Generative art refers to art that in whole or in part has been created with the use of an autonomous system. An autonomous system in this context is generally one that is non-human and can independently determine features of an artwork that would otherwise require decisions made directly by the artist. In some cases the human creator may claim that the generative system represents their own artistic idea, and in others that the system takes on the role of the creator.
The Generative Art is a contemporary form of artistic creation, whereby not necessarily the artwork or end product is in the center, but the creation process and the underlying ideas. The work or product is created by processing a processual invention, that is, a set of rules created by the artist or a program that is recorded in the form of, for example, natural language, musical language, a binary code, or a mechanism.
“Generative art” is often used to refer to algorithmic art (computer generated artwork that is algorithmically determined). But generative art can also be made using systems of chemistry, biology, mechanics and robotics, smart materials, manual randomization, mathematics, data mapping, symmetry, tiling, and more. Many works that make organic expressions with a sense of unity, such as the middle of artificiality and nature, by utilizing the freedom of calculation and the computational speed of computer and executing the theory obtained in natural science.
Generative art often serves artists as a means to avoid intentionality. The processing takes place in a self-organizing manner, in the form of a relatively autonomous process, such as actions that – as in the score to a happening – are made according to instructions, by a computer program that executes instructions, image information or other concepts, or by other media and aids. Under different production conditions, the process runs differently. The result moves in more or less given limits, but is unpredictable in it.
Generative art refers to a work of art that is algorithmically generated, synthesized and constructed by computer software algorithms or mathematical / mechanical / random autonomous processes. Many works that make organic expressions with a sense of unity, such as the middle of artificiality and nature, by utilizing the freedom of calculation and the computational speed of computer and executing the theory obtained in natural science.
Generative art is an art using a natural scientific system as a main subject as a creation method. As a premise, it can be said that it differs from other art sectors in that it is necessary to design a mechanism that operates autonomously and create a work. Works by the system may execute scientific theories such as complex systems and information theory. The system constructed with generative art is very similar to the system found in various fields of science. Such a system changes the degree of complexity over time in the edge of chaos and shows unpredictable behavior by going back and forth between chaos and order. However, the system itself operates deterministically. Wolfgang Amadeus Mozart’s “Musikalisches Würfelspiel” (music dice play) 1757 is an early example of a generic system based on randomness. Its structure is based on the elements of order on the one hand and on the other hand on the elements of disorder.
Since the creator is required to have a high degree of mathematical image capability and complicated algorithm devising and packaging technology, the threshold for entry is high. It is also an area where people enrolled in the science field who are good at handling mathematical formulas and algorithms enter the field by touching works in this field and feeling a strong appeal. Artists or creators prepare certain basic principles, materials such as mathematical formulas and templates, and process them so that a random or semi-random process works. In many works, even in its basic principle, by constructing a system that interacts with each other between the theoretical elements, enabling complicated expressions that can not be obtained only by linear addition synthesis of simple elements There. The result will remain to some extent within the set limits, but there is also a tendency to produce subtle and bold changes. The idea of conducting artistic creation activities based on existing artworks and the like is one of the important elements of generative art and represents the fundamental nature of the process oriented.
Generative art sometimes introduces real-time nature, and applies feedback and generation processes to the present state of the work and changes it every now and then. Such works never see the same situation again. For demonstration scenes and video jockey culture etc. use various graphical programming environments (eg Max / Msp, Pure Data) to create real-time generative audiovisual work.
Until the appearance of Processing in the 2000s, the programming environment that can concentrate only on the essence of creative content was not maintained, and it is still difficult to say that it is a general creation method. Coupled with the prosperity of media art in various advertising media (Web site, digital signage, etc.) and events in the 2010s and the spread of Processing and openFrameworks in school education of arts, it is a field expected to develop in the future.
Artificial intelligence and automated “behavior” are introduced as a new means of generative art. Generative art is not an art movement or ideology. It is just a creative method, not related to the intention and content of the work.
Generative art theories:
In the most widely cited theory of generative art, in 2003 Philip Galanter describes generative art systems in the context of complexity theory. In particular the notion of Murray Gell-Mann and Seth Lloyd’s effective complexity is cited. In this view both highly ordered and highly disordered generative art can be viewed as simple. Highly ordered generative art minimizes entropy and allows maximal data compression, and highly disordered generative art maximizes entropy and disallows significant data compression. Maximally complex generative art blends order and disorder in a manner similar to biological life, and indeed biologically inspired methods are most frequently used to create complex generative art. This view is at odds with the earlier information theory influenced views of Max Bense and Abraham Moles where complexity in art increases with disorder.
Galanter notes further that given the use of visual symmetry, pattern, and repetition by the most ancient known cultures generative art is as old as art itself. He also addresses the mistaken equivalence by some that rule-based art is synonymous with generative art. For example, some art is based on constraint rules that disallow the use of certain colors or shapes. Such art is not generative because constraint rules are not constructive, i.e. by themselves they don’t assert what is to be done, only what cannot be done.
Margaret Boden and Ernest Edmonds:
In their 2009 article, Margaret Boden and Ernest Edmonds agree that generative art need not be restricted to that done using computers, and that some rule-based art is not generative. They develop a technical vocabulary that includes Ele-art (electronic art), C-art (computer art), D-art (digital art), CA-art (computer assisted art), G-art (generative art), CG-art (computer based generative art), Evo-art (evolutionary based art), R-art (robotic art), I-art (interactive art), CI-art (computer based interactive art), and VR-art (virtual reality art).
Types of generative art:
Johann Philipp Kirnberger’s “Musikalisches Würfelspiel” (Musical Dice Game) 1757 is considered an early example of a generative system based on randomness. Dice were used to select musical sequences from a numbered pool of previously composed phrases. This system provided a balance of order and disorder. The structure was based on an element of order on one hand, and disorder on the other.
The fugues of J.S. Bach could be considered generative, in that there is a strict underlying process that is followed by the composer. Similarly, serialism follows strict procedures which, in some cases, can be set up to generate entire compositions with limited human intervention.
Composers such as John Cage,:13–15 Farmers Manual and Brian Eno:133 have used generative systems in their works.
Generative visual art:
The artist Ellsworth Kelly created paintings by using chance operations to assign colors in a grid. He also created works on paper that he then cut into strips or squares and reassembled using chance operations to determine placement.
Artists such as Hans Haacke have explored processes of physical and social systems in artistic context. François Morellet has used both highly ordered and highly disordered systems in his artwork. Some of his paintings feature regular systems of radial or parallel lines to create Moiré Patterns. In other works he has used chance operations to determine the coloration of grids. Sol LeWitt created generative art in the form of systems expressed in natural language and systems of geometric permutation. Harold Cohen’s AARON system is a longstanding project combining software artificial intelligence with robotic painting devices to create physical artifacts. Steina and Woody Vasulka are video art pioneers who used analog video feedback to create generative art. Video feedback is now cited as an example of deterministic chaos, and the early explorations by the Vasulkas anticipated contemporary science by many years. Software systems exploiting evolutionary computing to create visual form include those created by Scott Draves and Karl Sims. The digital artist Joseph Nechvatal has exploited models of viral contagion. Autopoiesis by Ken Rinaldo includes fifteen musical and robotic sculptures that interact with the public and modify their behaviors based on both the presence of the participants and each other.:144–145 Jean-Pierre Hebert and Roman Verostko are founding members of the Algorists, a group of artists who create their own algorithms to create art. A. Michael Noll, of Bell Telephone Laboratories, Incorporated, programmed computer art using mathematical equations and programmed randomness, starting in 1962. The French artist Jean-Max Albert, beside environmental sculptures like Iapetus, and O=C=O, developed a project dedicated to the vegetation itself, in terms of biological activity. The Calmoduline Monument project is based on the property of a protein, calmodulin, to bond selectively to calcium. Exterior physical constraints (wind, rain, etc.) modify the electric potential of the cellular membranes of a plant and consequently the flux of calcium. However, the calcium controls the expression of the calmoduline gene. The plant can thus, when there is a stimulus, modify its « typical » growth pattern. So the basic principle of this monumental sculpture is that to the extent that they could be picked up and transported, these signals could be enlarged, translated into colors and shapes, and show the plant’s « decisions » suggesting a level of fundamental biological activity.
Maurizio Bolognini works with generative machines to address conceptual and social concerns. Mark Napier is a pioneer in data mapping, creating works based on the streams of zeros and ones in ethernet traffic, as part of the “Carnivore” project. Martin Wattenberg pushed this theme further, transforming “data sets” as diverse as musical scores (in “Shape of Song”, 2001) and Wikipedia edits (History Flow, 2003, with Fernanda Viegas) into dramatic visual compositions. The Canadian artist San Base developed a “Dynamic Painting” algorithm in 2002. Using computer algorithms as “brush strokes,” Base creates sophisticated imagery that evolves over time to produce a fluid, never-repeating artwork.
Software art:For some artists, graphic user interfaces and computer code have become an independent art form in themselves. Adrian Ward created Auto-Illustrator as a commentary on software and generative methods applied to art and design.
In 1987 Celestino Soddu created the artificial DNA of Italian Medieval towns able to generate endless 3D models of cities identifiable as belonging to the idea.
Literature:Writers such as Tristan Tzara, Brion Gysin, and William Burroughs used the cut-up technique to introduce randomization to literature as a generative system. Jackson Mac Low produced computer-assisted poetry and used algorithms to generate texts; Philip M. Parker has written software to automatically generate entire books. Jason Nelson used generative methods with Speech-to-Text software to create a series of digital poems from movies, television and other audio sources
Generative live coding:
Generative systems may be modified while they operate, for example by using interactive programming languages such as Max/MSP, vvvv, Fluxus, Isadora, Quartz Composer and openFrameworks. This is a standard approach to programming by artists, but may also be used to create live music and/or video by manipulating generative systems on stage, a performance practice that has become known as live coding. As with many examples of software art, because live coding emphasises human authorship rather than autonomy, it may be considered in opposition to generative art.
Automatic generation systems:
A very simple computer program makes it possible, thanks to the random draw function of the microprocessor, to automatically choose a predefined number of elements (or itself random and included in an arbitrary range). The program then randomly orders the elements (“we mix the cards”). Finally, these elements are received (seen, heard, etc.) in the order provided by the computer program. The conceptual illustration of this very simple system is the slide show whose photographs (elements previously made by a human) follow each other on a computer screen but at each launch of the viewing program, the order of the photographs is different.
The “random draw with constraints”. This system, much more evolved, allows to operate directly on the constituent elements of the targeted art (pixel, sound, note, word, etc.). In the field of music, for example, it is a question of automatically arranging the notes, one after the other and not as above, to arrange segments of music of a given length and previously played by a or several musicians and recorded in audio (wave) or in a midi file (pattern). Applying this fundamental principle and its research in artificial intelligence, the French René-Louis Baron has designed a process protected by international patents (“MedalComposer”) allowing the composition of millions of melodies “consistent” and orchestrated in all styles musical (including counterpoint). The weight of this program is tiny (40 kilobytes), which allows it to be embedded in a low-cost chip for industrial use. The constrained random draw process allows greater freedom of programming according to the constraints imposed on the composition software. It also offers a greater variety of works generated in existing musical styles or “invented” by the program.