Instructor: Dr. Ebrahim Ansari
Office Hours: See my weekly Schedule
Location: Computer Science and Information Technology Dept., Room 219
Required Text: Artificial Intelligence Structures and Strategies for Complex Problem Solving, 6E
Author: George F Luger
Publisher: PERSON /Addison Wesley
Supplementary Material: Lecture noted peovided by teacher
Author: Ebrahim Ansari
In the course, we will give an overview of the main representatives of evolutionary algorithms and explain the algorithms in detail. The main theoretical results about these algorithms as well as practical application examples are discussed. The biological background, basic foundations of optimization theory, and relationships to other fields will complete the course.
The existing approaches to evolutionary computation - including e.g. genetic algorithms, evolution strategies, evolutionary programming, genetic programming, classifier systems - all share the same basic model, but are considerably different in their practical instantiations.
We should learn about these subjects:
Each assignment will have a clearly stated due date and time. Assignments start out being easy but get harder over the semester.
You should prepare and give up your assignments before deadline directly to me.
There will be one final examination.
Your performance in this class will be evaluated using your scores for quizzes, programming assignments, and two tests. The weights of each of these components are listed below. There are no extra credit projects or assignments to improve your grade.
Acts that exceed the bounds defined by the approved collaboration practices will be considered cheating. Such acts include:
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