At the EvoStar 2008 evolutionary computation conference in Naples, Italy (man, I wish I could have gone), three scientists have released the completely free and downloadable book, “A Field Guide To Genetic Programming”.
Genetic programming (GP) is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until high-fitness solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions.
This unique overview of this exciting technique is written by three of the most active scientists in GP.
This is an incredibly useful and practical book for anyone interested in artificial intelligence and machine learning. It is an up-to-date guide to the subject, summarizing two decades of research.
What kind of problems are genetic programs good at solving? The book tells you what traits these problems have:
- The interrelationships among the relevant variables is unknown or poorly understood (or where it is suspected that the current understanding may possibly be wrong).
- Finding the size and shape of the ultimate solution is a major part of the problem.
- Signiﬁcant amounts of test data are available in computer-readable form.
- There are good simulators to test the performance of tentative solutions to a problem, but poor methods to directly obtain good solutions.
- Conventional mathematical analysis does not, or cannot, provide analytic solutions.
- An approximate solution is acceptable (or is the only result that is ever likely to be obtained).
- Small improvements in performance are routinely measured (or easily measurable) and highly prized.
Get the book here.