Difference between revisions of "1993 FromConditionalOughtstoQualitat"

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* 14. Poole, D., "Decision-theoretic Defaults," <i>9th Canadian Conference on AI</i>, Vancouver, Canada, 190- 197, May 1992.
 
* 14. Poole, D., "Decision-theoretic Defaults," <i>9th Canadian Conference on AI</i>, Vancouver, Canada, 190- 197, May 1992.
 
* 15. R. D. Shachter, Evaluating Influence Diagrams, Operations Research, v.34 n.6, p.871-882, Nov.-Dec. 1986
 
* 15. R. D. Shachter, Evaluating Influence Diagrams, Operations Research, v.34 n.6, p.871-882, Nov.-Dec. 1986
* 16. Yoav Shoham, Reasoning About Change: Time and Causation from the Standpoint of Artificial Intelligence, MIT Press, Cambridge, MA, 1988
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* 16. [[Yoav Shoham]], Reasoning About Change: Time and Causation from the Standpoint of Artificial Intelligence, MIT Press, Cambridge, MA, 1988
 
* 17. Spohn, W., "Ordinal Conditional Functions: A Dynamic Theory of Epistemic States," in W.L. Harper and B. Skyrms (Eds.), <i>Causation in Decision, Belief Change, and Statistics</i>, D. Reidel, Dordrecht, Holland, 105-134, 1988.
 
* 17. Spohn, W., "Ordinal Conditional Functions: A Dynamic Theory of Epistemic States," in W.L. Harper and B. Skyrms (Eds.), <i>Causation in Decision, Belief Change, and Statistics</i>, D. Reidel, Dordrecht, Holland, 105-134, 1988.
 
* 18. Stalnaker, R., "Letter to David Lewis" in Harper, L., Stalnaker, R., and Pearce, G. (Eds.), <i>Ifs</i>, D. Reidel Dordrecht, Holland, 151-152, 1980.
 
* 18. Stalnaker, R., "Letter to David Lewis" in Harper, L., Stalnaker, R., and Pearce, G. (Eds.), <i>Ifs</i>, D. Reidel Dordrecht, Holland, 151-152, 1980.

Revision as of 14:24, 13 August 2019

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Abstract

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.

2. INFINITESIMAL PROBABILITIES, RANKING FUNCTIONS, CAUSAL NETWORKS, AND ACTIONS

1. (Ranking Functions).

Let [math]\Omega[/math] be a set of worlds, each world [math]w \in \Omega[/math] being a truth-value assignment to a finite set of atomic variables [math](X_1, X_2, … ,X_n)[/math] which in this paper we assume to be hi-valued, namely, [math]X_i \in {true, false}[/math]. A belief ranking function [math]\kappa(w)[/math] is an assignment of non-negative integers to the elements of [math]\Omega[/math] such that [math]\kappa(w) = 0[/math] for at least one [math]w \in \Omega[/math]. Intuitively, [math]\kappa(w)[/math] represents the degree of surprise associated with finding a world [math]w[/math] realized, and worlds assigned [math]\kappa = 0[/math] are considered serious possibilities. [math]\kappa(w)[/math] can be considered an order-of-magnitude approximation of a probability function [math]P(w)[/math] by writing [math]P(w)[/math] as a polynomial of some small quantity f and taking the most significant term of that polynomial, i.e., ...

References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
1993 FromConditionalOughtstoQualitatJudea PearlFrom Conditional Oughts to Qualitative Decision Theory1993
AuthorJudea Pearl +
titleFrom Conditional Oughts to Qualitative Decision Theory +
year1993 +