Syllabus for SSE 636

Computational Intelligence Applications

Changes are certain.

Fall Semester 2009 (09F)

Instructor: Dr. Paul E. MacNeil

Office:       Suite 223a, School of Engineering

Phone:       478-301-2185

                  478-301-2732

Email:        macneil_pe@mercer.edu

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Textbooks and Supplies:

Texts (including web sites):

(Read the note after the list of texts before you buy!)

• AI for Game Developers (1st ed.), by David M. Bourg and Glen Seemann, O'Reilly, ISBN 0596005555 (2004) (required) Check Out This Text at Amazon.com

• AI Application Programming (1st ed.), by M. Tim Jones, Charles River Media, ISBN 1584504218 (2005) (required) Check Out This Text at Amazon.com

• IEEE Computational Intelligence Society
• Wikipedia Article on Computational Intelligence
• Wikipedia Article on Genetic Algorithms
• Wikipedia Article on Fuzzy Logic
• Wikipedia Article on Neural Networks
• Another Wikipedia Article on Neural Networks
• Fuzzy Logic Course
• Fuzzy Logic FAQ
• comp.ai.fuzzy group
• Wikipedia Article on Genetic Programming
• genetic-programming.com Fine work by John Koza and others.
• Genetic Algorithm FAQ (see especially Part 2) Note that this FAQ has not been updated for some time.
• The Genetic Programming Notebook
• Neural Networks - An Introduction
• Neural Net Tutorial
• Neural Networks with Java: neural net overview
• Self Organizing Maps

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Software (including web sites):

• Note that this course is intended to be OS neutral.

• TBD - more information will be available later.

• An Internet ftp client of your choice.  Core FTP LE is free and works well http://www.coreftp.com/ .  (Required, but your choice)

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Other Useful Resources (including web sites):

• TBD

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Catalog Description (Course Purpose):

Appications of computational intelligence methods to solve problems.

The texts are written in C and in C/C++. Your implementation language may be Java, C#, or (object-oriented) C++.

Please note that this course is conducted *asynchronously* with regard to the face-to-face class meeting schedule. That is, the course begins on August 25, 2009, for *all* students.

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Course Objectives:

Breadth and Depth in Defining, Analyzing, and Solving Complex Problems:

• After successfully completing this course, you should be able to demonstrate a basic capability to apply advanced computational intelligence methods to solve complex problems.

Communicate Technical Aspects of the Solution for Complex Software Engineering Problems to a Technical Audience:

• After successfully completing this course, you should be able to demonstrate a basic ability to communicate regarding the application of dadvanced computational intelligence methods to a technical audience.

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Prerequisites:

SSE 550 Object-Oriented Design I or permission of the program director.

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Class Location:

• The Macon face-to-face meetings take place in the Engineering Building Room 216b. (Directions to the Macon campus, and a map of the Macon campus can be found at  http://www2.mercer.edu/Admissions/macon.html and  http://www2.mercer.edu/About_Mercer/MaconMap/default.htm [look for Building 34 on the map], respectively.)

• The Online Learning asynchronous "meetings" take place in Cyberspace; i.e., on the Internet.

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Grading:

Credit will be given only for original work.

Listserv/Wiki Contributions

• The Listserv/Wiki contribution grade will be awarded based on the professor's professional judgement regarding your contributions to the course.
• The course wiki pages are for technical issues, technical solutions, and other substantive material relevant to the course subject matter.
• Course-specific listserv messages are for technical issues, technical solutions, and other substantive material relevant to the course subject matter. Other course-related items (questions, procedural issues, etc.) are also welcome.
• There is another listserv that is not specific to any one course. Messages on this listserv are for software engineering-related items that are applicable to several courses or to no course.
• If you have a question about any of this, please ask!

More information about grading is contained in the General Project Rubric.

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Assignments:

• Purpose of projects:

  • Use the projects to develop your capabilities, and

  • Use the projects to demonstrate your capabilities.

• Deliverables for all projects:

  • Your report should be a single, standalone document in .html or .doc format.

  • Your report should be organized in such a way as to make the topics that you want credit for covering easy to find, and demonstrate your capabilities clearly and convincingly. Everything you want considered for credit, including code and tests (including test results), should be included in the report.

  • Each project can be a single, integrated project that tries to actually do something, or a collection of exercises that demonstrate your capabilities but don't accomplish anything else, or any combination of these two alternatives that you find convenient.

  • You may include other material outside of the report, if you wish, but this material may or may not be considered in evaluating your work.

  • For each capability that you demonstrate within a report or major section of that report, you may present only the final result of your work; you need not demonstrate every step in the development of that result.

• Some suggestions for doing a project are contained in the One Way to Do a Project page.

• Project 1 (solo):

  • Pick a computational intelligence topic from one or both of the texts. Announce your selection via the listserv. If you have not previously done a computational intelligence course with me, choose Genetic Algorithms.

  • Develop an example application of this topic, using this development effort to both develop and demonstrate your capabilities in applying the techniques of this topic.

• Project 2 (solo):

  • Pick one or more computational intelligence topic(s) from one or both of the texts. (Please do not repeat topics from Project 1.) Announce your selection via the listserv. If you have not previously done a computational intelligence course with me, choose Neural Networks.

  • Develop an example application of this topic (these topics), using this development effort to both develop and demonstrate your capabilities in applying the techniques of this topic (these topics).

• Project 3 (solo):

  • Pick one or more computational intelligence topic(s) from one or both of the texts. (Please do not repeat topics from Project 1 or Project 2.) Announce your selection via the listserv. If you have not previously done a computational intelligence course with me, choose Fuzzy Logic.

  • Develop an example application of this topic (these topics), using this development effort to both develop and demonstrate your capabilities in applying the techniques of this topic (these topics).

• Project 4 (team):

  • Pick one or more computational intelligence topic(s) from one or both of the texts. (You may repeat some topics from Project 1, Project 2 or Project 3, but please include at least one new topic.) Announce your selection via the listserv).

  • Develop an example application of this topic (these topics), using this development effort to both develop and demonstrate your capabilities in applying the techniques of this topic (these topics).

• TBD

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Additional Information:

• Asynchronous Learning Nets (ALNs)

  • Self Study: You study the texts and any other course study material on your own.

  • Collaborative Projects: After your self-study, you collaborate (via the Internet [email, ftp]) with your partner(s) to produce a team product. Your collaborative work is substantial, asynchronous, and rapid.

  • This course is an online learning course. Please read this Online Learning web page regarding online learning in this course and this program.

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• What Do I Do?

• Subscribe to the course email listserv and be able to access our FTP server; your professor can tell you how to do this.

• Study the assigned material.

• Write and read email messages about ideas, problems and solutions to do with the assigned study material.

• Do the assigned exercises.

• Write and read email messages (to/from the listserv) about ideas, problems and solutions to do with the assigned homework.

• Review the exercises done by other people, as assigned by the professor.

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Changes to this Syllabus:

There will be changes to this syllabus, so check back frequently, and don't forget to hit "Reload" or "Refresh".

Schedule of Events and Assignments:

TBD

Notes:

tbd

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Schedule of Macon Face-to-face Class Meetings:

attendance is 100% optional.

All Macon face-to-face meetings are from 6:00 pm to 9:00 pm.

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Important Additional Information:
Students requiring accommodations for a disability should inform the instructor at the close of the first class meeting or as soon as possible.  If you are not registered with Disability Services, the instructor will refer you to the Disability Support Services office for consultation regarding documentation of your disability and eligibility for accommodations under the ADA/504.  In order to receive accommodations, eligible students must provide each instructor with a “Faculty Accommodation Form” from Disability Services.  Students must return the completed and signed form to the Disability Services Coordinator on the 3rd floor of the Connell Student Center.  Students with a documented disability who do not wish to use academic accommodations are also strongly encouraged to register with Disability Services and complete a Faculty Accommodation Form each semester.  For further information, please contact Carole Burrowbridge, Disability Services Coordinator, at 301-2778 or visit the web site at http://www.mercer.edu/stu_support/swd.htm

Accreditation: Mercer University is accredited by SACS.