Grammatical Evolution is a new kind of evolutionary algorithm that evolves computer programs in an indirect manner . The evolved "genotype" is a string of numbers (in contrast to the explicit program code genotype of Genetic Programming, for example). These numbers are decoded into a program by using them to index into a BNF description of the program's grammar, and using the indexed productions as the components of the generated program.
This book, written by GE's inventors, explains the process. There is some biological background, a description of the GE algorithm itself, and some simple case-studies demonstrating its effectiveness. If you want a brief, clear overview of GE, and some background material, here it is.
Foundations in Grammatical Evolution for Dynamic Environments is a cutting edge volume illustrating current state of the art in applying grammar-based evolutionary computation to solve real-world problems in dynamic environments. The book provides a clear introduction to dynamic environments and the types of change that can occur in them. This is followed by a detailed description of evolutionary computation, concentrating on the powerful Grammatical Evolution methodology. The book continues by addressing fundamental issues facing all Evolutionary Algorithms in dynamic problems, such as how to adapt and generate constants, how to enhance evolvability and maintain diversity. Finally, the developed methods are illustrated with application to the real-world dynamic problem of trading on financial time-series.
This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.