Abstract
Mobile robots with dextrous hands and sophisticated
sensory systems will require intelligent, knowledge-based,
expert controllers. In this paper we develop a design for a
robot controller which can acquire task knowledge as it interacts
in the world with its human users. The design is based on four
reasonable assumptions which lead us to a theoretical
framework for robot learning systems. The framework is called a multiple
context learning system. It is a production system with multiple
templates for forming productions as the system interacts with the world.
The paper discusses elaborations of the framework and experimental tests of
the system.
Notes
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