CS 448 Machine Learning -- Fall 2011



Overview:

This course will address machine learning techniques and philosophical issues concerning machine learning. Learning techniques will include: Darwinian optimization techniques (sometimes called artificial evolution or artificial life), learning in simulated neural networks, plus state space tree search and modification. Philosophical issues include: "Can a machine be intelligent?","Can a digital computer without a body be intelligent in the way people are?", "Is consciousness a precondition of intelligence?", "Is intelligence without emotion an oxymoron?", and, "How can machine intelligence be assessed?".

Approach:

Class time will be used mostly for lectures and group discussions of readings and related issues. Out of class time will be divided between reading and programming in Java. The texts address philosophical and technical aspects of machine learning and intelligence. You will write programs to implement some learning techniques from scratch; for others, working programs will be provided to experiment with and/or modify. Students (selected at random at the beginning of the discussion period) will present the 2 or 3 main ideas in the day's reading.

Evaluation:

Your grade will be determined by exams, labs, and discussions. Labs will count 40%, exams 60%. There will a mid-term, and a final which will count double the mid-term. Exams will cover philosophical and technical topics. Labs must be demonstrated on time; late labs will not be accepted (as solutions will typically be distributed immediately after the due date; you can use the sample solution to do the next part of the lab if you didn't finish yours).

Plagiarism:

You are welcome to use any and all code you find in books, notes, on disk or on the Internet -- so long as you have permission and credit your source. All work you hand in as your own must be your own. The penalty for misrepresenting another's work as your own (commonly called plagiarism) is failure in the course.

Finally:

If you feel the class is going too fast, or too slow, or in the wrong direction -- let me know!