Presentation Khatami Shadi

CELLULAR AUTOMATA

SYSTEMS Dynamic

Static (input only)

Reactive Sytems - the Response is always fixed “designers oftehn use the word ‘interactive’ to describe systems that simply react to input, for example, describing a set of Web pages connected by hyperlinks as interactive media.” -Usman Haque

Input

FUNCTION

Output

Interactive Sytems Syn. Feedback Loop, closed information loop, serlf-regulating systems, recirculating system - The response is dynamic and dependent on the input

Input

Dynamic

Static (input only)

Feedback

SYSTEMS

FUNCTION

Output

First Order - Simple feedback loop - Has only one loop - Can not adjust its own goals Feedback

Input

SET FUNCTION

Output

Second Order

- Can modify its goals based on the effects of another system or inputs from the environment - Second order systems can be nested within one other and they can either reinforce each either or have competing goals.

Assess Outcome

Dynamic

Static (input only)

Reactive Interactive

Syn. Learning System, Self adjusting system

SYSTEMS

DETERMINE FUNCTION

First Order System Output Environmental factor Second Order System Output

Output

CELLULAR AUTOMATA A regular

grid of cells with finite states and a defined neighbourhood. any dimension

eg. on/off

eg. A cell’s neighbourhood can be itself and its surrounding cells in any direction up to 2 cells distance.

First Order Second Order

Time = 0 Cells are given a defined state to begin with.

Ti = 1 unit Time ge generation 1 Each cell

assesses its own state and the state of its neighbours and responds according to a set of rules.

SYSTEMS

eg. If 2 or more neighbours are ‘on’, turn ‘off.’ Otherwise, remain ‘on’

Time = 2 unit Ti generation 2 g Each cell

Time Ti = 3 unit generation 3 g

Dynamic

Static (input only)

Reactive Interactive

according to some fixed rule

Time Ti = 4 unit generation 4 g

re-asesses its own state and the state of its neighbours and responds according to a set of rules. typically the rules are the same for all cells and are applied to all cells simultaneously.

Conway’s Game of Life - Neighbours = directly surrounding cells. States = live/dead. Rules: 1_cell with fewer than 2 live neighbours dies. 2_Cell with more than 3 live neighbours dies. 3_Cell with 2 or 3 live neighbours lives to next generation. 4_dead cell with exactly 3 live neighbours becomes live.

Brian’s Brain - Neighbours = directly surrounding cells.States =on/dying/off. Rules: 1_off cell turns on if exactly two neighbours are on. 2_On cells enter a dying state.3_dying cells go to off state.

CELLULAR AUTOMATA - Digital Models

CELLULAR AUTOMATA - Digital Model (2D) < http://www.youtube.com/watch?v=xOL0gXEEl5c>

CELLULAR AUTOMATA - Digital Model (2D)

CELLULAR AUTOMATA - Digital Model (3D)

Mixing of two liquids appears random. However, the process follows a definite set of rules. Each molecules ability to move and therefore mix depends on its own physical properties and the physical properties of its neighbours. These conditions are assessed and direction and speed of motion are determined accordingly.

CELLULAR AUTOMATA - Biological Model (mixing of liquids)

Each cell undergoes a chemical reaction activated by motion or its adjacent neighbours.

CELLULAR AUTOMATA - Biological Model (bioluminescent algae)

Secretion of pigment from each cell is dependant on its neighbouring cells similar to Rule 30 where cells are activated based on a mathematical sequence of numbers.

CELLULAR AUTOMATA - Biological Model (conus seashells) < http://en.wikipedia.org/wiki/Cellular_automaton>

Déplacements It consists of 24 cells arranged in a grid. Each fan acts as a cell and is activated according to the ‘game of life’. Hardware: 24 fans, 3 Pico IP systems, 1 computer. Software: Processing, PicoLib. (Developed Braun)

CELLULAR AUTOMATA - Physical Model < http://www.decept.org/nolife/index_english.html#video>

by

Manuel

Evil/Live 2 - 256 halogen lights and speakers were arranged in a 16 x16 grid each acting as a cell and following the rules of ‘game of life’.

(Developed by Bill Vorn)

CELLULAR AUTOMATA - Physical Model < http://blog.makezine.com/archive/2008/11/game_of_life_materialized.html>

Propagaciones -

It consists of 50 small robots installed on top of poles. They are all made of similar circuits but each looks different. They interact with people around them and among each other by turning lights on and spinning around. Each follows the rules from Conway’s game of life.

(Developed by Leandro Núñez )

CELLULAR AUTOMATA - Physical Model < www.we-make-money-not-art.com/yyy/0aaarco98ub.jpg>

Adaptive Fa[ca]de -

An adaptive skin that is constantly training itself to understand the environment. It uses an artificial neural network that responds to the level of light in the environment aiming to provide optimal light intensity for a space.

(Developed by Marilena Skavara )

CELLULAR AUTOMATA - Physical Model < http://www.digital-architecture.org/hinterlands/exhibitor/marilena-skavara/>