We limit workshop attendance to 8-10 people per session. If there is sufficient interest, we will schedule multiple sessions of some workshops. A number of different EAs have been studied, but they all share some common elements and processes. The better structures are allowed to reproduce and the structures which do not perform as well are eliminated. Most importantly, variation is introduced into the offspring structures, providing a mechanism for exploration of the space of possible structures.
Many variants perform no better, or even worse, than the parents, but some offspring perform better.
This generational process is repeated, leading to continuing adaptation of the structures. By defining the appropriate structures and evaluation function, EAs have been used in a wide variety of search and optimization problems and in many kinds of machine learning systems. Examples of each EA will be discussed and the differences between the approaches will be outlined. Handouts will include references to sources of further information, including information and software packages available via the Internet. That is, an initial population of randomly generated computer programs are evaluated to rate how well they solve the problem at hand.