I485: Biologically Inspired Computing
Lab 1: Introduction to bioinspired algorithms in Python
Contents
Existing knowledge of ...
Programming?
Python?
Netlogo?
Graphics programming?
Implementing algorithms?
Bio-inspired/alife/multi-agent programming?
To do the (five) lab assignments this semester, we will need to ...
Implement the appropriate biologically-inspired algorithms
(examples: genetic algorithms, fractals, ant-colony inspired algorithms, etc.)
Support them with the approriate data-structures
(examples: genomes & mutation operators, spatial virtual worlds, data points & labels, etc.)
Handle I/O to algorithms
(get user parameters,
display graphics
, read/write files, etc.)
Finally, the logistics: submit to Oncourse
Today, we will cover:
Two ways of doing graphics in Python:
turtle module
- Logo-type Turtle graphics for python
Pygame
- Python game programming module
Some simple algorithms to demonstrate these abilities:
Koch curve / snowflake (subset of L-systems):
koch.py.txt
Game of life (cellular automata):
life.py.txt
Questions?
More
Acknowledgements
Lab prepared by
Artemy Kolchinsky
.
Links
All Class Labs
I485/I585 Biologically-inspired Computing
Life Inspired
For more information contact
Artemy Kolchinsky
or
Luis Rocha
.
Last Modified: February 2, 2009