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--Introduction--
This project seeks to provide an introduction to core concepts in genetics,
evolution, and programming. The material makes no assumptions regarding the
hypothetical students knowledge of evolution, taking an approach of 'show'
rather than 'tell'. A basic understanding of ecology and statistics may
enhance one's appreciation of the subject.
Regarding experience with computers and programming, some basic skills and
tools are required. One should have Python 2.7 installed, have a good text
editor, and be able to type instructions in a terminal. For Linux and Mac,
gedit is one of many good text editing options for beginners, and for Windows
I recommend Notepad++. Linux and Mac users should know how to open Terminal,
and Windows users should know how to open Command Prompt. There are a few ways
to run python programs, and one should familiarize oneself with how to supply
arguments to a commandline program. A commandline example:
'python run_sim.py --popsize 128'
In this instance, "--popsize 128" tells the program from the start to use 128
as the value for the population size in the simulation.
Each exercise should provide one with the needed cues to begin examining the
code for important details and how to run the code (see each README.txt).
Depending on ones experience, some parts of the code may be slightly complex.
Comments in the code are provided to help guide one through what tasks are
being accomplished. Each exercise should come with a set of questions to help
highlight critical concepts.
--Acknowledgments--
This project was sparked by a post by Christopher Gilbert at MotomaSTYLE:
http://motomastyle.com/genetic-programming-the-python-way-the-basics/
which was a Python implementation of Chris Eigner's Genetic Programming 101
in Ruby:
http://eignerchris.tumblr.com/post/428590094/genetic-programming-101-ruby
I owe them thanks for their work which prompted me along into genetic
programming and for some inspiration of my own code. I hope that my own work
might do the same for others.
- Pablo -