Titlebook: Scalable Uncertainty Management; 10th International C Steven Schockaert,Pierre Senellart Conference proceedings 2016 Springer International

乐器演奏者

A Belief-Based Approach to Measuring Message Acceptabilitycoming information is associated with an acceptance degree. In particular, such degree may be used as input weight for any possibilistic conditioning operator with uncertain input (i.e., weighted belief revision operator).

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车床

Possibilistic Graphical Models for Uncertainty Modelingations. Thanks to independence relations, they allow a compact representation of complex and uncertain information and they greatly simplify the critical tasks of information elicitation, representation and inference. Many alternative belief graphical models have been proposed to overcome the limits

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积极词汇

愤怒事实

Incremental Preference Elicitation in Multi-attribute Domains for Choice and Ranking with the Borda d with respect to multiple attributes and the individual preferences are unknown. More precisely, assuming that individual preferences are representable by linear multi-attribute utility functions, we propose an incremental elicitation method aiming to determine the Borda winner while minimizing the

seroma

Graphical Models for Preference Representation: An Overviewitate elicitation, exhibit some form of independence, and serve as a basis for solving optimization and dominance queries about choices. The expressiveness of the representation setting and the complexity of answering queries are then central issues for each approach. This paper proposes an extensiv

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Fuzzy Labeling for Abstract Argumentation: An Empirical Evaluationach, we proposed a fuzzy labeling algorithm for computing the (fuzzy) set of acceptable arguments, when the sources of the arguments in the argumentation framework are only partially trusted. The convergence of the algorithm was proved, and the convergence speed was estimated to be linear, as it is

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