When & Where
Tuesdays & Thursdays, 3:30-4:50pm in SBSG 2200

Lisa Pearl, Department of Cognitive Sciences, SBSG 2314
Office Hours for Lisa: Tuesday 11:00am - 12:00pm, and by appointment.
Email is the best way to reach her to schedule an appointment
not during regular office hours.

Mark Steyvers, Department of Cognitive Sciences, SBSG 2316
Office Hours for Mark: By appointment.
Email is the best way to reach him to schedule an appointment.

This class also has a message board on EEE.


  • 12/26/14: Welcome to the class webpage!
    All readings can be accessed using the username and password received in the first class session. (Check the "other questions" forum of the message board to get it.) Of course, you can also always track down these articles yourself in most cases. Look to the schedule, and be thinking about what papers/topics you'd like to present to the class.

    Before the first session, please make sure you have viewed the message board and posted your response for the first set of discussion points. (It's easy, we promise.)

Human cognition is incredibly complex, involving multiple domains of knowledge, a variety of cognitive processes, and many types of observable behavior. Computational methods have been used successfully to investigate different questions about cognition, drawing on theoretical assumptions and architectures that can be broadly applied (e.g., analysis-by-synthesis, generative models, and Bayesian inference). We examine a variety of computational approaches to questions in cognition, evaluating their performance, their similarities, their strengths, and their weaknesses, with a focus on their ability to explain the observable data we have about human cognition.

A bibliography of the articles we'll read and refer to can be found in the readings section, and all articles can be accessed through the schedule page (provided you have the class username and password).

We consider two broad questions throughout the course:

  1. Principles underlying models of cognition: What are the fundamental assumptions about cognition that computational models rely on? What are the processes underlying human behavior that computational models attempt to encode or generate from other more basic components? What is the relationship between the implicit knowledge, the underlying process, and the observable data that an accurate model must include?
  2. Computational models of cognition: Human cognition involves an amazingly complex set of systems capable of generating the human behavior we observe in a variety of different domains, including language, decision-making, and memory. What can computational modeling methods tell us about the knowledge humans implicitly have in each domain? What about the processes that generate the observable human behavior?