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In S. Lichtenstein & P. Slovic (Eds.), The Construction of Preference (pp. 397-410).
In this paper, the philosophy of the PP method has been used, but two components have been totally redesigned: a simpler algorithm is used for the construction of preference functions; and the optimizer is replaced by a genetic algorithm that avoids possible local minima problems.
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A critic can argue that the construction of preferences for the combined alternative set {⟨A,0⟩, ⟨C,10⟩, ⟨B,20⟩, ⟨A,30⟩, ⟨C,40⟩, ⟨B,50⟩…} out of preferences over the primary alternative set ({A,B,C}) should not be performed in the straightforward simple way that was indicated in the examples.
Furthermore, preferences appeared stable within and between interviews, suggesting that there was «very little evidence of the construction of preferences».
Finally, it refers to the impact of presentation on individuals' information processing (i.e. their gaining of knowledge, their formulation of risk and benefit perceptions, and their construction of preferences).
Complicating matters is empirical research suggesting that our preferences are subject to such powerful contextual influences that it is better to talk about the construction of coherent preferences than about their derivation from underlying desires (see, e.g., the papers in Lichtenstein and Slovic 2006).
However, we show that the use of preference logic grammars allow construction of a much more powerful and declarative commercial standardizer, and discuss in detail how the use of the non-monotonic construct of preferences leads to improved commercial software.
Aggregate rationality demands the construction of a collective preference over policies that also satisfies the axioms of subjective expected utility theory.
One of the most well-known examples of preference construction is the compromise effect.
The kinetic data determined at each position allow for the construction of the overall sequence preference heat map for LexA Pa.
The current Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidelines explicitly recommend the examination of patients' values and preferences in the construction of clinical practice guidelines [ 25].
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