AI: Genetic Algorithms and the Top of the Heap
When I started working with GAs some 13 years ago, I picked up the seminal books of the time: "Adaptation in Natural and Artificial Systems" (ANAS) by Dr. John H. Holland and "Genetic Algorithms in Search Optimization and Machine Learning" (GASOML) by Dr. David E. Goldberg. Holland's book is thick with math (you'd think that I'd love this), but I found as an introductory book that it did not provide for a practical treatment of this discipline. It jumped in head first into theory (somewhat as I do in many of my posts here). I now find Holland's book a pleasure to review and revisit on a regular basis.
The book that gave me a formal introduction to GAs, including a gentle introduction, was Dr. Goldberg's book. So after 13 years of this stuff, I decided to email Dr. Goldberg and thank him for the groundbreaking work he has done. I'm certain that I'm not the first nor the last to do this. Goldberg, Holland, Koza and many others paved the way in GA and GP as we know it today. I received a great response in return and am happy to find him both approachable and thoughtful.
Dr. Goldberg has been blogging for some time now and you may find him here. He is affiliated with the University of Illinois at Champaign-Urbana (home of the Fighing Illini, the bane of my Wisconsin Badgers in basketball) and has a great deal of resources available for the GA professional, academic and practitioner alike. I've noticed that he has a recent book available as well "The Design of Innovation" that may be found here. I've ordered it and will post a review after a thorough read as time permits.
If you wish to be competent in GA and have no formal exposure in this discipline, GASOML is a MUST. If you are a math guy or gal, ANAS is the foundation for this discipline.
His recent post here, leads me to believe he has a better grasp of both GAs and the ability to unwind than I. I'm curious if there is noodle salad on board . . .