CSC 480 Artificial Intelligence I
Summary
This course will provide an in-depth survey of important concepts, problems, and techniques in artifical intelligence (AI). No previous knowledge of AI is necessary to take the course. The course is particularly suitable for graduate students who want to gain the technical background necessary to build intelligent systems, or as a preparation for more advanced work in AI. Topics will include Intelligent agents, Search techniques, Game playing, Logical reasoning, Planning, Reasoning under uncertainty, and Knowledge representation.
Prerequisite: CSC 301, 383, 393, or 402 (or equivalent knowledge in data structures and algorithms)
Texts
Artificial Intelligence: A Modern Approach, Third edition, by Stuart Russell and Peter Norvig. Prentice-Hall, 2003. ISBN 10-digit: 0-13-604259-7, 13-digit: 978-0-13-604259-4.
Grading
The grade breakdown will be as follows:
| 5 Assignments |
50% |
| Midterm |
25% |
| Final Exam |
25% |
The grading scale will be determined by a curve. The cutoffs will be no higher than the following: 90-100, A; 80-89.99, B; 70-79.99, C; 60-69.99, D; 0-59.99, F. Plusses and minuses will be given at the high/low ends of each grade range (no A+'s or D-'s).
Assignment late policy
To be considered on time, an assignment must be turned in by the beginning of class on its due date. Late submissions may be turned in up to 1 week late; however, late assignments will be penalized 2 points (out of 100) for each day that they are late. Late submissions will not be accepted beyond the beginning of class one week after the due date.
Prerequisites
CSC 301, 383, 393, or 402 (or equivalent knowledge in data structures and algorithms)
Policy on Working Together
You may feel free to discuss assignments with other students or with a tutor at a general level. This may include discussion of issues such as the types of data structures and control flow needed for the assignment. However, you must write all of your own code yourself, and you may not work with others when writing code, with the exception of asking the tutors (or me) for debugging help. It has been my experience that if you write code together, or copy from a friend's old assignment, or if a tutor writes your program for you, you will be caught. Any violations of this policy will be dealt with very seriously.
Intro to AI; Search (if time). Text: Ch. 1-2, 3 (if time)
Search, Game playing. Text: Ch. 3-5.
Logic. Text: Ch. 8.
Logic, cont. Text: Ch 9.
Introduction to Planning; review for Midterm Exam. Text: Ch. 10-11.
Midterm exam; Planning, cont. Text: Ch. 10-11.
Bayesian probabilities and Bayesian networks. Text: Ch. 13-14.
Introduction to Machine Learning. Text: Ch. 18.
Introduction to Natural Language Processing. Text: Ch. 22-23.
TBD; Review for Final Exam.
This syllabus is subject to change as necessary during the quarter. If a change occurs, it will be thoroughly addressed during class, posted under Announcements in D2L and sent via email.
Evaluations are a way for students to provide valuable feedback regarding their instructor and the course. Detailed feedback will enable the instructor to continuously tailor teaching methods and course
content to meet the learning goals of the course and the academic needs of the students. They are a requirement of the course and are key to continue to provide you with the highest quality of teaching. The
evaluations are anonymous; the instructor and administration do not track who entered what responses. A program is used to check if the student completed the evaluations, but the evaluation is completely
separate from the student’s identity. Since 100% participation is our goal, students are sent periodic reminders over three weeks. Students do not receive reminders once they complete the evaluation.
Students complete the evaluation online in CampusConnect.
This course will be subject to the university's academic integrity policy. More information can be found at http://academicintegrity.depaul.edu/ If you
have any questions be sure to consult with your professor.
All students are expected to abide by the University's Academic Integrity Policy which prohibits cheating and other misconduct in student coursework. Publicly sharing or posting online any prior or current materials from this course (including exam questions or answers), is considered to be providing unauthorized assistance prohibited by the policy. Both students who share/post and students who access or use such materials are considered to be cheating under the Policy and will be subject to sanctions for violations of Academic Integrity.
All students are required to manage their class schedules each term in accordance with the deadlines for enrolling and withdrawing as indicated in the University Academic Calendar. Information on enrollment, withdrawal, grading and incompletes can be found at http://www.cdm.depaul.edu/Current%20Students/Pages/PoliciesandProcedures.aspx.
Students who feel they may need an accommodation based on the impact of a disability should contact the instructor privately to discuss their specific needs. All discussions will remain confidential.
To ensure that you receive the most appropriate accommodation based on your needs, contact the instructor as early as possible in the quarter (preferably within the first week of class), and make sure that
you have contacted the Center for Students with Disabilities (CSD) at:
Lewis Center 1420, 25 East Jackson Blvd.
Phone number: (312)362-8002
Fax: (312)362-6544
TTY: (773)325.7296