Genetic algorithm resource

Lately I'm interested in a topic of genetic algorithms, but i couldn't find any good resource. If you know any good resource, book or a site i would appreciate it. I have solid knowledge of algorithms and A.I. but im looking for something with good introduction in genetic programing.

From stackoverflow

• Here is Roger Alsing's recent article about building "Mona Lisa's picture" with a genetic algorithm :http://rogeralsing.com/2008/12/07/genetic-programming-evolution-of-mona-lisa/

  Edited to remove hot link to the picture See: http://rogeralsing.files.wordpress.com/2008/12/evolutionofmonalisa1.gif

  I've implemented my own version of this algorithm:

  

  See http://plindenbaum.blogspot.com/2008/12/random-notes-2008-12.html

  Jamie Penney : Thats a cool image sequence, I doubt the owner of that blog would like you hotlinking it though.

  Pierre : @Jamie. You're right. I removed the link.

  Steve : The original is not even close to a genetic algorithm (haven't looked at yours though). Its simulated annealing with a greedy acceptance criteria.

  bias : Be careful what you're calling a GA!

• If I may plug one of my favorite books, The Algorithm Design Manual by Steve Skiena has a great section on genetic algorithms (plus a lot of other interesting heuristics for solving various types of problems).

• I found Melanie Mitchell's book, An Introduction to Genetic Algorithms, to be very good. For a wider coverage of evolutionary computation topics, Introduction to Evolutionary Computing by Eiben and Smith is also worthwhile.

  If you're just starting out, I recently wrote an introductory article that may be of use.

  There are further links both in that article and also on the home page for my evolutionary computation framework.

• There is a great introduction to genetic algorithms at AI-Junkie.com as well as tutorials on many other AI and machine learning techniques. The genetic algorithms tutorial is aimed to 'explain genetic algorithms sufficiently for you to be able to use them in your own projects' while keeping the mathematics down as much as possible.

• The book Programming Collective Intelligence by OReilly had chapter covering genetic algorithms. It might be a little bit to basic but it was a very illustrating example.

• This is a nice free book on the subject

  http://www.lulu.com/items/volume_63/2167000/2167025/2/print/book.pdf

• A short introduction I wrote a long time ago is available here, but a better short introduction is here.

  For a larger and comprehensive, although somewhat out-dated, list of resources visit the comp.ai.genetic FAQ.

• Practical Genetic Algorithms

• I know this is an old question, but no answer has been accepted yet, so I thought I'd add my own contribution. One of the best free resources in my opinion for all things related to evolutionary computation (genetic algorithms, evolution strategies, genetic programming, etc.) is Sean Luke's online book Essentials of Metaheuristics.

• Best references for me so far:

  • Genetic Algorithms in Search, Optimization, and Machine Learning by David E. Goldberg: a classic, still considered as the bible of GAs by many.
  • An Introduction to Genetic Algorithms by Melanie Mitchell: more recent than the previous reference and packed with probably more interesting examples.
  • A Field Guide to Genetic Programming by Poli, Langdon, McPhee: this is more of a hands on guide and is getting very good reviews.

  Also if you're an absolute beginner I'd suggest you to start with the Hello World of Genetics Algorithms. There's nothing like a nice clean example to get started.