A Framework for Planning under Uncertainty
Jonathan King Tash
Group in Logic and the Methodology of Science
University of California
Berkeley, California 94720
tash@cs.berkeley.edu
Abstract
This work presents a planning paradigm which integrates the flexibility and
clear semantics of decision theory with search procedures providing many of
the efficiency properties of classical heuristic planning methods. We
define plans in a manner similar to the classical paradigm but extended to
represent nondeterministic actions, using utilities to represent goals. We
then outline a search procedure for good plans which is guided by decision
theory, and discuss knowledge representation issues from the point of view
of improving decisions. This paradigm puts plan choice on the same level
as action choice, and has as emergent properties variants of desirable
features of more classical planners, such as abstraction and reactivity.
Appeared in
1993 AAAI Spring Symposium Technical Report on Foundations of
Automatic Planning: The Classical Approach and Beyond, pp. 137-141
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