REQ: Kadenze Generative Art and Computational Creativity (Simon Fraser University)
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
Course 1: Generative Art and Computational Creativity
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
Course 2: Advanced Generative Art and Computational Creativity
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
Featured Coursework
- Identify and analyze generative art pieces
- Adapt and improve generative art patches in Max/MSP
- Design and develop a new and original generative system
- 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
Course 1: Generative Art and Computational Creativity
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
Course 2: Advanced Generative Art and Computational Creativity
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
Featured Coursework
- Identify and analyze generative art pieces
- Adapt and improve generative art patches in Max/MSP
- Design and develop a new and original generative system