Model Curriculum

Introduction
Cognitive systems is a fast-developing new approach to understanding intelligent systems. It is founded on many different disciplines and, consequently, an ideal curriculum for teaching a course on cognitive systems - natural and/or artificial - would have to embrace a huge number of topics. In a perfect world, a course would address

  • artificial intelligence
  • psychology
  • neuroscience
  • non-linear dynamical systems theory
  • synergetics
  • autonomous systems theory
  • machine learning
  • pattern recognition
  • computer vision
  • sound recognition
  • haptic sensing
  • aural perception
  • cybernetics
  • neural networks
  • evolutionary computation
  • computer science
  • epistemology
  • philosophy
  • linguistics
  • semiotics
  • robotics
  • manipulation
  • communication
All of these topics, and many others, impact in some way or other on cognitive systems.

In this article, we plan to create a model curriculum for such a course. We do so in the knowledge that it would probably not be feasible to teach the full course in a single semester, for example. It is more a model curriculum that can be sampled (or pruned) to suit the needs or interests of a particular instructor. Doing it this way has the advantage that you know what you are leaving out.

For a PDF of the latest draft of the Cognitive Systems Model Curriculum, please click here.

Ideally, each section of this curriculum would have some supporting course material to make the creation of a course on cognitive systems easier. You can find a collection of links to some course material on the Course Material page.

Refer also to the results of Network Action 044-4 Cognitive Systems Outreach Curriculum Project.