Uncertainty in Artificial Intelligence
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From Conditional Oughts to Qualitative Decision Theory
Judea Pearl
The primary theme of this investigation is a decision theoretic account of conditional ought statements (e.g., "You ought to do A, if C") that rectifies glaring deficiencies in classical deontic logic. The resulting account forms a sound basis for qualitative decision theory, thus providing a framework for qualitative planning under uncertainty. In particular, we show that adding causal relationships (in the form of a single graph) as part of an epistemic state is sufficient to facilitate the analysis of action sequences, their consequences, their interaction with observations, their expected utilities and, hence, the synthesis of plans and strategies under uncertainty.
Pages: 12-20
PS Link:
PDF Link: /papers/93/p12-pearl.pdf
AUTHOR = "Judea Pearl ",
TITLE = "From Conditional Oughts to Qualitative Decision Theory",
BOOKTITLE = "Proceedings of the Ninth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-93)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1993",
PAGES = "12--20"

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