Second lecture in Algorithmic Design course at
@AaltoARTS deals with fundamentals of algorithmic design - mathematical building blocks for computation.

Session 2.1. - Fundamentals

#algorithmicdesign #generativeart #computationaldesign
@AaltoARTS "The purpose of computing is insight, not numbers." quote by Richard Hamming.

Computational design is about exposing the creative process by making it explicit, in form of a formal diagram or code. Designers are often not trained to do this, so they complain.
Reconstruction of Alberti’s map in “Descriptio urbis Romae”, by Luigi Vagnetti from 1974. Alberti described locations of monuments in Rome using polar coordinates, which is an early example of digital code representing spatial information.
The hexadecimal code for Mies van der Rohe’s Seagram
building, by Lionel March, 1972. Today we would call this a "voxelized" representation.
#computationaldesign #voxels
Code of Life

To decode a DNA codon, move from the center towards
the periphery (left). A series of codons in part of a messenger RNA molecule (right). This molecule will instruct a ribosome to synthesize a protein according to this code.
Design Space

In a parametric model, a dimension can be ascribed to every variable parameter, and thus the model becomes a many-dimensional space. Every point in that space represents a design solution. Diagrams below show solutions to different parametric models.
Color Space

RBG (left) and HSB (right) color spaces. RGB model is capturing physical principles behind mixing of light to create colors, but HSB is more intuitive and closer to how we think of colors. This insight came from @tylerxhobbs and his writings on color and code.
Vector Graphics

Polygons can be represented through a list of their vertices. The order of vertices encodes the edges of the polygon, which can be displayed by connecting adjacent vertices in the list.
We can harness linear algebra to manipulate multi-dimensional arrays containing all kind of data inside, not just numbers. Below, examples of arithmetic operations on arrays in NumPy, a popular library for scientific computing.

#python #numpy
Boolean Algebra of Shapes

Boolean operations and digital logic gates (left) can be used for modeling 3D objects through CSG (constructive solid geometry) implemented in many CAD and modeling software. Foundation for this is set theory in mathematics.

#booleanalgebra #settheory
Concurrent models of computation - many similar parts acting locally in parallel

In algorithmic design, the most popular models of computation are concurrent models. Below, Game of Life cellular automata (left) and agent based model (right) are classic examples of these.
Four computer-generated random patterns based on the composition criteria of Mondrian’s “Composition With Lines”, by A. Michael Noll, 1965

In algorithmic design, randomness and its forms are essential for producing variation and introducing unpredictability. Diagram shows coverage of the unit square with randomly distributed points. Above for additive quasi-random numbers, below for pseudo-random numbers.
Pseudo-randomness in Nature

Rule 30 cellular automaton is a type of pseudo-random number generator. Interestingly, Conus textile shell pattern is similar in appearance to Rule 30 🤯

#rule30 #cellularautomata
Recommended reading:

“The Logic of Architecture - Design, Computation and
Cognition” by William J. Mitchell (1986)
“Architecture After the Age of Printing” by Peter Eisenman (1992)

#algorithmicdesign #computationaldesign
To get our hands dirty, let's do a simple coding exercise using #python in #rhino3d - a classic random walk structure ↓

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Recommendations from around the web and our community.

This is a great summary. I can’t overstate how much of a positive difference it made for me to switch to HSB. I hope everyone gives it a good try