Cognitive Science | Math & Logic for Cognitive Science
Q520 | 1031 | L Moss

1:00-2:15, TR, BH 215

Q520 introduces a wide variety of mathematical topics pertinent to
cognitive science and related fields.  Those topics are primarily
taken from probability and linear algebra, and secondarily from
logic, algorithms and complexity theory, and optimization. The
intended applications will be to models for uncertain reasoning,
such as Bayesian nets and other graphical models, hidden Markov
models, and some types of neural nets.  In addition, the class will
also present the basics of logic, both in its classical form and
some systems for areas like default reasoning.  It will also
introduce concepts like entropy and game-theoretic equilibrium.  So
the class will see many application areas. But it will not be a
class in using or even building application tools. And although the
applications include some of the main tools in cognitive science and
artificial intelligence, the overall point is to introduce a large
body of related mathematical ideas in a friendly way, so that
cognitive science students will be stimulated to continue learning
in their own areas.