ICS 171: An Introduction to Artificial Intelligence

Summer Session II, 1999

• Classroom: ICF 101
• Time: MW 1:00 to 2:50, F 10:00 to 11:50
• Instructor: Dmitry Pavlov
• Electronic Mail: pavlovd@ics.uci.edu, 171-questions@ics.uci.edu
• Office: CSE 334
• Office Hours : MW 12:00 to 12:50
• Textbook:
• S. Russell and P. Norvig Artificial Intelligence: A Modern Approach Prentice Hall, 1995
• Teaching Assistants
• Jieping Lu, jlu@ics.uci.edu, Office: CSE 332
• Discussion Section: MW 03:00-03:50, ICF 101

Course Goals:

Learn the basic AI techniques, the problems for which they are applicable and their limitations. Topics covered include search algorithms (including heuristic search), knowledge representation, learning algorithms, and elements of probabilistic modeling.

Academic Honesty:

Academic honesty is taken very seriously. It is the responsibility of each student to be familiar with UCI's current academic honesty policies. Please take the time to read the current UCI Senate Academic Honesty Policies. Also you may want to look at the ICS Department's policies on cheating .

Projects:

There will be one computer project and you will have at least 3 weeks to complete it. The project assignment will be handed out after the first week of classes.

Policy on Late Projects: You will automatically lose 20% for each period of 24 hours for which a project deliverables is late: after 5 days you will receive no credit.

Grading:

There will be weekly homework assignments that are intended to help you understand material and keep up with what is covered on the lectures. You will be allowed to work in teams of at most 3 people on the assignment. Each person participating in the team must make a significant contribution and turn in her/his own write-up of the problems. The questions similar to the ones in homework will be given on quizzes or exam. Solutions to assignments will be discussed on the discussion sections. Homeworks will account for 20% of your grade.

There will be a 15-20 minute quiz in the beginning of each Wednesday's lecture. The quizzes will account for 30% of your overall grade.

There will be a final exam, closed-book, during finals week. This will account for 30% of your grade.

There will be one computer project, possibly with intermediate deliverables. The project will account for 20% of your grade.

Policy on Regrading: Turn in the paper, with a reason for the request for regrading written down on a separate sheet of paper and a signed statement that the paper wasn't altered in any way, to your TA or instructor within 1 week of receiving it. Note that the entire paper will be regraded which could result in your grade either increasing or decreasing.

Bulletin Board:

Please post questions, suggestions, etc to the ics.171 news group . Also please check this news group for announcements, answers to homework etc. If you don't understand something, others probably don't either and will have the same question.

Syllabus

Grades - are sorted with respect to the last 4 digits of the student ID number. Please, let us know immediately if you find any discrepancies between the scores we have on file and your actual scores.

Handouts

• Lecture Slides
• Homework assignments

Resources on the Internet

• A very comprehensive list of Web resources about AI from the Russell and Norvig textbook.
• Much of the text for the HAL book . Well worth looking at to get a broad and entertaining view of the history of AI. See also David Stork's page on Hal-related events and information.
• An interesting tour of the history of AI with some general background information about AI.
• How much commercial and research activity is there in the general area of automated algorithms for recognizing faces from images? A lot more than you might think! Lots of face-recognition related information here including demos and software.

Thanks to Professor Padhraic Smyth for the help in the preparation of this page.