Generative Art and Computational Creativity
Kıvanç Tatar is a musician playing trumpet and electronics, a composer interested in experimental music, and a researcher studying artificial intelligence on the applications of musical tasks. His work has been exhibited in Germany, Italy, Brazil, Australia, USA, Canada, and Turkey; including the events Mutek_IMG, and the cultural program at 2016 Rio Olympics. His performance practice combines free improvisation with live electronics. Currently, he is a Ph.D. student at School of Interactive Arts and Technology, Simon Fraser University. In the Metacreation Lab, he is working on audio synthesis, generative art, musical composition, musical performance with artificial intelligence, and Musical Metacreation.
Research interests: Computational Creativity, Evolutionary Computation, Musical Agent Design, Artificial Intelligence, Multi-agent Systems, Machine Listening, and Machine Improvisation, and Performance Studies.
Arne Eigenfeldt is a composer of live electroacoustic music, and a researcher into intelligent realtime music systems. His music has been performed around the world, and his collaborations range from Persian Tar masters to contemporary dance companies to musical robots. He is currently a professor of music and technology at Simon Fraser University, Canada, and is the co-director of the MetaCreation Lab (metacreation.net), which aims to endow computers with creative behaviour.
His research into intelligent musical agents has been presented at conferences such as ICMC, NIME, ISMIR, ICCC, GECCO, EvoMusArt, EMS, SMC, ISEA, and CHI, while the artistic output of his systems have been shown at ICMC, SMC, ISEA, SEAMUS, and Generative Arts.
This program offers an in-depth overview of the history and practice of generative systems applied to creative tasks. After defining generative art and computational creativity, students will be introduced to the various families of algorithms from artificial intelligence, machine learning, and artificial life that have been used for generative processes so far. The lecture material is illustrated by numerous examples from past and current productions across creative practices such as visual art, music, poetry, literature, performing arts, design, architecture, games, bioart and robotic art. The coursework will have you putting some of these algorithms to practical use in developing new generative pieces using the graphical programming language Max. This program will provide you with an approachable but comprehensive knowledge of some of the most powerful algorithms out there while addressing relevant philosophical and societal debates associated with the automation of creative tasks.
- Ability to identify, describe, evaluate, critique, and contrast generative artworks and computationally creative systems
- Ability to implement and test generative art systems by using Max at an intermediate to advanced level
- Understanding of and ability to articulate and discuss the societal, ethical, and philosophical issues surrounding computational creativity and generative art practices
- Session 1: Introduction and Typology of Generative Art
- Session 2: History Of Generative Art, Chance Operations, and Chaos Theory
- Session 3: Rule-Based Systems, Grammars and Markov Chains
- Session 4: Cognitive Agents And Multiagent Systems
- Session 5: Reactive Agents And Multiagent Systems
- Session 6: A-Life And Cellular Automaton
- Session 7: Introduction and Typology of Generative Art
- Session 1: Evolutionary Computing and Genetic Algorithms
- Session 2: Genetic Programming and Evolutionary Ecosystems
- Session 3: Artificial Neural Networks and Deep Learning
- Session 4: Search-based Approaches to Creativity
- Session 5: Evaluation Methods for Computational Creativity
- Session 6: Societal and Philosophical Perspectives
- Identify and analyze generative art pieces
- Adapt and improve generative art patches in Max/MSP
- Design and develop a new and original generative system
- Equipment: PC or Mac computer with installation privileges
- Software: Max 7
Students should have intermediate knowledge of Max/MSP in order to complete assignments.
- A verified Specialist Certificate that prove you completed the Program and mastered the subject.*
- A verified course Certificate for each individual course you complete in the program.*
- 3.0 transferable academic college credit(s) (additional fees apply)
* Each certificate earned is endorsed by Kadenze and the offering institution(s).
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