This page, http://www.cs.uiowa.edu/~hzhang/c145/, is always under construction.


CS4420 (22C:145) - Artificial Intelligence, Fall 2014

Prerequisites: Grades of C- or higher in 22C:031.

11:00-12:15 TuTh, Room 61 SH


Instructor: Hantao Zhang
Office: 201B MLH,
Email: hantao-zhang@uiowa.edu,
Tel: (319) 353-2545
Office hours: TuTh, 1:00-2:30
TA: Aaron (Shiyao) Wang
Office: 201C
Email: shiyao-wang@uiowa.edu,
Tel:
Office hours: MWF 1-2PM,


Textbooks

In addition, a number of class notes and handouts will be available through the course web site.


Course Purpose

This is a survey course on Artificial Intelligence (AI). The overall goal is to introduce students to a number of topics and techniques in AI. Students should be prepared to put in considerable time and effort into reading and programming to become familiar with these topics and gain experience with these techniques. At the end of the semester, students should have the knowledge required to identify areas which they would like to investigate in more depth in related courses. This knowledge includes:

First Midterm on 10/16/14 (75 minutes in class) (30% of final score)
exam problems from last year
answer keys to problems

Second Midterm on 12/11/14 (75 minutes in class) (35% of final score)
2013 final exam problems


Class Participation (5% of final score)


Homeworks (Six, each counts for 5% of final score)

LATE-DUE HOMEWORK ARE NOT ACCEPTED.
For homeworks involving programming, please submit your code and a transcipt of a sample run.


Policies

For the policies on ACADEMIC DISHONESTY and PROCEDURE FOR COMPLAINT, see the Student Academic Handbook, http://www.clas.uiowa.edu/students/academic_handbook/index.shtml of the Colleage of Liberal Arts and Sciences.

The instructor of this course will follow the policies outlined at http://www.clas.uiowa.edu/faculty/teaching/new_policytemplate.shtml for ACCOMMODATIONS FOR DISABILITIES, UNDERSTANDING SEXUAL HARASSMENT, REACTING SAFELY TO SEVERE WEATHER.

For more details, please see the syllabus.


Popular Books Related to AI


Lecture Notes

You are expected to study all the material in each chapter covered in the readings even if that material is not explicitly discussed in class or in the homework. You are also expected to study the extra material presented in class which is not in the textbook. Material presented in class, but not in the book may appear on tests.

The lecture notes are a supplement to the course textbook. They are supposed to help you understand the textbook material better, they are not a replacement for either the textbook or the lecture itself.



Hantao Zhang