Abstract
In order to build autonomous robots that can carry
out useful work in unstructured environments new
approaches have been developed to building
intelligent systems. The relationship to traditional
academic robotics and traditional artificial intelligence
is examined. In the new approaches a tight coupling
of sensing to action produces architectures for
intelligence that are networks of simple
computational elements which are quite broad, but
not very deep. Recent work within this approach has
demonstrated the use of representations, expectations,
plans, goals, and learning, but without resorting to
the traditional uses, of central, abstractly manipulable
or symbolic representations. Perception within these
systems is often an active process, and the dynamics
of the interactions with the world are extremely
important. The question of how to evaluate and
compare the new to traditional work still provokes
vigorous discussion.
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