ECE 469: Artificial Intelligence

Fall 2013

Wenesday 5:00 PM - 6:00 PM Rm 502, Thursday 1:00 PM - 3:00 PM Rm 506

Instructor Info

Instructor: Carl Sable
e-mail: CarlSable.Cooper@gmail.com
Office: Room 614

Textbook

"Artificial Intelligence: A Modern Appraoch, 3rd Ed."
by Stuart Russell and Peter Norvig
The book has a nice associated website

Grading

Project 1: 33 1/3%
Project 2: 33 1/3%
Final Exam: 33 1/3%

Projects

  • Project #1
    Click here for a suggested schedule and other helpful information
    Click here for a readme file briefly describing the files provided below
    Click here to download my Checkers executable (compiled under Cygwin)
    Click here to download my Othello executable (compiled under cygwin)
    Click here for cygwin1.dll (if you need it; see the readme)
    Click here to download my Checkers executable (compiled under Ubuntu)
    Click here to download my Othello executable (compiled under Ubuntu)
    Sample Checkers board #1
    Sample Checkers board #2
    Sample Checkers board #3
    Sample Checkers board #4
    Sample Checkers board #5
    Sample Checkers board #6
    Sample Checkers board #7
    Sample Checkers board #8
    Sample Checkers board #9
    Sample Checkers board #10
    Sample Othello board #1
    Sample Othello board #2
  • Project #2
    Click here for my annoated version of Figure 18.24
    Click here for the raw data of the Wisconsin Diagnostic Breast Cancer (WDBC) dataset
    Click here for a description of the data set by its creators
    Click here for my pre-processed WDBC training set file
    Click here for my pre-processed WDBC test set file
    Click here for my initial neural network for the WDBC dataset
    Click here for my trained neural network for the WDBC dataset
    (with a learning rate of 0.1 after 100 epochs)
    Click here for my results file (using the above trained neural network)
    Click here for a mini WDBC training set with one document (to help with debugging)
    Click here for the neural network trained on the mini WDBC training set
    (with a learning rate of 0.1 after 1 epoch)
    Click here for my grades training file
    Click here for my grades test file
    Click here for my inital neural network for the grades dataset
    Click here for my trained neural network for the grades dataset
    (with a learning rate of 0.05 after 100 epochs)
    Click here for my results file (using the above trained neural network)

    Schedule

    The schedule will be updated as the semester progresses.