This course explores basic human cognitive processes, to include categorization, inference, problem solving, decision making, learning, and creativity, with an eye towards computational modeling of these processes. But this is not a cognitive modeling course per se.  Certainly, I will not prescribe methodologies for cognitive modeling. Rather the course is intended to whet your appetite for research at the nexus of cognition and computation, with an emphasis on the lesser studied topics among most computer scientists (i.e., natural cognition), and to deepen your knowledge in some important areas of that intersection.

While I have listed themes of categorization, inference, problem solving, decision making, learning, and creativity separately, they overlap very substantially. Indeed, learning will pervade the material we cover on the other themes. Because learning will be pervasive, I won’t call it out separately on the course Schedule — it will be part of many weeks’ material and discussions. Ideally, our discussions will synthesize across the topics listed as the course progresses, and I’ve set aside class time at the end of the semester to treat synthesis explicitly.

This is a seminar course of readings and discussion, not a lecture-based course, with a final student project being the focus of the last third of the semester. The coverage is far from exhaustive. I have assigned many readings that are “classics” or otherwise exemplars, but you will augment these articles by finding, reading, and reporting on more recent and more diverse works that reference and perhaps expand on these earlier papers. These additional readings and final project will allow you to somewhat customize the course to your particular interests, while staying within themes that we are addressing.