Lectures: 1 session / week, 3 hours / session
This class will consider computational models of some of the core structures of human cognition: concepts, causal relationships, word meanings and intuitive theories. We will emphasize questions of inductive learning and inference and the representation of knowledge. Class meetings will mix lectures and discussion, covering both the necessary cognitive science and computational background and confronting state-of-the-art research questions.
This class is suitable for intermediate to advanced undergraduates or graduate students specializing in cognitive science, artificial intelligence, and related fields. A course in cognitive science, and a course in probability or statistics, are helpful.
Before each week's meeting, every student attending the class is required to submit a short (approximately one page) response to one of the topics for that week's discussion. These notes are due by 2:00 p.m. on the day of class. They should be submitted electronically by posting to the class discussion board. Students are encouraged to read as many of these responses as they can before class, and to respond to others' posts using the interactive features of the discussion board.
Students will also be required to submit a term project that confronts some open research question related to the topics and approaches discussed in class.