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.