Catalog description: Solving computation problems by "growing" solutions; simulates natural evolution using analogues of mutation, crossover, and other generic transformations on representations of potential solutions; standard EC techniques such as genetic algorithms and evolutionary programming, mathematical explanations of why they work, and a survey of some applications; the focus is on solving real-world problems using projects. Graduate-level research and possible paper or presentation required for grad cr.
Evolutionary computation's goal is to solve problems by "evolving" solutions. It simulates natural evolution using analogies of mutation, crossover, and other genetic transformations on representations of potential solutions.
In this course we will examine how evolutionary computation (EC) works, how to apply it to problems, and current research areas in EC. There will be a strong emphasis on research projects and we will read some of the current literature.Prerequisites: CS121 and CS210 or permission of instructor
This course meets from 1:030-11:20 on MWF in JEB 25. Other course information