An Introduction to Artificial Intelligence

Principles of Artificially Intelligent Machines

CS 427 / 527

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Instructor: Prof. Lydia Tapia
Office: FEC 349E
Office Hours: Tues. 3:15pm-4:15pm, Wed. 2:00pm-3:00pm, Thurs. 3:15pm-4:15pm; other times by appointment
Office Phone: 505-277-0858

TA: Noor Abu-El-Rub
Office: FEC 126
Office Hours: Mon. 9:00am-10:30am and Fri. 9:00am-10:30am; other times by appointment

Course URL:

Lecture: Tuesday, Thursday 2:00-3:15 PM, Woodward Lecture Hall 149

Textbook: Artificial Intelligence: Structures and Strategies for Complex Problem Solving (6th Edition), George F. Luger, Addison-Wesley Pearson, 2009.

(optional) AI Algorithms, Data Structures and Idioms in Prolog, Lisp, and Java, George F. Luger and William A. Stubblefield, Pearson Education, 2009.

Course Content and Tentative Schedule: The course will cover the following topics.

Week of Topic Reading
8/19 AI, its roots and scope Ch 1
8/26 Structures and strategies for state space search Ch 3
9/2 Heuristic search Ch 4
9/9 Predicate calculus Ch 2
9/16 Advanced topic: Robotic Intelligence online
9/23 Probabilistic Methods in AI Ch 5
Midterm 1
9/30 Architectures for AI problem solving Ch 6
10/7 Prolog N/A
10/14 Intro. AI representational Schemes Ch 7
10/21 Representation & knowledge-based systems Ch 8
10/28 Representation & knowledge-based systems Ch 8
11/4 Reasoning in uncertain situations Ch 9
11/11 Building a rule based expert system in Prolog N/A
11/18 Building a rule based expert system in Prolog N/A
11/25 Advanced topic: TBD N/A
12/2 Course Summary and review Ch 16
Midterm 2

Assignments and Grading: All assignments will be announced in class and posted on the course web page. If you miss class for any reason, it is your responsibility to find out what assignments you missed.

Your grade will be based on four components:
No late assignments will be accepted. There will be no make-up exams except for university-excused absences. Please discuss unusual circumstances in advance with the instructor.

Requests for instructor-initated drops MUST be in writing via email to the course instructor before the final exam. They will be evaluated on a case-by-case basis.

Course grades will be assigned according to this scale:
A for 90% or above of the total points,
B for 80 to 89%,
C for 70 to 79%,
D for 60 to 69%,
and F for less than 60%.

Academic Integrity: For everyone's benefit, students should uphold the guidelines in the University of New Mexico Student Code of Conduct.

For the assignments in this class, discussion of concepts with others is encouraged, but all assignments must be done on your own, unless otherwise instructed. If you use any source other than the text, reference it/him/her, whether it be a person, a book, a solution set, a web page or whatever. You MUST write up the solutions in your own words. Copying is strictly forbidden.

Americans with Disabilities Act (ADA) Policy Statement: The Americans with Disabilities Act (ADA) is a federal antidiscrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact the Department of Student Affairs, Accessibility Resource Center in Mesa Vista Hall, Rm. 2021.

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There will be a series of programming tasks.

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Students are expected to write a paper on a topic on AI during the course of this class. Possible paper topics include: 527- Appropriate paper sources include:

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Useful Links


8/26/14 Game Descriptions

9/2/14 A* Activity

Announcements Syllabus Homework Projects Paper Useful Links Slides