intro class
... after a discussion, we decided to stick to the AIAMA textbook
survey of topics rather than focus on machine learning through
the Udacity course.
The first assignment is posted on the
assignments page.
background
This is an intermediate / upper level CS course,
looking at how to program computers to do
the things that people do.
Essentially then this is an "advanced algorithms" class,
with lots of math approaches to hard problems such as image analysis
and computer vision, natural language processing, robot navigation,
and automated reasoning.
this semester
Once we see who's taking the class,
I want to have a discussion of topics and resources.
The default textbook that I've used several times is
Stuart Russell & Peter Norvig's "Artificial Intelligence: A Modern Approach, 3rd edition"
(AIAMA), which covers a lot of ground and is popular as a college AI text.
Another option is to use that and other online sources
as resources, but follow Peter Norvig & Sebastian Thrun's
Udacity's Intro AI
class, which is more focused on statistical methods then AIAMA,
which looks at knowledge representation and other, perhaps less "hot", techniques.
(Here is it's
syllabus.
I'd also like to choose a coding language that
we can use for class work, probably either Python
or Common Lisp (both of which are available for AIMA).
The task of making a machine into a person - a sentient being, however you define that -
is these days usually called "artificial general intelligence." That is not typically
what AI researchers work on, and is not really the focus of this course. Instead, we
like most folks in the field will be dealing with various smaller human abilities.
(tentative) homework
Browse through the topics in both AIAMA and the udacity course
and look at the coding and math levels in each, and come to our first full
class prepared to discuss.
