|
This course will introduce the fundamental questions, findings and methods of cognitive science. The computational approach to cognition and the notion of abstract mental representation are introduced within the interdisciplinary framework of the field. Basic knowledge of cognition, computation, and evolution is surveyed. Symbol systems are described and their role in standard representations is discussed. Artificial neural networks are proposed as a model of both the brain and the mind. Linguistic models are introduced and philosophical challenges are discussed.
Basic techniques of descriptive and inferential statistics and their applications to research in psychology.
Linguistic diversity and change; cultural emphases in language and relation to world view.
Introduction to the computational study of human and machine intelligence. Discussion of computational models, algorithms, and research in neural processing, vision, memory, learning, reasoning, and information processing.
The course will feature individual research projects of a relatively modest scale. Students will have wide latitude in negotiating a realm of study, as well as the approach to study of the selected topic. The research project must be interdisciplinary to the extent that it draws on at least two contributing disciplines to cognitive science. Furthermore, the project must stand in a justifiable relationship to the computational/representational assumption which unifies the field. Beyond this, the project must be mindful of the constraints of capstone objectives for the arts and sciences, learning outcomes for cognitive science majors, and to the interests and orientation of the professor teaching the course.