18-799-K   Artificial Cognitive Systems

Location: Africa

Units: 12

Semester Offered: Fall

Course discipline


Course description

The goal of this course is to expose students to a comprehensive cross-section of the main elements of artificial cognitive systems, a discipline that draws on artificial intelligence, developmental psychology, and cognitive neuroscience. Concepts are introduced in an intuitive, natural order, with an emphasis on the relationships among ideas and building to an overview of the field, equipping students with sufficient knowledge and understanding to study specific topics in greater depth. The course is delivered through a mix of teaching, reading, and in-class discussion. A particular feature of the course is its emphasis on progressive deepening: covering topics several times in increasing detail as the course proceeds. This approach helps the student develop her or his understanding of each topic, and the relation of that topic to other topics. Student progress is assessed by a series of multiple-choice tests and written individual & group assignments.

Learning objectives

Students will learn about the nature of cognition and the motivation for studying artificial cognitive systems and they will be introduced to different ways to model cognitive systems. Students will learn about the three paradigms of cognitive science: the cognitivist paradigm, the emergent paradigm, and the hybrid paradigm. They will examine cognitive architectures in some detail, learning about the role of a cognitive architecture, its desirable characteristics, its core cognitive abilities, and the different options when designing one. They will study several representative cognitive architectures at various levels of detail. Students will learn about autonomy, both robotic and biological, and they will be introduced to the concepts of constitutive autonomy, behavioral autonomy, homeostasis, allostasis, and self-organization. They will learn about embodiment and the various hypotheses on the embodiment, including empirical evidence to support these hypotheses. They will study development and learning and how these two processes differ, including motivation, drives, and value systems. Students will learn about the different forms of memory and how these are involved in different types of anticipation, through self-projection, prospection, and internal simulation. They will learn about the different stances taken on knowledge and representation and the symbol grounding problem. Finally, they will learn about social cognition, social interaction, and the relevance of joint action, shared goals, shared intention, and joint attention. In this context, they will also learn about reading intentions, theory of mind, instrumental helping, collaboration, interaction dynamics, and different schools of thought on cognitive development.


After completing this course, students will 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.
  • Distinguish between instrumental helping, cooperation, and collaboration.
  • Explain how social cognition relies on the ability to take perspectives and form a theory of mind.
  • Explain the interplay between joint action, shared goals, shared intention, and joint attention in social cognition.

Content details

  • The nature of cognition: course overview, motivation.
  • Paradigms of cognitive science: cognitivist, emergent, and hybrid
  • Cognitive architectures
  • Autonomy
  • Embodiment
  • Development and learning
  • Memory and prospection
  • Knowledge and representation
  • Social cognition




David Vernon