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Transcript
Behavior-Based Artificial
Intelligence
Pattie Maes
MIT Media-Laboratory
Presentation by:
Derak Berreyesa
UNR, CS Department
Abstract
Uses behavior-based artificial
intelligence as a new approach to
studying intelligence.
Deals with autonomous systems that
must deal with changing goals in an
unpredictable environment.
Two approaches to AI
Knowledge-Based AI
Knowledge based systems have prior
knowledge about the environment and
there task.
Behavior-Based AI
React to there changing environment
and goals
They “behave” in a problem domain.
Knowledge-Based AI
Isolated and advanced competences.
“Closed” systems that only connect to the
user, not the environment.
Deal with one problem at a time.
Uses static knowledge structures to solve
problems.
Don’t have to adapt to changing situations.
When creating an autonomous system a
computer takes over as the user.
Behavior-Based AI
Has several competences but they are not as
intelligent as isolated competence would be.
“Open” system that has little time to react.
Decides itself what the problem to be solved
next is.
Relies more on producing behavior than
knowledge.
Emphasis on adaptation.
Behavior-Based problem
solving
A system that can learn has to rely less
on planning.
Environment can be exploited.
Learn over time.
Interacts in society to help accomplish
tasks.
A Mobile Robot
Knowledge-Based would create a model
of the office to update as often as
possible. It would include the location
of the robot itself and the location of
certain objects.
Behavior-Based would have specific
modules for wall following, going
through doors, etc.
An Interface Agent
Knowledge-Based will learn all it can
about what it should prompt the user
for and/or try to do when the user does
something.
Behavior-Based will have a each
separate module try to learn about it’s
own specialized task.
Conclusion
Behavior-Based AI have proven to be
very efficient so far.
More fundamental research needs to be
done.
A better understanding of the
underlying principles.