Q250 | 1056 | Eberle

Lecture: MW 2:30-3:45pm, WY 125 Lab section 1057: F, 9:05-9:55am, LI 503 One source of scientific theory comes from the analysis of empirical data. Often, however, it is not possible for the subject of study to be investigated directly and empirically, and, even when it is possible, it turns out that a very useful way to gain insights into scientific phenomena is to build models of them. Mathematics provides methods for the analysis of data. It also provides tools for building models of objects, states and processes studied in the different specific areas of science. The purpose of this course is to introduce students to some of the main mathematical and logical tools used in building models in cognitive science. The emphasis will be on the intuitive ideas behind the mathematics, i.e. the main goal will be to have the students learn the ideas first at an intuitive level and then to go towards a deeper acquaintance with the ideas. The course will introduce the main concepts, notions and results from first-order logic, machines, set theory, and linear algebra for parallel distributed processing (neural networks). The lab hours will be devoted primarily to the use of computational tools. The material for the course is self-contained and no prerequisites beyond a sound high school mathematics background are needed.