Course Syllabus

CPSC5185G-V01 Artificial Intelligence, CRN: 21358

Spring Semester 2013

Instructor | Description | Objectives |Resources |Access |Coursework |Communication Assessment | Responsibilities|Schedule | Policies | Help | Importantdates

Instructor information

Name: Dr. Shamim Khan

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

Office hours:

Office hours:

Mon, Wed10:00 – 11:00 AM, 3:00-6:00 PM

Tue, Thu5:00 – 6:00 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.

E-mail: (CougarView e-mail preferred for course related communication)

Web:

Office Phone: 706-507-8184; School Phone: 706-507 8170; School Fax: 706/565-3529

Description

This course covers the fundamentals of artificial intelligence and its application to problem solving. The emphasis is on popular AI methodologies used for developing software systems known as intelligent systems. This course involves practical work.

Pre-requisite knowledge: Programming experience at the intermediate level or higher. Abasic knowledge of vectors, matrices, calculus and probability theory would be useful.

Learning objectives

After completing this course, you should be able to: / How the learning outcome will be assessed
  • Defineartificial intelligence (AI) and state its goals
  • Describe the characteristics of intelligence
  • Name common (artificially)intelligent system methodologies and give examples of such systems
/
  • Weekly on-line discussions

  • Expressknowledge using logical expressions
  • Derive new knowledge through reasoning using propositional and predicate logic
/
  • Weekly on-line discussions
  • Assignment

  • Demonstrate understanding of the structure and operation of a rule-based expert system
  • Build a simple rule-based expert system using an expert system shell
/
  • Weekly on-line discussions
  • Assignment

  • Demonstrate understanding of fuzzy logic and fuzzy reasoning
  • Build a simple fuzzy rule-based expert system using MATLAB or a fuzzy system shell
/
  • Weekly on-line discussions
  • Assignment

  • Demonstrate understanding of the artificial neuron and the Artificial Neural Network (ANN) as a simple model of the biological neuron and neuronal networks
  • Demonstrate understanding of machine learning through supervised and unsupervised training of ANNs
  • Build a simple ANN system using MATLAB or an ANN development environment
/
  • Weekly on-line discussions
  • Assignment

  • Demonstrate a basic understanding of evolution in nature, and how evolutionary computation methodologies are modeled on it
  • Demonstrate sufficient understanding of Genetic Algorithms (GA) by developing a GA-based solution to a problem
/
  • Weekly on-line discussions
  • Assignment

  • Demonstrate a basic understanding of common knowledge representation schemes
/
  • Weekly on-line discussions

  • Demonstrate understanding of the concept of search space and various methods for conducting search for finding a solution
/
  • Weekly on-line discussions

  • Demonstrate understanding of Case-Based Reasoning (CBR) as an analogy-based problem solving strategy
/
  • Weekly on-line discussions

  • Demonstrate a basic understanding of probabilistic reasoning used in working with uncertain data
/
  • Weekly on-line discussions

  • Describe the function of an intelligent (software) agent, their classification and current applications
/
  • Weekly on-line discussions

  • Decide which type of intelligent system methodology would be suitable for a given application problem
/
  • Project proposal

  • Develop a simple intelligent system based on a chosen methodology
/
  • Project work and report

Required reading material

1 / / Textbook:
Artificial Intelligence Illuminated, Author: B. Coppin, Publisher: Jones and Bartlett, 2004
2 / Topic notes and lecture slides (Available online)

Supplementary reading material

1 / Artificial Intelligence: A Guide to Intelligent Systems, 2nd edition
Author: Michael Negnevitsky, Publisher: Addison Wesley, 2004
2 / Other material cited in lectures, topic notes and the course Web site

Software required

  • Jess expert system shell

Available for free download at:

  • MATLAB & Simulink Student Version, Release 2009a for Windows

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 online purchase[1] as detailed below (you may be able to find sources in addition to this).

Vendor: Mathworks

Price: $99

Student versions of Neural networks (NN), Fuzzy logic (FL) and Global Optimization (includes Genetic algorithms) toolboxes: $29 each.

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

As an alternative to MATLAB, you can use one of the less sophisticated public domain NN, FL and GA software available for free from the Internet. In that case, you’ll be responsible for sourcing the software. Remember that these may not be as powerful or stable, and I may not be able to give you much support.

How to Access the Course

Desire2Learn(D2L) is the new CSU Learning Management System -- what is commonly known as CougarVIEW.You can access the course through the CougarView course management system at:

Your CougarVIEW username is the same as your CougarNET login ID & password.

Students who add courses during the first week of the semester, should be able to access their newly added course within 24-36 hours.

For additional help contact the CSU Help Desk (CCTbuilding level 1, phone:706-507-8199).

There are also a number of support resources for CougarView that are listed below:

Browser Checker

CougarVIEW-D2L Starter Guide

CougarView Troubleshooting

GeorgiaView D2L Help Center

D2L Help Files

Once you've entered 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. 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 CougarView.

Once you have clicked on the course's name and accessed the course, you will find a home page with a navigational bar displaying the course title and a set of links that is used to navigate between tools and homepages. Each course and home page has its own navbar that links to relevant tools and contents. Contents such as lecture notes and assignments will be progressively added to the course during the semester.

How This Course Will Work

This course will consist of lectures, readings, discussion questions, assignments, and an end-of semester project. On a weekly basis, you will need to:

  1. download the week’s lectures and any other relevant material made available online through CougarView;
  2. read lectures to review the main points of the week's lesson;
  3. get a more in depth understanding by completing 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. participate in the current discussion question and submit responses to others in the class based on your readings, online research and any personal experience;
  6. work on the current assignment to meet the given deadline;
  7. decide on and complete a final project in consultation with me.

Instructional Methods and Techniques

  1. The class will be taught online using D2L/CougarView.
  2. You must log in to CougarView regularly for learning activities and for finding out about latest additions, updates, announcements etc.
  3. You will be expected to submit assignments and project through CougarView drop boxes.
  4. You will participate in asynchronous threaded discussions.
  5. CougarView will be the major method of interaction in this course between you, your course instructor and fellow students in the class.

Communication

  1. E-mail is the preferred means of communication. Please use CougarView e-mail for all course related messages.
  2. Always include your original message (and any responses to it) in your messages. This is helpful for me as I receive many student messages during the semester and may need to be reminded of any previous communication with you related to your current message.
  3. You are also welcome to call me (707 507 8184) with any question or just for a chat. Please leave a voice message if I am out of office and I’ll call you back as soon as possible.

Assessment components

Weekly online discussions / 30% (including 20% for response to discussion questions, 10% for comments on other students' posts)
4 Assignments / 40%
Project / 30% (including 3% for the proposal)

Grading scale

A (Excellent) / 90% - 100%
B (Good) / 80% - 89%
C (Average) / 70-79 %
D (Poor, passing) / 60-69 %
F (Failing) / below 60 %
The WF grade is assigned when a student withdraws from a course after the W grade deadline (see Important dates/holidays) or when an instructor drops a student for excessive absences.

CourseAssignments

The course assignments will cover theoretical and practical aspects of some of the AI topics taught in the course. They will require you to read the topic material, do online research and do some hands-on work.

When you have completed an assignment consisting of more than one files, zip all files into a single file, then upload and submit this one file into CougarView using the Dropbox link. To zip an application in Windows, simply right-click the folder containing the application, select "Send To," then select "Compressed (zipped) Folder."

Online Discussions

There will be 14 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 eachweekly discussion question of at least 150 words (unless otherwise stated) by Thursday 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 one step further than just presenting facts, article excerpts).

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. Replies to comments made on your initial response to a discussion question 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 the 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 discussions is to stimulate academic debate. Critical thinking is highly desirable! If you do not agree with someone's post, you are encouraged to say so. Just do so with respect and courtesy.

Please address the person, whose post/comment you are responding to, by his/her first name 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 discussion contribution past its deadline will be ignored.

I will read every posted message and post my comment tosummarize the week’s discussion usually by Monday of the following week.

Discussion Etiquette

CSU is committed to open, frank, and insightful dialogue in all of its courses. Diversity has many manifestations, including diversity of thought, opinion, and values. Students are encouraged to be respectful of that diversity and to refrain from inappropriate commentary. Students as well as faculty should be guided by common sense and basic etiquette. The following are good guidelines on online etiquetteto follow:

  • Never post, transmit, promote, or distribute content that is known to be illegal.
  • Never post harassing, threatening, or embarrassing comments.
  • If you disagree with someone, respond to the subject, not the person.
  • Never post content that is harmful, abusive; racially, ethnically, or religiously offensive; vulgar; sexually explicit; or otherwise potentially offensive.
  • In the absence of facial cues and voice inflections, intended humor may sometimes be interpreted as offensive. If you’re critical of something, be careful to criticize the idea and not the person.

Project

The project will be due on Monday, April 29. It will involve the use of an intelligent system methodology to develop a system for finding a solution in an application chosen by you. Some of the project topics from last year are listed below as examples:

  • Predicting the strongest pre-flop set of four hole cards in apoker game by 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
  • Maze traversal by a robotic mouse driven by a genetic algorithm
  • Fuzzy real estate investment property evaluation system

You are required to send me a proposal for a project by mid-term (see weekly schedule below). The 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.

Instructor responsibilities

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

  • posting lectures online in a timely manner;
  • responding to student concerns via e-mail in a timely manner (within 24 hours usually if I am not out of town);
  • monitoring and summarizing discussions;
  • logging in to CougarView daily to study new developments;
  • providing timely feedback to you on your homework as appropriate
  • 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
  • actively 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
  • (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 purposes directly related to classroom activities.

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

Student Portfolio

Students are encouraged to keep and maintain a portfolio of all of their work (assignments, projects, etc.) throughout their academic program. It is recommended that you keep a copy on your personal H: drive atCSUand back it up regularly on your own portable media.

Readiness for Education at a Distance Indicator (READI)

READI is the Readiness for Education At a Distance Indicator. READI is an indicator of the degree to which distance learning will be a good fit for you. READI will help you prepare to be successful as a distance learning student. You are not penalized for guessing on the READI assessment; please enter an answer for each question on the assessment. Upon completion of READI you will receive a score report which will not only help you understand your strengths and opportunities for improvement, but will also provide you with resources to help you succeed. Remember, this assessment is strictly for your benefit. Take the time to rate yourself honestly by following this link:

Tentative weekly schedule (subject to change – check CougarView calendar for up-to-date assessment due dates)

WEEK # / TOPIC / ACTIVITIES/DUE ASSESSMENTS
1
(1/7-1/13) / Topic 1: Introduction to AI and intelligent systems / Read syllabus, become familiar with CougarView tools (calendar, e-mail, discussions)
Read topic note, text book chapters 1 & 2, any relevant articles
Topic 2: Logic for AI / Read topic notes, text book chapter 7, any relevant articles
2
(1/14-1/20) / Topic 3: Rule-based expert systems / Read topic notes, text book chapter 9, any relevant articles
Discussion 1
3
(1/21-1/27) / Topic 3: Rule-based expert systems (cont.) / Continue reading on rule-based expert systems
Discussion 2
1/16, Monday MLK day holiday
4
(1/28-2/3) / Topic 3: Rule-based expert systems (cont’d) / Continue reading on rule-based expert systems
Discussion 3
5
(2/4-2/10) / Topic 4: Fuzzy systems / Read topic notes, text book chapter 18, any relevant articles
Assignment 1(January 31)Discussion 4
6
(2/11-2/17) / Topic 4: Fuzzy systems (cont’d) / Continue reading on fuzzy logic-based systems
Discussion 5
7
(2/18-2/24) / Topic 5: Artificial neural networks / Read topic notes, text book chapter 11, any relevant articles
Discussion 6
8
(2/25-3/3) / Topic 5: Artificial neural networks (cont’d) / Continue reading on artificial neural networks
Assignment 2(February 25)Discussion 7
9
(3/4-3/10) / Spring Break (no classes) / Project proposal (March 5)
10
(3/11-3/17) / Topic 6: Evolutionary computation / Read text book chapters13 & 14,topic notes, any relevant articles
Discussion 8
11
(3/18-3/24) / Topic 6: Evolutionary computation (cont.) / Continue reading onevolutionary computation
Discussion 9
12
(3/25-3/31) / Topic 7: Knowledge representation / Read text book chapter 3 of Coppin, any relevant articles
Assignment 3 (March 25)Discussion 10
13
(4/1-4/7) / Topic 8: Search methodologies / any relevant articles
Discussion 11
14
(4/8-4/14) / Topic 9: Case-based reasoning / Read topic notes,any relevant articles
Discussion 12
15
(4/15-4/21) / Topic 10: Probabilistic reasoning / Read text book chapter 4,any relevant articles
Discussion 13
16
(4/22-4/28) / Topic 11:Intelligent Agents / Read text book chapter 19, any relevant articles
Assignment 4 (April 22) & Discussion 14
17 (4/29) / Project (April 29)

General Policies- Attendance

For the online portion of this class, attendance involves logging in at least thrice a week on CougarView and spending at least an hour each session. Be aware that you get from this course only what you put in. Note that you are ultimately responsible for reading the textbook, all discussions, important announcements, etc. in order to ensure a successful learning experience.Refer to the CSU Catalog
( for information on class attendance and withdrawal.