Artificial Life, Generative Art and Creative Code

Code: DATT4950
Title: Artificial Life, Generative Art and Creative Code
Credit: (3.00 Units)
When: Fall 2016, Mondays 10:00 - 13:30
Where: GCFA, ACW 103
Instructor: Graham Wakefield
Email: grrrwaaa at yorku dot ca Prerequisite: LE/EECS 1030 3.0, FA/DATT 2050 3.0, or permission of course director.
Website: http://grrrwaaa.github.io/courses/datt4950/
Code materials: https://github.com/grrrwaaa/courses/tree/master/code

Gallery

Synopsis: This course addresses computation as a creative medium from a biologically-inspired standpoint to develop artworks, adaptive media and simulations approaching the fascinating complexity of nature.

Artists, composers, designers and architects have always drawn inspiration from nature, but until recently only rarely have they been able to leverage nature’s creative mechanisms. From its origins computing has also found biological inspiration in pattern formation, self-construction and reproduction, intelligence, autonomy and collective behaviour. Frameworks explored in the course include complex dynamical systems, fractals, cellular automata, agent-based systems, evolutionary and developmental programming, artificial chemistries and ecosystems.

The course is focused on practice in the arts, interactive media, and design: interactive audiovisual applications are implemented both in-class and through student projects, and are critically examined by interweaving the history, theory and landmark works in the literature of generative art, evolutionary music and art, and process art, as well as artificial life, systems biology, and bioinformatics research, and philosophies of process, creativity, and the aesthetics of nature.

Rationale: Autonomous complexity is one of the fundamental hallmarks of computational art; an integral message of the medium. Biologically-inspired methods of digital media formation have found wide applications in art, film, music, video games, robotics, and other computationally-facilitated experiences, frequently drawing upon scientific models of pattern formation, system dynamics, and symbol processing in large populations. Art has always been deeply concerned with its relationship to nature, though the forms of the relationship have changed many times. Likewise, from its origins computing has also found biological inspiration in pattern formation, self-construction and reproduction, intelligence, autonomy and collective behaviour. This course is necessary to understand such developments from their arts and science foundations, in both theory and practice.

Learning outcomes / objectives: At the completion of the course students will:

Contact hours: 3.5 per week, split between lectures and lab work. Lectures focus on the introduction of theoretical, aesthetic and conceptual content of the course. Labs focus on the application of lecture material in the form of instructor-led reconstructions, excercises/studies, and larger projects, and will include time for one-on-one meetings.

Assessment: Assignments, projects, quizzes, readings and participation, with the following weighting for the final grade:


Schedule

Content may vary from this plan according to needs and interests of students.

1. Sep 12

Course overview. Introduction to the field(s), and the coding environment used in lectures & labs.
Cellular Automata, classes of behaviour, Game of Life.

2. Sep 19

CA variations: non-homogeneity, stochastics, asynchrony, unbounded states. Continuous, reaction-diffusion. Particle/block rule. Multi-scale systems.

3. Sep 26

CA variations: non-homogeneity, stochastics, asynchrony, unbounded states. Continuous, reaction-diffusion. Particle/block rule. Multi-scale systems.

4. Oct 3

Due: Assignment I (15%)

Quiz I (5%)

Agent-based modelling. Turtles and tortoises, vehicles, steering models, random walks.

5. Oct 17

Boids, subsumption architectures.
Agents and fields. Chemotaxis, stigmergy, social models.

6. Oct 24

More on agents and environment. Vehicles again; stigmergy; life, death & resources.

http://codepen.io/grrrwaaa/pen/Zpwkxw?editors=0010

http://codepen.io/grrrwaaa/pen/pEGXNE?editors=0010

http://codepen.io/grrrwaaa/pen/EgrYgV?editors=0010

7. Oct 31

Quiz II (5%)

Due: Assignment II (15%)

Evolution (natural and artificial). Selection models, mutation models, population models.

8. Nov 7

Evolution continued; ecology and ecosystem, aesthetic selection & biomorphs. Genetic programming.

Biomorphs created in the lab today

9. Nov 14

Quiz III (5%)

Assignment III discussion/assistance.

10. Nov 21

Course evaluation

Due: Assignment III (15%)

Special topic: beyond the lab environment.

Final project/portfolio discussion.

Quiz III (5%)

11. Nov 28

Due (in class): Work-in-progress of final project

Rewriting systems and artificial chemistries. Tierra, Alchemy.

Final project/portfolio assistance.

12. Dec 5

Due: Final project (40%)

The 40% is broken into:

(See the deliverables page for more details).


Readings

Highly recommended:

Further reading: