HMI722. Cognitive Modeling, 3p

Instructor Rita Kovordanyi, IDA/LiTH,
Semester Spring 2004 Course homepage
Prerequisites Introductory course in AI. Familiarity with basic AI programming techniques.
  1. Lectures introducing basic modeling concepts and theoretical problems.
  2. Seminars on how different modeling paradigms relate to each other.
  3. Small modeling assignments using available modeling tools.
  4. Cognitive neuroscience as a basis for cognitive modeling; design principles for biologically based cognitive models.
  5. Marrs three levels of analysis; should cognitive modeling be focused on resulting behavior or its underlying cognitive mechanisms?
  6. Virtues and disadvantages of connectionist versus symbolic models.
  7. Interactive activation models; processing in cascade. Unified architectures of cognition; comparison between EPIC, ACT-R and Soar.
  8. Hybrid architectures: ACT-R/PM, EPIC-Soar, COGNET.


For 3p

Active participation in the seminars and lectures.

+2p: Completion and report on small modeling assignments plus a short term paper in which an existing model is critically scrutinized.

++2p: Completion and written presentation of a small modeling project.