Langlotz, C. P., Shortliffe, E. H., and Fagan, L. M., 1986. Using decision theory to justify heuristics, Proc. Fifth National Conference on Artificial Intelligence, 215-219.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....be used descriptively to identify the conditions under which one inference technique is better than another, or to explain why a technique is good or bad in specific circumstances. In particular, the theory may be applied in AI to provide a formal analysis of informally developed techniques (e.g. (Langlotz et al. 1986)) It also permits comparison of AI theories with formal psychological theories. Normatively construed, however, logical and economic rationality provide different conceptions of how one should think, and logic has also overshadowed economic rationality as a normative theory of thinking. By their ....

Langlotz, C. P., Shortliffe, E. H., and Fagan, L. M. 1986. Using decision theory to justify heuristics. In Proceedings of the National Conference on Artificial Intelligence, pp. 215-- 219.

....between the possible inefficiencies resulting from using approximate values of expected utilities and the value of time needed for a more accurate model. A very attractive method of dealing with the complexities of an all encompassing formalism is compilation. It has been advocated before in [12, 15, 13] that decision theory can be made to justify heuristic rules of behavior under uncertainty and be compiled in a number of different ways into condition action rules, action utility rules, and so on. These suggestions are quite applicable to the formalisms of multiagent interaction and ....

C. P. Langlotz, E. Shortlife, and L. M. Fagan. Using decision theory to justify heuristics. In Proceedings of the National Conference on Artificial Intelligence, pages 215--219, Philadelphia, Pennsylvania, August 1986.

....be assimilated since individual default rules may be evaluated as individual assumptions. This view of adoption of default rules has been urged by [Doyle 1983a] and more recently by [Shoham 1987] By taking utility to be a simple function of application costs and speedup benefits, Smith 1985] [Langlotz, et al. 1986], and [Minton 1988] have applied rational evaluation to concrete cases of selection of inference rules. Such economic calculations may be made either at the time the information is needed or, as in the default rules prominent in inheritance systems and reason maintenance, in advance. When made ....

Langlotz, C. P., Shortliffe, E. H., and Fagan, L. M., 1986. Using decision theory to justify heuristics, Proc. Fifth National Conference on Artificial Intelligence, 215-219.

....the importance of utility considerations in default reasoning. Similar intuitions were mentioned in many of the early works on default and defeasible reasoning (e.g. McCarthy, 1980 ] In particular, several works use expected utility consideration in evaluation of heuristic rules (e.g. Langlotz et al. 1986 ] More recently, decision theoretic foundations for defaults were advocated by Shoham (1987) and Doyle (1989) Doyle provides a formal analysis of Pascal s wager and shows how an assumption (the existence of God) can be justified in terms of utility. Finally, Poole (1992) examined a ....

C. P. Langlotz, E. H. Shortliffe, and L. M. Fagan. Using decision theory to justify heuristics. In Proc. National Conference on Artificial Intelligence (AAAI '86), pp. 215--219. 1986.

....paper, we use the ideas of decision theory to measure the value of plans. More precisely, we postulate an underlying probabilistic model for the world, and define the value of the plan in terms of its expected utility. A similar approach has also been used in the context of knowledge compilation [LSF86, Hor87, HBH89]. For example, in the previous example, we assume that there is some probability that the car will fail to start, and use that probability to assign expected utilities to various plans that involve turning the key in the ignition. We can then compare the expected utility of the plan chosen by the ....

C. P. Langlotz, E. H. Shortliffe, and L. M. Fagan. Using decision theory to justify heuristics. In Proc. National Conference on Artificial Intelligence (AAAI '86), pages 215--219, 1986.

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Langlotz, C. P., Shortliffe, E. H., and Fagan, L. M., 1986. Using decision theory to justify heuristics, Proc. Fifth National Conference on Artificial Intelligence, 215-219.

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Langlotz,C., Shortliffe,E., and Fagan,L.: "Using Decision Theory to Justify Heuristics"; Proc. AAAI-86, pp.215--219. = certainty factors, Bayes rule, and probability.

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