Craig Boutilier
Department of Computer Science
University of British Columbia
Vancouver, BC, CANADA, V6T 1Z4
email: cebly@cs.ubc.ca
Abstract
We present a logic for representing and reasoning with qualitative
statements of preference and normality and describe how these may
interact in decision making under uncertainty. Our aim is to
develop a logical calculus that employs the basic elements of
classical decision theory, namely probabilities, utilities and
actions, but exploits qualitative
information about these elements directly for the
derivation of goals. Preferences and judgements
of normality are captured in a modal/conditional logic, and
a simple model of action is incorporated. Without quantitative
information, decision criteria other than maximum expected utility are
pursued. We describe how techniques for conditional default
reasoning can be used to complete information about both preferences
and normality judgements, and we show how maximin and maximax strategies can
be expressed in our logic.
Appeared KR-94
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