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Generative Art and Computational Creativity

Simon Fraser University via Kadenze

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This course proposes an introduction and overview of the history and practice of generative arts and computational creativity with an emphasis on the formal paradigms and algorithms used for generation.

On the technical side, we will study core techniques from mathematics, artificial intelligence, and artificial life that are used by artists, designers and musicians across the creative industry. We will start with processes involving chance operations, chaos theory and fractals and move on to see how stochastic processes, and rule-based approaches can be used to explore creative spaces. We will study agents and multi-agent systems and delve into cellular automata, and virtual ecosystems to explore their potential to create novel and valuable artifacts and aesthetic experiences.

The presentation is illustrated by numerous examples from past and current productions across creative practices such as visual art, new media, music, poetry, literature, performing arts, design, architecture, games, robot-art, bio-art and net-art. Students get to practice these algorithms first hand and develop new generative pieces through assignments and projects in MAX. Finally, the course addresses relevant philosophical, and societal debates associated with the automation of creative tasks.

Music for this course was composed with the StyleMachineLite Max for Live engine of Metacreative Inc.
Artistic direction: Philippe Pasquier, Programmation: Arne Eigenfeldt, Sound Production: Philippe

Taught by

Philippe Pasquier
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What are MOOCs?
MOOCs stand for Massive Open Online Courses. These are free online courses from universities around the world (eg. Stanford Harvard MIT) offered to anyone with an internet connection.
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Reviews for Kadenze's Generative Art and Computational Creativity
4.5 Based on 2 reviews

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5.0 8 months ago
Anonymous completed this course.
I found the course very enriching and complete in what it covers and I enjoyed doing the course work. We discover a wide range of artists in all fields of art (that includes music of course) who have put into practice generative art and computational creativity in their special fields of art. The course is up to date. I have read about markov chains and Lindberg generation but with this course I learned how to apply them in Max/MSP/Jitter, and that's great. The coursework is well thought out and the homeworks not only allow us to apply what we learned but to go further in our personal artistic practice if we wish.

The course is so rich that I recommend taking a lot of notes for future reference otherwise one forgets.
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4.0 8 months ago
Anonymous partially completed this course.
this course requires quite a lot of prior knowledge but it's really interesting even if you are not that familiar with the subject
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