04-801/F2-Carnegie Mellon University Africa - Carnegie Mellon University


Artificial Cognitive Systems

Course discipline: ICT
Units: 6
Lecture/Lab/Rep hours/week: 4 hours lecture/week

Semester/year offered (fall/spring, even/odd years): Fall, all years
Pre-requisites: None

Course description:

The primary goal of this course is to expose students to a comprehensive cross-section of the main elements of artificial cognitive systems. Inspired by artificial intelligence, developmental psychology, and cognitive neuroscience, the aim is to build systems that can act on their own to achieve goals: perceiving their environment, anticipating the need to act, learning from experience, and adapting to changing circumstances.

Learning objectives:

Students will learn to identify the key characteristics of cognition and the different levels of abstraction that are required to model cognitive systems. They will also learn to recognize the chief differences between the two main paradigms of cognitive science and to understand contemporary attempts to reconcile them. They will learn how models of cognition are captured by various cognitive architectures and they will study several architectures at different levels of detail. These will provide the basis for further study of the key issues of autonomy, embodiment, learning & development, memory & prospection, knowledge & representation, and social cognition.


After completing this course, students should be able to:

  • Identify the key attributes of a cognitive system.
  • Explain the main characteristics of cognitivist, emergent, and hybrid cognitive science.
  • Compare cognitive architectures using several criteria and design an outline cognitive architecture for a given application scenario.
  • Explain how a specific hybrid cognitive architecture works and show how it can be used to allow a robot to reason about its environment and achieve goals set by a user.
  • Explain the implications of computational functionalism and its relationship to the embodied cognition thesis.
  • Distinguish between learning and development and explain how these processes are facilitated by different forms of memory and knowledge.

Content details:

  • The Nature of Cognition
  • Paradigms of Cognitive Science
  • Cognitive Architectures
  • Autonomy
  • Embodiment
  • Development and Learning
  • Memory and Prospection
  • Knowledge & Representation
  • Social Cognition

Delivery: Face-to-face

Faculty: David Vernon