This course provides a basic introduction to the field of Artificial Intelligence. Topics covered will include: search, knowledge representation, reasoning and learning.
I take the academic honesty of my students very seriously and I will not tolerate any form of dishonest behaviour. It is your responsibility to understand and be familiar with UCI's academic honesty policies: Read and understand the UCI Senate Academic Honesty Policy and the ICS policy on cheating.
Note that any academic dishonesty can result in a grade of F and a letter in your permanent student file.
I will evaluate students on the basis of homework assignments, a mid-term exam, a final exam, and a programming assignment. Your final grade will be the better of:
Homework: Homework will be assigned in each class and will be due in one week at the start of the discussion section. For example, homework assigned for lecture 1 will be due in the discussion on August 15; homework for lecture 2 will be due on August 17.
Regrading Policy: Turn in your paper within one week of receiving it with a written note explaining why you are requesting a regrade. Note that regrading may result in your mark increasing or decreasing.
Bonus Points: I will occasionally offer bonus questions to students. Students are eligible for up to a total of 5 bonus points. These points will be added to the final mark. For example, if your final grade was 83% and you got 2 bonus points then your mark would be 85%. Bonus questions must be done individually. The current opportunities for bonus points are:
Current Grades (no longer available)
News Group
Read the ics.171 newsgroup for course announcements, answers to questions, etc. If you have a question, please post it here.
The programming project must be done individually. You may use any language available on the ICS Unix accounts including: Java, C, C++, and Lisp. The project will be due on September 7.
Some additional notes.
How to determine if an arbitrary puzzle is solvable.
| Note: Because of the compressed schedule, please try to read the assigned material before each lecture. |
The files available for download are in two formats: postscript (ps) and pdf format. Postscript files may be viewed with ghostscript and the pdf files can be viewed with Adobe Acrobat. The pdf and ps files are exactly the same.
| Lecture | Date | Topic | Reading | Handouts |
| 1 | Tuesday Aug. 8 | Introduction to Artificial Intelligence: What is AI? Intelligent Agents |
Ch. 1,2 | notes: ps, pdf homework: ps, pdf solution: ps, pdf |
| 2 | Thursday Aug. 10 | Search: Problem Solving as Search, Uninformed Methods |
Ch. 3 | notes: ps, pdf homework: ps, pdf solution: ps, pdf |
| 3 | Tuesday Aug. 15 | Search: Informed Methods Iterative Improvement Methods |
Ch. 4 except SMA* | notes: ps, pdf homework: ps, pdf solution: ps, pdf |
| 4 | Thursday Aug. 17 | Search: Game Playing | Ch. 5 | notes: ps, pdf homework: ps, pdf solution: ps, pdf |
| 5 | Tuesday Aug. 22 | midterm exam | midterm prep: ps, pdf midterm solutions: ps, pdf |
|
| 6 | Thursday Aug. 24 | Reasoning: Propositional Logic | Ch. 6 | notes: ps, pdf homework: ps, pdf solution: ps, pdf |
| 7 | Tuesday Aug. 29 | Reasoning: First Order Logic | Ch. 7.1, 9 (except 9.7) | notes: ps, pdf homework: ps, pdf solution: ps, pdf |
| 8 | Thursday Aug. 31 | Reasoning: Handling Uncertainty with Probability | Ch. 14 | notes: ps, pdf homework: ps, pdf solution: ps, pdf |
| 9 | Tuesday Sept. 5 | Learning: improving a computer's performance with experience | to be announced | |
| 10 | Thursday Sept. 7 | Review | ||
| 11 | Tuesday Sept. 12 | Final Examination |
Much of the course material used has been developed by others and I would like to thank Charles Dyer, Dmitry Pavlov, Mike Pazzani, Padhraic Smyth and the textbook authors for making available their notes.