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Adaptive Reasoning for Real-world Problems - A Schema-based Approach (Hardcover)
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Adaptive Reasoning for Real-world Problems - A Schema-based Approach (Hardcover)
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This book describes a method for building real-world problem
solving systems such as medical diagnostic procedures and
intelligent controllers for autonomous underwater vehicles (AUVs)
and other robots. The approach taken is different from other work
reported in the artificial intelligence literature in several
respects:
* It defines "schema-based reasoning, " in which schemas --
explicitly declared packets of related knowledge -- are used to
control not only the reasoner's planning, but also all other facets
of its behavior.
* It is a kind of reactive reasoning that the author calls
"adaptive problem solving" -- the reasoner maintains commitments to
future goals but is able to change its focus of attention as the
problem-solving situation requires.
* It is a "context-sensitive" reasoning method. Every decision it
makes relies on the use of contextual knowledge to be appropriate
for the current problem-solving situation. Furthermore, context is
represented explicitly; by always keeping a current representation
of the context in mind, the reasoner's behavior is automatically
sensitive to the context with very little work needed per decision.
* Schema-based reasoning -- a generalization of case-based
reasoning -- extends the usual idea of case-based reasoning to
encompass all aspects of the reasoner's behavior, and it extends it
to make use of generalized "cases" (i.e., schemas) rather than
particular cases, thus saving effort needed to transfer knowledge
from an old case to a new situation.
Though the work originated in the domain of medical diagnostic
problem solving, treating diagnosis as a planning task, it is even
more appropriate for controlling autonomous systems. The author is
currently extending the approach by creating a robust controller
for long-range autonomous underwater vehicles that will be used to
carry out ocean science missions.
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