Instructor: Eric Eaton Offices: ITE 220, ITE 339. I will be in ITE 220 during my scheduled office
hours. If you need to find me other times, you can find me in my research lab,
ITE 339. Office Hours: Monday 2:30pm-3:30pm, Wednesday 11:30am-12:30pm in ITE 220,
and
by
appointment. E-mail:
Here's the UMBC catalog description: This course is designed as a
broad introduction to artificial
intelligence. Topics include an
overview of Artificial Intelligence
(AI), its subfields and applications;
knowledge representation,
techniques and issues; natural
language understanding; search;
logic and deduction; basic robot
plan generation; expert systems;
handling uncertainty and learning.
And here's my description: Artificial Intelligence is, in my opinion,
the coolest and most exciting subfield of computer science. In this course,
we will explore several major areas of AI, including search, knowledge representation
and reasoning, planning, machine learning, and game playing. We will also relate
these topics to their applications in robotics, computer gaming, medical diagnosis,
computer vision, natural language understanding, and many other areas. Google, NSA, and NASA all use AI technology.
AI's successes, such as the IBM
Deep Blue chess program beating Kasparov (1996),
the DARPA grand challenge autonomous vehicle competition (2005), and
solving checkers (July 2007) are
well-publicized and very popular.
This is the reference manual for Common Lisp. It isn't required for the course, since most of you will find the online version sufficient
as a resource, but there is a print version if you like real books.
Prerequisites
Prerequisite: CMSC 341.
A background in probability, statistics, and linear algebra would be helpful,
but it isn't required. Those of you without this background might have to work
a bit harder when we get to those sections of the course.
Course Outline
The course will be broken up into the following rough sections:
A course mailing list has been established for distributing news
and discussing course-related topics. Students should feel free to
post general problems, news articles, questions, and answers to the list for
the benefit of the entire class. At no time should students post homework solutions
or solutions to exam questions to the course mailing list; posting such solutions
will be
interpreted as academic dishonesty.
Posting such solutions will be the sole responsibility of the course staff.
Individual concerns should be e-mailed directly to course staff.
Although not required, it is highly recommended that you subscribe to
the course mailing list. If you do not subscribe to the list, there
is no guarantee that you will receive up-to-date information about the course.
To post to the course mailing list, send email to cmsc471-fall07@lists.umbc.edu
Communication
As you will discover, I am a proponent of two-way communication. I expect
everyone to participate actively in classroom discussions by asking questions,
contributing answers, and proposing ideas. I welcome feedback during the semester
about the course.
In return, I will make myself available to answer student questions, listen
to concerns, and talk about any course-related topic (or otherwise!). Come
to office hours! This
helps me get to know you. Also, you are welcome to stop by my office and chat.
There are many more exciting topics to talk about that we won't have
time to
cover in-class. If you don't find me in ITE 220, check my research lab, ITE
339.
Whenever you e-mail the instructor or TA, please use a meaningful subject
line and include the phrase "CMSC 471" at the beginning of that line.
Your e-mail will catch my attention and I will respond quicker if
you do this. I make
an effort to respond to e-mails within 24 weekday hours.
Your final grade will be determined according to the following
criteria:
90% <= A <= 100%
80% <= B < 90%
70% <= C < 80%
60% <= D < 70%
0% <= F < 60%
These criteria may be adjusted slightly in your favor. Incomplete grades will be given only for verifiable medical
illness or other such dire circumstances.
Homework Assignments
There will be six (6) homeworks assigned over the course of the
semester. Each homework will be assigned at least one week in advance
of its due date. The homework assignments will be a mix of written, programming,
and analytical components.
Homework assignment solutions must be turned in at the start
of class in typeset hardcopy on the designated due date. Homework assignments
can be submitted up to 24 hours late for a 25% penalty, and 48 hours late for
a 50% penalty. No submissions later than 48 hours will be accepted. Extensions will be given only in the
case of verifiable medical excuses or other such dire circumstances, if requested in advance.
0-24 hours late: 25% penalty
24-48 hours late: 50% penalty
more than 48 hours late: no credit
Penalties are applied by taking off that percentage of the points you would have earned: your_score_without_penalty * (1 - penalty) = your_score_with_penalty.
For example, if you would have earned a 90% on the assignment, but you turned it in 5 hours late, your score would be 90% * (1 - 0.25) = 67.5%.
All homework solutions must be typeset. Any solutions requiring math or proofs must use proper
mathematical notation. Similarly, graphs should be well-constructed with all axes properly labeled.
I highly recommend the use of the LaTeX text formatting system, but you can use any program capable
of producing proper mathematical notation. The main course page contains links to good LaTeX
websites and links to example files.
All solutions are required to be your own, individual work. You
may, and are encouraged, to discuss methods, concepts, and assignments
with anyone; however, the solutions turned in must be your own work.
A good rule of thumb is to be alone when you sit down to actually
generate solutions to the assigned problems, and to not show your solutions
to anyone else.
At the top of your submission, you must include a clear statement specifying
the source of any assistance you received on this assignment. This includes any
websites you consulted, other students with whom you discussed any of the
problems, etc. If you did not receive any assistance, you must say so.
Submissions without this statement will be penalized.
Lectures and Readings
You are expected to attend all classes. You are responsible for all
material covered in the lecture (including material that is not included in the
textbook), and all material in the readings (including material that is not
covered during lecture). You are responsible for familiarizing
yourself with the assigned readings before each class. If you miss a class,
you are responsible for getting the notes and any verbal
information given during class from a fellow classmate. If handouts were
given out or assignments returned, you may come to my office to get them.
Exams
There will be one midterm and a final exam. The exams will be closed-book and closed-notes. Test dates for all exams
have already been announced, so plan your schedule accordingly. In the case of verifiable
medical excuses or other such dire circumstances, arrangements must be made with
the instructor for a makeup exam. You are responsible for initiating these
arrangements, not your instructor, before the test date.
Exams will cover material from lectures, homeworks, and assigned readings (including topics
not discussed in-class). So, keep up with those readings!
UMBC Statement of Values for Academic Integrity
By enrolling in this course, each student assumes the responsibilities
of an active participant in UMBC's scholarly community in which
everyone's academic work and behavior are held to the highest
standards of honesty. Cheating, fabrication, plagiarism, and
helping others to commit these acts are all forms of academic
dishonesty, and they are wrong. Academic misconduct could result
in disciplinary action that may include, but is not limited to,
suspension or dismissal. To read the full Student Academic Conduct
Policy, consult the UMBC Student Handbook, the Faculty Handbook, or the UMBC Policies
section of the UMBC Directory. [Statement adopted by UMBC's Undergraduate Council and Provost's Office.]
Any violation of the UMBC academic honesty policy will carry the following minimum penalty: the student will receive no
positive credit on the assignment, and the assignment will count against the student's final grade by the full amount it was worth.
For example, cheating on an assignment worth 10% of the final grade would result in the student getting no credit for completing the assignment
and the assignment counting 10% against their final grade, giving them a maximum possible grade of 80% in the class.
Cheating in any form will not be tolerated. Cheating includes but is not limited to: copying a solution from another student or the internet (or providing your solution to another student),
plagarism, working in collaboration with another student on individual work, and using resources prohibited by the assignment.
Instances of cheating will be
reported to the UMBC Academic Conduct Committee. These reports are filed by the
Committee and can be used for disciplinary action such as a permanent record on
your transcript. You are expected to be honest yourself and to report any cases
of dishonesty you see among other students in this class. Reports of dishonest
behavior will be kept anonymous.
Legitimate Collaborations
All of this being said about academic honesty, I do want to encourage you to discuss the material
and work together to understand it. Here are my thoughts on collaborating with other students:
The readings and lecture topics are group work. I encourage you to discuss the readings and associated topics with each other.
Work together to understand the material. I highly recommend forming a reading group of 3-5 people -- we will explore many challenging
ideas in AI and it helps to have multiple people working together to understand them.
It is fine to discuss the topics covered in the homeworks, to discuss approaches to problems, and to sketch out general solutions. However,
you MUST write up the homework answers, solutions, and programs individually. You are not permitted to share mathematical results, program code,
knowledge representations, experimental results, etc. If you made any notes or worked out something on a white board
with another person while you were discussing the homework, you shouldn't use those notes while writing up your answer, however tempted you may be to do so.
You are fully permitted to (and should!) discuss the project with members of your team. I also encourage you to work outside of your team to
understand the other topics in the course. However, remember that there will be a competition, so you don't want to give other teams any of your good ideas!
Exams, of course, must be your own individual work.
If you have any questions as to what types of collaborations are allowed and which are dishonest, please ask me before you make a mistake.
Acknowledgements
Thanks to Marie desJardins, Tim Finin, and Terran Lane for making their course materials available. Many of the course materials
for this class have been adapted from those sources.
