Genetic Algorithms: Learning by Evolution

In the Genetic Algorithms (GA) component of this class the students will be initially introduced to the overview of the GA's, and some examples of how a GA might be applied. Then, the students will be introduced to the main components of a GA (population and problem representation, fitness function, selection method, and genetic operators) and the students will be exposed to commonly used techniques and their tradeoffs for each component. Emphasis will be placed on how problem representation can affect the ease with which a GA solves a problem and development of effective problem representation will be stressed. Finally some GA applications will be discussed. A number of the aforementioned GA topics are included in the pdf file below.

Notes |pdf|