Enactive Artificial IntelligenceFDA162, 2004VT
No of lectures
8 (16 hours)
Graduate and D-level students in computer science or applied cognitive science.
The course was last given
To explore, understand, and model key issues of “enactive cognitive AI”.
Programming experience or background in cognitive science.
The course is organized as a series of design sessions, discussions, and small, weekly “deliverables.” The course will meet once a week for 8 weeks; each week will be divided between design sessions – and “status” presentations/discussions of student projects. The course will also meet at the end of the quarter for final presentations of student projects.
This is a project-oriented course for cognitive scientists interested in
modeling cognition in terms of “enactive” mechanisms. Enactive AI
is an outgrowth of "constructivist AI" and has its roots in developmental
psychology, constructivism, and self-organizing models of biology. This
approach to AI differs from others in that the emphasis is not on the
“recovery” of (pre-given) features of the world, but rather how
autonomous systems can generate viable “life-worlds” through their
activity. Students will be asked to form teams and develop working
implementations of key ideas from Enactive AI.
The course will explore relevant concepts and mechanisms from Enactive AI, including: development psychology; autopoiesis; self-organization and self-maintenance; cellular automata; "situated action"; and subsumption architectures.
Readings will be short and distributed as needed, and may include work by Jean Piaget, Jakob von Uexkull, Marvin Minsky, Seymour Papert, Humberto Maturana, Francisco Varela, Eleanor Rosch, Susan Oyama, Gary Drescher, Barry McMullin, and Rodney Brooks. Note that "readings" will also include using/studying existing simulations.
Active participation, weekly deliverables, and a public presentation of a completed final project.
Course size is limited to 20 participants. Course language is English. Note: for this course we will try to create a balance between students who want to build their own simulations -- and students who want to write papers about the course themes. In both cases, the emphasis in this course is on “completing a final project,” so students are expected to be comfortable with either a) programming, or b) writing a publication-quality paper. Students who apply for the course should send an email indicating which kind of activity/project they would like to do. (For implementations, students are free to choose any programming language -- Java, Scheme, Lisp, etc. -- but a final project must work "for real" in some significant sense. It cannot be a "mock up" or "Director presentation.")
Page responsible: Director of Graduate Studies
Last updated: 2012-05-03