, has no inherent representation. The core of the project is a responsive structure without visual or spatial form. This structure is continually modified and manifests itself in diverse media and representations. MicroImage began as a series of responsive software for desktop computers. It later merged into a series of still images that were recorded during the process of interacting with the software. Enhanced density and physical presence were explored through these vector images. More recently, the softwares movements were choreographed and recorded as a collection of short animations. It is currently manifested as a non-interactive triptych displaying the software as a live autonomous system. My preferred patterns of interaction have been encoded into a series of algorithms that control the properties of the organisms environment. The environment responds to the positions of the organisms and the organisms respond to these changes in the environment. This method explores a balance between dynamic, generative software and controlled authorship. The formal qualities of MicroImage were selected to enable the dynamic structure to be highly visible. Each organism consists of two text files written in the C++ programming language. These files, micro.cpp and micro.h are respectively 265 and 48 lines long. The files specify the behavior of each organism by defining the rules for how it responds to its simulated environment. After making a range of form explorations, each organism was given the most minimal visual form possible on computer screen a pixel. To differentiate the various categories of organisms, each type was assigned a distinct color. Aggressive organisms were assigned warm colors and passive organisms were assigned cool colors. As a further refinement, the values of the colors were modified to change in relation to the speed of the organism. When the organism is moving at its maximum speed it is represented with its pure hue, but as it slows down the hue changes along a gradient until it reaches black. I soon realized that representing the organisms with a single pixel placed too much emphasis on their location and not their quality of movement. In the current software, the representation was changed to an extended pixel a line. Each organism is displayed as a line connecting its current position and its previous twenty positions. Through this visualization, the movement of each organism is seen in both static images and kinematic representations. The linear notation allows the viewer to discern the past and present motion of the organism. The future movement may be imagined through following the degree of curvature in the line. The core of the MicroImage software was written in one day over two years ago. The current version of the software has developed through a gradual evolution. While the base algorithm controlling the movement was constructed in a rational way, subsequent developments were the result of aesthetic judgments constructed through many months of interacting with the software. Through directly manipulating the code, I was able to develop hundreds of quick iterations and make decisions based on analyzing the responsive structures created by the code. This process was more similar to intuitive sketching than rational calculation.

Self organization and other emergent processes
Umberto Roncoroni

Problem: is it possible and useful to develop a truly self-organized software system, in other words, an artificial system capable of autonomy and independence from the artist structural order? Actually, we already have enough over production of human art to accept the increased estaethic saturation that computers automation will produce. Nevertheless, for Artware3 I'm presenting two projects of artifical art just becuase they seek some answers, by technical and teoretical means, to these questions; in this case, the artwork production is only marginally interesting, in fact what I try to analize is the meaning of emergence and self organization inside the deepest dynamics of artistic creation. Posing that digital technology today cuestions creativity inside every aspect of all possible human activities, artificial processes should be investigated more deeply; here, art is an important tool due to its holistic and humanist nature and because this research could be virtually free from political and economical influences. Open and indeterministic processes, such as autopoiesis, self organization and emergence, when translated into algorithms and implemented into software code, let investigate and experiment the power of interaction and evaluate the benefits of the interdisciplinary and systemic approach, that play a primary but unknown role into creative processes. Inside these two projects, then, its investigated the possibility to design and develop such a digital visual language and verify its capability to generate a complete autonomous order. Thus, I'm compelled to avoid the tipical tips and tricks of abstract or decorative visual languages that plague computer art: for instance, simmetry, tassellation, or random numbers generators that offer only a pale copy of natural complexity. But what I really think is that a true artificial autopoiesis is not possible: every algorithmic process is deterministic and only appears autonomous and emergent because of the extreme complexity of the systemic interaction that iteration can produce. But the fact that we can't understand or control the final state of some system (actually, this is what chaos theory tries to understand) doesn't mean that the same system is capable of self organization. This option only belongs to living systems, the only ones that, following Bertalanffy and Maturana, we are cleared to define as really autopoietic. So artificial cybernetic systems are closed and order is a behavior determined and designed by the artist/programmer. Nevertheless, this doesn't mean that the aesthetic importance of these tecniques is weakened: it just implies to change the artisitc goal we are trying to score. This goal is the interactive relationship that is generated in the software context between simulated emergence, information and data space embedded into the software, the interfaces media functionality and the new role of the artist and the reader/public. So simuylated emergence offer the chance to globally explore the creative structures that are generated by digital tools. We need to understand how these tools interact and the power that properly belongs to each one: new flavors of interaction emerge and seek our consciousness, and this posit new problems that we can't just put aside. These elements discuss the links between technology, art and postmodern culture, especially regarding some aspects of that some theoreticians interprete as fragmented, free and indeterministic.
Self similar organic system
This set of images are generated with a software package that I started to develop a couple of years ago. Basically, these algorithms concoct two natural processes: self similarity and micro organic life. First of all, a macroscopic structure is built, using Cellular Automata (a simple artificial life technique), then this artificial structure is visualized at microscopic level, using another generative process (something like Lindenmayer systems). Now this two levels communicate to each other to build a third system, more complex and self similar both in the macroscopic and microscopic plane. It is really interesting to study the dynamic interactions and the artistic power of the different forms of the link between artificial beings and the software user, that through interface objetcs takes some kind of control over the process (in fact, the system is to be considered as open). In the first place, we are developing a new art form, that expand the field of creativity and its related dynamics outside the boundaries of individuality towards the complexity of natural systems, through a parallel bottom up approach (the artist doesn't impose a predetermined artistic idea, but lets this idea emerge from feedback); secondly and inside the creative behavior, the role of knowledge and of interface media is also properly discussed.
Emergent structures
These images are the instances of an experiment that deals with those elements that, starting over a simple initial condition (in this case a square environment and two particles that run inside this space mutually modifying their paths) could possibly generate not only complexity, but the maximum formal and structural diversification and indetermination. I'm doing this following some conditions: first, not to use random functions; second, not to use simmetry or other kinds of deterministic order that are an illusion of real complexity. Pictures are organized to reflect the development of this research, and parameters or other process that are implemented are explicit and transparent to the user and can be resumed in a) spatial and position relationships b) sensibility to environment changes that depends on the particles status c) feedback between environment and particle behavior. The important aspect is the complexity architecture, this means to design relationships and links in order to develop a free formal construction. Thus, the interesting thing here is the modifications that affect the creative process: this devolps into something interactive, multi author, interdisciplinary. It is focused on the dynamics not in the artwork itself. Creations occurs not by forza di levare as Michelangelo said, but by growth, interaction, collaboration, and shared knowledge. This project is just a first approach to a field that needs to be more deeply studied: in the first place, digital tools (software and interface) are evolving into a parallel aesthetic process; this interference with the artwork is precisely the context that appears to be still aesthetically unknown.