Complexity and Emergence
Cellular Automata
Inspired by Go, originally implemented as analog system.
Try it in motion online or offline.
Reminds of fire burning forests, bacteria, molds, etc…
(SimCity is based on cellular automata as well)
Flocks
Flock algorithm (Boids) implementation in processing
Birds, fish, bugs, buffalos…
1) Don’t get too crowded.
2) Don’t get too isolated.
3) Swim with neighbors.
(An optional 4th rule is that you should do what it takes to flee predators)
Recursion
In order to understand recursion you must first understand recursion.
Ok, imagine a function that calls itself.
Fractals
Self similar patterns based on mathematical sets. Formulas are relatively simple to define but generate a great level of complexity.
Some resources about fractals here.
Artificial Life
Cindermedusae by Marcin Ignac
Evolutionary algorithms
Darwin Hill (arbitrary selection)
Karl Sims – Evolved Virtual Creatures, Evolution Simulation, 1994
Process:
- Generate the initial population of individuals randomly – first Generation
- Evaluate the fitness of each individual in that population
- Repeat on this generation until termination (time limit, sufficient fitness achieved, etc.):
- Select the best-fit individuals for reproduction – parents
- Breed new individuals through crossover and mutation operations to give birth to offspring
- Evaluate the individual fitness of new individuals
- Replace least-fit population with new individuals
Communion by Matt Pyke (Universal Everything) and Field.io – Marcus Wendt and Vera-Maria Glahn. Video here.
The installation is in a rectangular room with 6 separate projection on the walls creating almost a 360º environment. The final piece includes an array or evolving creatures going through stages of development – evolution from simple to complex with human like properties with generative behaviours
Want more of this? Read Out of control by Kelvin Kelly. Not extremely new, a little too Californian Ideology (pre dot com boom) but still good.