CS3361 Homepage

Description:

CS3361 is an introductory course on Artificial Intelligence (AI). The course will survey basic issues and concepts such as search, representation, knowledge, experience, memory, inference, and control. It will focus on selected topics in problem solving and learning.

Objectives:

The objectives of the course are (i) to provide a broad survey of AI, (ii) to develop conceptual understanding of the basic concepts and major topics in AI, and (iii) to develop design skills in building simple AI systems.

Format:

The course will consist of the following:
1. Class lectures and discussions
2. Discussions on the newsgroup git.cc.class.3361
3. Reading assignments
4. Four projects
5. Three Examinations

Readings:

• Primary text: Artificial Intelligence: A Modern Approach, S. Russell and P. Norvig, Prentice Hall, 1995.
• Supplemental AI texts: Artificial Intelligence: E. Rich and K. Knight, McGraw Hill, Second Edition; Artificial Intelligence, P. Winston, Addison-Wesley, Third Edition; Artificial Intelligence, E. Charniak and D. McDermott, Addison-Wesley. Hal's Legacy: 2001's Computer as Dream and Reality, David G. Stork, MIT Press.
• Supplemental AI programming texts:Lisp, Winston and Horn, Addison-Wesley; AI Programming, Charniak, Riesbeck, McDermott and Meehan, Lawrence-Erlbaum; Paradigms of AI Programming, P. Norvig, Morgan-Kauffman.

Design Projects:

There will be four design projects. Each project will be about two weeks long. Students are welcome to use any CLTL 2 compliant version of Common Lisp on a machine of their choice. All programs should be tested on the acme version prior to submission. The TA will provide more specifications if required.

Examinations:

There will be 3 examinations: 2 in quarter exams and 1 final exam. The first exam is scheduled for the end of January. The second is scheduled for the end of February, and the final is schedule for mid March.

Grading:

The two mid term examinations will constitute 15% each of the final grade, and the final will count 30%. The first project will constitute 8% of the final grade, and the last three projects will be worth 10%. Class attendance and participation will account for the remaining 2%.

Grading Policy:

All assignments must be turned in on time - no extensions will be granted but incomplete assignments will be graded for partial credit. Exams may be rescheduled in the case of a verifiable emergency.

Please feel free to look at the course schedule for the class. It may be updated on occassion. I will be adding the first page of the syllabus to this page very soon.

Assignments

• Here is assignment #1 it consists of an assignment specification and a map in GIF form.
• Here is assignment #2
• Here is assignment #3
• Here is assignment #4

Course Notes

• January 8 & 10, 1997 Introduction to Artificial Intelligence
• January 13, 1997 Problem Spaces
• January 15, 1997 Search
• January 17, 1997 Knowledge Representation
• January 22, 1997 Planning
• January 24, 1997 STRIPS
• February 3, 1997 Expert Systems
• February 5, 1997 Case-Based
• February 10,12,14, 1997 Learning
• February 17,19,21, 1997 Natural Language Processing
• February 26,28, 1997 Vision
• March 3, 1997 Robotics and Action
• March 5, 1997 Sub-symbolic Approaches
• March 12, 1997 Can Machines Think?

Exam 1

• Sample Answers (note: some of the formating is not right here, so let me know if you can't figure out the answers)
• Average = 76.9

Exam 2

• Sample Answers (note: some of the formating is not right here, so let me know if you can't figure out the answers)
• Average = 70.2

Contact Information:

Last Modified: 15 JAN 97 by Todd Griffith