Decision making with consonant belief functions: Discrepancy resulting with the probability transformation method used
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چکیده
منابع مشابه
Decision Making with Consonant Belief Functions: Discrepancy Resulting with the Probability Transformation Method Used
Dempster−Shafer belief function theory can address a wider class of uncertainty than the standard probability theory does, and this fact appeals the researchers in operations research society for potential application areas. However, the lack of a decision theory of belief functions gives rise to the need to use the probability transformation methods for decision making. For representation of s...
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This paper studies decision making for Wal ley's partially consonant belief functions (pcb ) . In a pcb, the set of foci are par titioned. Within each partition, foci are nested. The pcb class includes probability and possibility functions as extreme cases. We adopt an axiomatic system, similar in spirit to von Neumann and Morgenstern's ax ioms for preferences leading to the linear util ity...
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A primary motivation for reasoning under uncertainty is to derive decisions in the face of inconclusive evi dence. However, Shafer's theory of belief functions, which explicitly represents the underconstrained na ture of many reasoning problems, lacks a formal pro cedure for making decisions. Clearly, when sufficient information is not available, no theory can prescribe actions without makin...
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Partially consonant belief functions (pcb), studied by P. Walley, are the only class of Dempster-Shafer belief functions that are consistent with the likelihood principle of statistics. Structurally, the set of foci of a pcb is partitioned into non-overlapping groups and within each group, foci are nested. The pcb class includes both probability function and Zadeh’s possibility function as spec...
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In modeling Multi-Criteria Decision Making (MCDM) problem, we usually assume that the decision maker is able to elicitate his preferences with precision and without difficulty. However, in many situations, the expert is unable to provide his assessment with certainty or he is unwilling to quantify his preferences. To deal with such situations, a new MCDM model under uncertainty is introduced. I...
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ژورنال
عنوان ژورنال: YUJOR
سال: 2014
ISSN: 0354-0243,1820-743X
DOI: 10.2298/yjor140401033c