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: PhilippeBertrand
Session 1: Introduction and Ontology of Generative Art (February 1, 2016) In this session, we define generative art and computational creativity and establish a typology of generative systems based on levels of autonomy and agency. Session 2: History of Generative Art (from pre-history to the 80s) (February 2, 2016) Generative art is nothing new, and this session goes through the history of the field from pre-history to the 80s Session 3: Generative Art and Text (February 2, 2016) This session focuses on generative processes deployed in literature, poetry and other written forms. Session 4: Generative Music (February 2, 2016) In this session, algorithms used for the generation of both notated and interpreted music are reviewed. Session 5: Generative Visual Art, Video, and Film (February 2, 2016) This session explores the various processes deployed to date in the field of static and moving images. Session 6: Generative Sculpture, Design, and Architecture (February 2, 2016) 3D and tangible realizations based on generative systems are reviewed in this session. Session 7: Generative Art and Performance, Dance, Theatre, and Circus (February 2, 2016) This session is exploring the various uses of generative systems in performative disciplines. Session 8: Generative Art and Games (February 2, 2016) This session reviews how generative algorithms are used in video games from procedural level generation to computational narratives and automatic character design. Session 9: Generative Art, Robotics, bio-Art and Web Art (February 2, 2016) This session introduces generative systems deployed in disciplines that did not exist before the computerization of our societies, such as robotics, Web Art, Virtual Reality, biotech-based art. Session 10: Computer-assisted Creativity (February 2, 2016) This session, defines the main concepts and approaches used in systems that are designed to collaborate with humans in their creative tasks. Session 11: Valuation and Evaluation of Generative Art (February 2, 2016) In this session, we explore the methodologies that can be used to evaluate how successful a given generative system is. Can a generative system be as good, or sometimes better than humans at their specific task? Session 12: Generative Art, Authorship and Societal Perspectives (February 2, 2016) This session concludes the course by deepening our understanding of the possible applications and implications of generative art. We address ethical, and philosophical concerns that can be raised by generative systems. What does developing or using a generative system means in terms of authorship and creativity
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.