CPSC5185G-V01 Artificial Intelligence

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29 Οκτ 2013 (πριν από 3 χρόνια και 7 μήνες)

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CPSC5185
G
-
V01

Artificial Intelligence

Spring Semester 200
9


Instructor information

Name: Dr. Shamim Khan

Office: Center for Commerce and Technology (CCT) Room 444

Office

h
ours:

Mon

10:
3
0 AM
-

12:
3
0 PM,
1:30 PM


4:30 PM

Wed 1
0
:00 AM
-

12:00 PM
,
1:30 PM


4:30 PM

Contacting me:

If you need to discuss something
,

which does not

require a face
-
to
-
face
meeting,

please e
-
mail me. If you need to see me face
-
to
-
face but cannot meet during
the scheduled office hours, please e
-
mail me so we can make arrangements to

meet
in

my office at a more convenient time.


Email:
khan_shamim@colstate.edu

(
preferred method of contact
)

Web:
http://csc.colstate.edu/khan

Office Phone: 706/565
-
35
19
;
Dep
t.

Phone: 706/568
-
2410
;
Dep
t.

Fax: 706/565
-
3529


Online access to c
ourse
:
http://webct.colstate.edu


Description

This course covers the fundamentals of artificial intelligence and its application for problem

solving. The emphasis is on popular AI and soft computing methodologies used for developing
software systems known as intelligent systems. The course involves
practical

work.


Learning objectives

Goals

How you will be assessed



L
earn the
rationale

behind

the artificial
intelligence and soft computing paradigms
with their advantages over traditional
computing.



Weekly on
-
line discussions



L
earn the basic theoretical foundations of
the following common intelligent systems
methodologies:



Search techniques



Rule
-
based expert systems



Fuzzy systems



Artificial neural networks



Genetic algorithms



Data mining



Case
-
based reasoning



Natural language processing



Intelligent agents



Weekly on
-
line discussions



Theoretical and practical a
ssignments

Artificial Intelligence

2

of
9




L
earn t
o decide which type of methodology
is suitable for a given type of application
problem



Project proposal identifying the problem
and justifying the selected methodology



L
earn to carry out the steps for developing
an intelligent system based on a chosen
met
hodology



Project report




Required
reading material


1


Textbook:
Artificial Intelligence: A Guide
to Intelligent Systems
, 2
nd

edition

Author: Michael Negnevitsky

Publisher: Addison Wesley

ISBN: 0
-
321
-
20466
-
2


2

“Chapter 4 Search Methodologies” from
A
rtificial Intelligence
Illuminated
,
Author: B. Coppin, Publisher: Jones and Bartlett,
2004, pp. 71
-
115. (Available from CSU Bookstore)

3

Topic

notes

and lecture slides (Available online)


Software required

1. Microsoft Windows XP or Vista, and the abilit
y to administer your own machine.

2. Internet Explorer 5.0 or higher or equivalent browser

3. Software as needed for
assignment and
project work.
You are strongly encouraged to buy

MathWorks MATLAB
Version 7.4 with toolboxes that allow you to develop appl
ications using
artificial neural network, fuzzy logic and genetic algorithm
s
.
This software is available on
-
campus in Computer Science Lab CCT450. A student version of MATLAB and the toolboxes
that you can install on your own machine
is available for onlin
e purchase
1

as detailed below
(you may be able to find sources in addition to these)
.


MATLAB & Simulink Student Version, Release 2007a

Version 7.4:


Vendor: Amazon UK

http://www.amazon.co.uk/MATLAB
-
Simulink
-
Student
-
Version
-
Release/dp/0979223903

Price:
$73 (approx.)


Vendor: JourneyEd.com

http://www.journeyed.com/itemDetail.asp?ItmNo=42391696

Pric
e:
$99


Student versions of
Neural networks (NN), Fuzzy logic (FL) and Genetic algorithms (GA)
toolboxes:

$59 each
.





1

Information retrieved on January 1, 2009

Artificial Intelligence

3

of
9


You have the option of not buying the GA toolbox to save money, if you are prepared to write
your own code to implement GA

(required for

one of the assignments)
.



You also have the option of not using MATLAB, and instead, using less sophisticated public
domain NN, FL and GA software available for free from the Internet. In that case, y
ou’ll be
responsible for sourcing the software
. Rememb
er that these may not be as
powerful or
stable
,

and I may not be able to give you much support.


Supplementary materials

O
nline resources (articles, software)


Online interface

Cougar
VIEW

(
WebCT Vista
)

will be
a major

method of interaction in this course.
You can
access
CougarView

at:
http://webct.colstate.edu/

.

Click on the "Log
-
in" link to activate the
CougarVIEW

logon dialog box, which will ask for your
CougarVIEW
username and password. Students who us
ed
CougarVIEW
in the previous
semester will use the same passwords for the current semester. New student passwords on
CougarVIEW

have been set to the students birth date in the format of DDMMYY. (Example
-

Birthday of Oct. 25, 19
80

is 2510
80
).


If you try

the above and
CougarVIEW

will not let you in, please click on the new
Online Support
Center

for
CougarVIEW

available to you 24 hours a day, 7 days a week.

Once you've entere
d
CougarView
, you will see a list of courses you have access to. Clicking on
the name of a course will take you to the course's home page. If you don't see the
"
Introduction to Artificial Intelligence
" course in the list, please e
-
mail me.
Note: One
common

reason for not being able to see the course in CougarView after you log in is late
enrolment in the course. From past experience, it usually takes a couple of days after enrolment
for the updated student database to be reflected in Couga
r
View.

Once you ha
ve clicked on the course's name and accessed course, you will find a home page
with links to other sections and tools, and a menu on the left
-
hand side. Please explore the
online interface and become familiar with components such as: discussions, calendar,

e
-
mail

and announcements. More

items such as lecture notes and assignments
will be progressively
added to course home page.

Note: CougarView is unavailable due to maintenance each week from 10 PM Friday to 7 AM
Saturday.

How This Course Will Work

This co
urse will consist of

lectures,

readings, discussion questions, assignments,
and
a
n end
-
of
semester

project. On a weekly basis, you will need to:

1.

download the week’s lecture notes and any other relevant material made available
online through CougarView
;

2.

re
ad lecture notes

to
review the
main points of the
week's lesson;

3.

get a more in depth understanding by
complet
ing

the readings from
the
text

and/or other
material referred to in the lecture notes
;

4.

check for any new discussion question in CougarView;

5.

partic
ipate in the current discussion question and
submit responses to
others in the class
based on
your

readings
, online research and any personal experience
;

Artificial Intelligence

4

of
9

6.

work on the
current
assignment to meet the given deadline;

7.

decide on and complete a final project

in
consultation with your Instructor.


Assessment components

Weekly online discussions

30% (including 2
0
% for response to discussion question,
10% for comments on other students'
post
s)

4
Assignments


40%

Project

30% (including 3% for the proposal)


Gradi
ng scale

A: 90
-
100 % B: 80
-
89 %


C: 70
-
79 %



D: 60
-
69 %


F: below 60 %


Discussions

There will be
1
3

threaded
online
discussions via
CougarView
.
To maximize your learning, you
are expected to participate actively in the weekly discussions
. This means posting responses to
discussion questions

and

commenting on other students' responses

or

comments
.


To earn maximum credit for responses to discussion questions
, you must post a response to
each

weekly
discussion question of at least 150 words

by Wednesday of the week
. In addition
to the minimum word count, your responses will also be graded based on their quality
--
that is,
relevance to the discussion question
,
clarity, and
evidence of analysis (going on step further
than just presenting facts,

article ex
cerpt
s)
.



To earn maximum credit for comments to other students
, you must post at least one substantive
comment to another student's response or comment

by Saturday of the week
.
R
eplies to
comments made to your responses to discussion question
s do not count as comments.



There is no minimum word count for comments, but the comments must add value to the
discussion to receive the maximum points. That is, comments must
be

more than
just
"Good
response" or "I agree." Your comments should add to t
he substance of the posting, request
clarification, provide a different perspective, or challenge the assertions made by providing real
or hypothetical scenarios that the original posting does not adequately address.


Remember, the purpose of course discu
ssions is to stimulate academic debate. Critical thinking
is highly desirable! If you do not agree with someone's post, say so. Just do so with respect

and
courtesy
.


Please address the person, whose post/comment you are responding to, by his/her first na
me to
make it clear who you are responding to.


In addition to the above, a
positive attitude

is essential to a healthy learning environment. Not
only should your posts be respectful and insightful, but they should also be positive in order to
benefit the
entire class.


Any contribution past its deadline will be ignored.



I will read every posted message

and post my comment by Sunday evening to summarize the
week’s discussion.



Artificial Intelligence

5

of
9

Project

The project will be due
on
Fri
day

of the last teaching week (see sc
hedule below)
.



It will involve the use of an intelligent system methodology to develop a system for classification
or prediction in an application chosen by you. Some of

the

project topics from last year are listed
below

as examples
:



A fuzzy decision sup
port system for handling bank checks



Predicting the strongest pre
-
flop set of four hole cards in a

poker
game

b
y using genetic
algorithm



A fuzzy inferencing recommender system for buying
classic and collectible automobiles



Fuzzy Expert System for guiding
educational intervention based on curriculum based
assessment



Fuzzy Real Estate Investment Property Evaluation System



Fuzzy Inference Systems for Fraud Applications



Solving The Traveling Salesman Problem using a Genetic Algorithm


You are required to send
me a proposal for a project
by midterm

(see weekly schedule below)
.
T
he final proposal will need to be approved by me after consultation with you before you start
working on it.


The project will involve practical work and a report.


You'll be responsible

for
ensuring you have access to
the software
to be used unless you decide to write it from scratch.

You are expected to work for about 8 weeks on this assessment component.


Artificial Intelligence

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of
9

Tentative weekly schedule
(subject to change



check CougarView calendar for up
-
to
-
date
assessment due dates
)

WEEK #

TOPIC

ACTIVITIES
/DUE ASSESSMENTS

1

(1/12
-
1/
18)

Topic 1: Introduction to AI and intelligent
systems

Read syllabus, Familiarization with
CougarView tools (calendar, e
-
mail,
discussions)

Read topic note, text book chapt
er

1, any
relevant articles

Topic 2: Rule
-
based expert systems

Read topic notes, text book chapters 2
-
3, any
relevant articles


2

(1/
20
-
1/
25
)

Topic 2: Rule
-
based expert systems
(cont’d)


Continue reading on rule
-
based expert
systems

Discussion
1

3

(1
/2
6
-
2
/
1
)


Topic 3: Fuzzy systems

Read topic notes, text book chapter 4, any
relevant articles

Assignment 1 & Discussion
2

4

(
2
/2
-
2/
8
)

Topic 3: Fuzzy systems (cont’d)


Continue reading on fuzzy logic
-
based
systems

Discussion
3


5

(2/
9
-
2/
15
)

Topic 4: Ar
tificial neural networks


Read topic notes, text book chapter 6, any
relevant articles

Discussion

4

6

(2/1
6
-
2/
22
)

Topic 4: Artificial neural networks
(cont’d)


Continue reading on artificial neural network
s

Discussion
5

7

(2/
23
-
2/2
8
)

Topic 5:
Artificial

neural networks
(cont’d)


Continue reading on artificial neural networks

Discussion
6

8

(3/2
-
3/8)

Topic 6: Evolutionary Computation

Read topic notes, text book chapter 7, any
relevant articles


Assignment 2 &

Discussion
7


9

(3/9
-
3/15)

Spring Break (n
o classes)

Project proposal

10

(3/16
-
3/22)

Topic 7: Knowledge engineering

Read topic notes, text book chapter 9, any
relevant articles

Discussion
8


11

(3/23
-
3/29)

Topic 8: Search methodologies

Read topic notes, chapter 4 of
Coppin
, any
relevant artic
les

Discussion
9


12

(3/30
-
4/5)

Topic 9: Data mining and knowledge
discovery

Read topic notes, text book chapter 9, any
relevant articles

Assignment 3 & Discussion
10


13

(4/6
-
4/12)

Topic 10: Case
-
based reasoning

Read topic notes, relevant articles

Di
scussion
11


14

(4/13
-
4/19)

Topic 11: Natural language processing

Read topic notes, relevant articles

Discussion
12

15

(4/20
-
4/26)

Topic 12: Hybrid Intelligent Systems

Read topic notes, text book chapter 8,
relevant articles


Discussion
13


16

(4/27
-
5/
3)


Topic 13 Intelligent agents

Read topic notes, relevant articles

Course ends

Assignment 4 & Project

17

(5/4
-
5/10)



Exam

Artificial Intelligence

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of
9

Instructor responsibilities

As an instructor of this course, I am responsible for:



posting lecture notes online in a timely ma
nner
;



responding to student concerns via
e
-
mail

in a timely manner (within 24 hours usually if I
am in town)
;




m
onitoring and
summarizing

discussions
;



logging in to
CougarView

daily to study new developments
;



posting
discussions

and important announcements

in a timely fashion


Student responsibilities

As a student in this course, you are responsible for:



managing your time and maintaining the discipline required to meet course requirements



covering all readings, online and offline, in a timely manner



active
ly participating in discussions and adhering to course deadlines



reading any e
-
mail sent by me and responding promptly

when required



logging in to
CougarView
regularly

to study new developments

(“I didn’t know” or “I didn’t
look on website” is not an accep
table excuse for failing to meet the course requirements)



(for those attending lecture classes) maintaining classroom etiquette
,

which includes not
distracting others in the class. Cell phones must be turned off, and computer use is only
allowed for activi
ties directly related to classroom activities.

If you fail to meet your responsibilities, you do so at your own risk.



Other important items

1.
Email is the preferred means of communication. Please use CougarView
e
-
mail

for all course
related messages.

2
.
Please CC to yourself any
e
-
mail

that you need to be sure has reached me. Please note that
I
am unable to provide individual confirmation
of receipt of your
e
-
mail

sent to me.

3
. Always include your original message (and any responses to it) in your mess
ages. This is
helpful for me as I receive many student messages during the semester.

5
. Please observe online etiquette; the absence of facial cues and voice inflections may render
offensive any intended humor. If you’re critical of something, be careful t
o criticize the idea and
not the person. Disagree cordially. No personal attacks (e.g. on religion, gender, race, etc.) are
permitted; such postings will be deleted without warning and the student will be penalized.


Academic dishonesty

Academic dishonesty

includes, but is not limited to, activities such as cheating and plagiarism
(http://aa.colstate.edu/advising/a.htm#Academic Dishonesty/Academic Misconduct). It is a basis
for disciplinary action. Any work turned in for individual credit must be entirely t
he work of the
student submitting the work. You may share ideas but submitting identical assignments (for
example) will be considered cheating. You may discuss the material in the course and help one
another with concepts; however,
any work you hand in for

a grade must be your own
.


A simple way to avoid inadvertent plagiarism is to talk about the assignments, but don't read
each other's work or write solutions together. For your own protection, keep old versions of
assignments to establish ownership unti
l after the assignment has been graded and returned to
you. If you have any questions about this, please contact me immediately.
All work that is not
your own
must

be properly cited.

This includes any material found on the Internet.
Collaboration
is not pe
rmitted on assignments or exams in this course
, unless explicitly specified by the
instructor.

Artificial Intelligence

8

of
9


No cheating in any form will be tolerated.
The penalty for the first occurrence of academic
dishonesty is a grade of F in this course
. Other penalties include s
uspension from the Computer
Science program at CSU and/or dismissal from the program. All instances of cheating will be
documented in writing in the university records. Students will be expected to discuss the
academic misconduct with the faculty member an
d the chairperson of the department. For more
details see
http://aa.colstate.edu/faculty/FacHandbook0203/sec100.htm#109.14

and the
Student Handbook:
http://sa.colstate.edu/handbook/handbook2003.pdf



For exams, access to any type of written material or discussion of any kind (except with me) is
not allowed. In addition to instructor
-
initiated penalties, there wil
l also be university
-
initiated
penalties and disciplinary action. Academic dishonesty could involve:



Having a tutor or friend complete a portion of your assignments.



Having a reviewer make extensive revisions to an assignment.



Copying work submitted by
another student.



Using information from online information services without proper citation.


Getting help

Student assistants in the Computer Center (see
http://cins.colstate.edu/studenthelp/in
dex.htm
)
can help you with basic computer
-
related problems such as logging on to the network, saving
your work, etc., but they are not obligated to help you with your assignments. There are several
tutors in the Computer Science department who may be able

to help you with some course
-
related work. Their schedule is posted in the Computer Science department and on the website
http://cs.colstate.edu
. You can always contact me through
e
-
mail
, fax, mail, in person during my

posted office hours or by appointment

at a mutually convenient time
.


Some URLs of interest

Websites that provide general information, including FAQ’s on advising and curricular issues:

1.
http:/
/cs.colstate.edu/html_hi/home/main.aspx

(CS, Computer Science, department at CSU)

2.
http://cs.colstate.edu/html_hi/home/faq_advising.aspx

(Advising FAQ)

3.
http://cs.colstate.edu/html_hi/academics/advisors.aspx

(Advisor listing)

4.
http://cs.colstate.edu/html_hi/programs/grad.aspx

(Graduate program main page
)

5.
http://cs.colstate.edu/html_hi/home/faq.aspx

(General FAQ, find free software!)

6.
http://cs.colstate.edu/html_hi/home/job_board
.aspx

(Job opportunities)

7.
http://csc.colstate.edu/memos/internship/

(Internship FAQ)

8.
http://clubs
-
orgs.colstate.edu/acm/

(Join ACM, a professio
nal organization)

9.
http://cs.colstate.edu/html_hi/academics/course_requests.aspx

(Request a course!)

10.
http://cs.colstate.edu/html_hi/academics/online_support.aspx

(Online student FAQ)

11.
http://cins.colstate.edu/

(Main page of the Computer Info and Networking Services at CSU)

12.
http://cs.colstate.edu/html_hi/facstaff/facstaff.aspx

(Faculty and staff pages)

13.
http://academics.colstate.edu/calendars/

(CSU calendar, important dates)

14.
http://registrar.colstate.edu/

(Registrar, apply for graduation, etc.)

15.
http://academics.colstate.edu

(Main page for ISIS registration system, schedule of classes)


Atten
dance

For the online portion of this class, attendance involves logging in at least thrice a week on
CougarView

and spending a least an hour each session. Be aware that you get from this course
only what you put in


if you log in and then aimlessly surf
the Internet for an hour during a
CougarView

session, you will not learn course
-
related material. Note that you are ultimately
Artificial Intelligence

9

of
9

responsible for reading the textbook, all discussions, important announcements, etc. in order to
ensure a successful learning exp
erience.


Student
W
eb space and
e
-
mail

account

All currently enrolled students (including online students) can request free Web server space on
the CSU student Web server. Simply go to
http://students.colstate.edu

and click on the "Get
Free Web Pages" icon. Then click on the links to request the account. Under normal
circumstances, the account and space will be created in a matter of seconds. This server is also
.NET capable. As a CSU student, you also have an
e
-
ma
il

account with the form
lastname_firstname@colstate.edu
. Since most CSU
-
related
e
-
mail
s are sent to this account,
please check it regularly or enable
e
-
mail

forwarding to another account.


Website(s)

It

is your responsibility to frequently look at the course material on
CougarView

to keep your
knowledge of class activities current.

Your instructor is

not responsible for missed assignments
or exams because you did not read an announcement regarding the de
adlines.


Confidentiality of shared information

CSU does not guarantee the confidentiality of information shared by students in the course
environment. Therefore, you should not share any confidential information from employers
unless explicitly released
for public use. It is not the instructor’s responsibility to ensure the
privacy, integrity, confidentiality or security of shared information.


CSU's ADA compliance statement

If you have a documented disability as described by the Rehabilitation Act of 197
3 (P.L. 933
-
112 Section 504) and Americans with Disabilities Act (ADA) and would like to request academic
and/or physical accommodations please contact Joy Norman at the Office of Disability Services
in the Center for Academic Support and Student Retention
, Tucker Hall (706) 568
-
2330, as
soon as possible. Course requirements will not be waived but reasonable accommodations may
be provided as appropriate.


Important dates/holidays

First day of classes:
Mon
day,
January

12

Schedule change

Drop/Add Courses
:

Ja
nuary
12
-
1
5

Add Courses only
:

January 1
6

Martin Luther King Holiday (no classes, offices closed)
: Monday,
January
19

Deadline to Withdraw

from course
:

Mon
day
, February
9

Mid
-
term: March 5

Spring

break

(no classes)
:
March
9
-
15

Last class day

for all courses
:
Mon
day,
May 4

Exams:

Wednesday, May 6


Monday May 11