810:161, Spring 2009

Artificial Intelligence

General Information

Instructor: Ben Schafer

Email: schafer@cs.uni.edu

Office: 316 ITTC, phone 273-2187

Office Hours: 

• MF, 11:00-11:50 AM, 1:00-1:50 PM
• Thursday, 10:00-noon
• Anytime my office door is open or by appointment

Class Info:  3 credits (section 1, AI only) or 4 credits (section 2, AI and "Introduction to Robotics")

Time and Place:  

• MWF 2:00-2:50, ITTC 322 (both sections)
• Wednesdays from 1:00-1:50, WRT 117, (section 2 only)
• Students taking section 2 should expect to spend additional time with their robotics team

Required Text:   Artificial Intelligence: A Modern Approach e2,  Russell & Norvig (ISBN 0-13-790395-2)

Supplemental Texts:  Our library contains several very good textbooks on Artificial Intelligence.  You may find these helpful for providing different examples (or even a different perspective), or preparing for your research paper.  While you should not feel you must limit yourselves to these, the following are all reasonable texts.

• Artificial Intelligence, Michael Negnevitsky

• The Elements of Artificial Intelligence,  Steven Tanimoto

• Artificial Intelligence,  Patrick Henry Winston

• Artificial Intelligence,  Luger & Stubblefield

• Exploring Artificial Intelligence in the New Millenium,  Lakemeyer & Nebel

• Blondie24:Playing at the Edge of AI,  David B. Fogel

Class Directory:  http://www.cs.uni.edu/~schafer/courses/161/  (Check here for lecture notes, announcements and supplemental class materials)

Class Mailing List: To send to this list you must use your uni.edu account.

• 810-161-01-SPRING@uni.edu  or 810-161-02-SPRING@uni.edu

Course Description

"Artificial Intelligence (AI) is devoted to the computational study of intelligent behavior"

What does that mean?  Well, that's a tough question to answer.  In fact, we could argue that a key purpose of this course is to help us develop the "language skills" to explain this sentence.  I use the term language skills to mean not only computer language skills to write some code which demonstrates AI, but also the human language skills to explain why that code might be classified as AI.

Ok, so that was kind of a weasel answer.  So what is a more accurate course description?

This course introduces the fundamental issues in the field of AI. Intelligent behavior includes a wide range of phenomena, such as perception, problem solving, use of knowledge, planning, learning, and communication. Scientists in the field have developed a wide range of techniques for modeling these phenomena, including state-space search, several knowledge representation schemes, and task-specific methods. The bulk of this course reflects this diversity. We will examine the fundamental questions and issues of AI and will explore the essential techniques. By the end of the course you should feel comfortable:

• discussing a broad range of issues in the field of AI,
• using and discussing the basic techniques of the field, and
• evaluating potential applications of AI technology.

Additionally, I hope that this course will also help you to appreciate the excitement of AI, its possibilities and limitations, its big questions and its big successes. I hope that by the end of the semester you understand why AI still captivates so many people with its promise -- and what this promise means for you as a practicing computer scientist.

This course is appropriate for students with programming experience.  810:063 or a similar course is a prerequisite.  Knowledge of Java is extremely helpful.

Course Structure and Policies

Class sessions – Our class meetings will consist of a mixture of lecture, discussion, and in-class exercises. While sometimes this material will reinforce your readings, it will often extend this material beyond what you find in your textbook.  Therefore, attendance is essential. You are expected to read assigned topics prior to the class session (an “active” schedule will be frequently updated on the website) and to participate actively in class.

Homework assignments – Over the course of the semester, you will complete six to ten homework assignments. These assignments may involve writing about issues in the field, applying techniques learned in class, writing code, and doing experiments with publicly available AI languages/toolkits.   I encourage you to discuss homework assignments with your classmates in order to help you understand the problems and to encounter different points of view. However, any work you submit must be your own. Discuss ideas, but write your own answers. You should acknowledge any collaborations and/or external sources in the work you submit. Undocumented or unacceptable collaboration will be considered forms of academic dishonesty (see below).

Research paper – You will work with one or more of your classmates to co-author one research paper during the semester. This paper will give you an opportunity to explore a topic in some detail and to go through the process of preparing a research document. Writing is an indispensable skill for any computing professional. I hope that you will use this paper as an opportunity to improve your professional writing skills.

Written Exams – There will be three written exams during the semester.  Two will be mid-term exams, while the other will be the scheduled final exam for the course.  The exams are closed book exams unless clearly announced otherwise. The actual date of each exam will be announced approximately one week prior to the exam.  There are no scheduled make-up exam dates.  If you are aware of conflicts prior to the exam, please make me aware of these as early as possible.

Introduction to Robotics Lab (section 2) – Participants in section 2 will complete an additional set of activities in exchange for an additional hour of course credit.  An addendum to this syllabus is provided for those students in section 2.

I try to accommodate student needs whenever possible, but I can only do so if I know about them. If you ever have to make alternate arrangements for a class session, an assignment, or an exam, contact me in advance. The safest way to make such arrangements is by notifying me via e-mail or phone of your circumstances and of how you can be reached. 

All assignments are due at their assigned date and time. In order to receive partial credit, always submit your best effort at that time. Late work will not be accepted for a grade.

Grading

The following approximate weighting will be used in assigning final grades.  This may shift slightly depending on the actual number of homework assignments made.

Grading for this course is on an absolute scale.  Once points are combined, final grades will be assigned based on cut off points no “higher” than:

• 90.0% < x <= 100.0% A
• 80.0% < x <= 90.0% B
• 70.0% < x <= 80.0% C
• 60.0% < x <= 70.0% D
• 0.0% < x <= 60.0% F

However, there are two exceptions to this:

• I reserve the right to lower your final grade in the course by one grade "level" (for example, from a B+ to a B) for each assignment for which you fail to submit at least some evidence of effort towards completion.  If an assignment has you completely stumped but you gave it some effort, then show me that you made that effort.  I can tolerate confusion, I can't tolerate people too lazy to even attempt the assignment.
• I reserve the right to lower your grade if you do not adequately participate with your co-authors in the process of writing the  research paper.
• For those students in section 2, robolab, I reserve the right to raise or lower your grade as much as one full letter grade for work that goes well beyond the lab expectations or fails to meet the lab expectations.  A bit more detail regarding this will be discussed in robolab.

Incompletes

Incompletes are awarded only in very rare instances when an unforeseeable event causes a student who has completed all the other coursework to date to be unable to complete a small portion of the work in the last week or two of the semester (typically the final project or exam).  Incompletes will not be awarded for foreseeable events including a heavy course load or a poorer-than-expected performance. Verifiable documentation must be provided for the incomplete to be granted, and arrangements for the incomplete should be made as soon as such an unforeseeable event is apparent.

Scholastic Conduct

You are responsible for being familiar with the University’s Academic Ethics Policies (http://www.uni.edu/pres/policies/301.shtml).

Copying from other students is expressly forbidden. Doing so on exams or assignments will be penalized every time it is discovered. The penalty can vary from zero credit for the copied items (first offense) up to a failing grade for the course.  If an assignment makes you realize you don't understand the material, ask a fellow student a question designed to improve your understanding, not one designed to get the assignment done. Your final submission for assignments should be individual, original work unless otherwise specified.

Any substantive contribution to your solution by another person or taken from a publication should be properly acknowledged in writing.  Failure to do so is plagiarism and will necessitate disciplinary action.  In addition to the activities we can all agree are cheating (plagiarism, bringing notes to a closed book exam, etc), assisting or collaborating on cheating is cheating.  Cheating can result in failing the course and/or more severe disciplinary actions.

Remember: Discussing assignments is good. Copying code or answers is not. 

Class Distractions

We live in a technological society, and many of you now carry a variety of electronic distractions with you.  These include cell phones, laptops, PDAs, MP3 players, etc.  While you are welcome to own and use these, and other, electronic devices, their use in the classroom is forbidden without my explicit permission (In fact, this is now a University-wide policy).

A few exceptions do exist, and I reserve the right to approve these situations on a case-by-case basis with prior notification.  For example, due to a family emergency it may be necessary to have your cell phone turned on. Unless we have discussed it in advance, all electronic devices should be turned off and left out of sight during class time.  The inappropriate use of any of these devices will cause you to receive a participation grade of negative one point regardless of your participation otherwise.  Multiple infractions may cause more extreme consequences, including removal from the course.

Accessibility

The Americans with Disabilities Act of 1990 (ADA) provides protection from discrimination for qualified individuals with disabilities. Students with a disability, who require assistance, will need to contact the Office of Disability Services (ODS) for coordination of academic accommodations. The ODS is located at 213 Student Services Center. Their phone number is 319/273-2676.  Additionally, please contact me immediately if you have a learning or physical disability requiring accommodation

Tentative Schedule

This course will be divided into six "units" largely mirroring the units defined on page xiii of Russell and Norvig.  Check the class website frequently for more fine-grained details (chapters/sections we will cover/skip), changes, and announcements.