Programming with Agents:
New metaphors for thinking about computation
Michael David Travers
Submitted to the Program in
Media Arts and Sciences,
School of Architecture and Planning on May 3, 1996
in partial fulfillment of the requirements for the degree of
Doctor of Philosophy at the
Massachusetts Institute of Technology
Abstract:
Computer programming environments for learning should make it easy to create
worlds of responsive and autonomous objects, such as video games or simulations
of animal behavior. But building such worlds remains difficult, partly because
the models and metaphors underlying traditional programming languages are
not particularly suited to the task. This dissertation investigates new
metaphors, environments, and languages that make possible new ways to create
programs -- and, more broadly, new ways to think about programs. In particular,
it introduces the idea of programming with "agents" as a means
to help people create worlds involving responsive, interacting objects.
In this context, an agent is a simple mechanism intended to be understood
through anthropomorphic metaphors and endowed with certain lifelike properties
such as autonomy, purposefulness, and emotional state. Complex behavior
is achieved by combining simple agents into more complex structures. While
the agent metaphor enables new ways of thinking about programming, it also
raises new problems such as inter-agent conflict and new tasks such as making
the activity of a complex society of agents understandable to the user.
To explore these ideas, a visual programming environment called LiveWorld
has been developed that supports the creation of agent-based models, along
with a series of agent languages that operate in this world.
Thesis Supervisors:
Marvin Minsky
Professor of Electrical Engineering & Computer Science
Toshiba Professor of Media Arts & Sciences
Mitchel Resnick
Assistant Professor of Media Arts & Sciences
Fukutake Career Development Professor of Research in Education
Available online:
HTML format.
PDF format (1.1mb, 206 pages). Acrobat reader is required.
Michael Travers / MIT
Media Lab / mt@media.mit.edu