Titlebook: Scalable Uncertainty Management; 11th International C Serafín Moral,Olivier Pivert,Nicolás Marín Conference proceedings 2017 Springer Inter

Mortal

Reasons and Means to Model Preferences as Incompletenary relation. Much has been written however on different models of preferences. We review some of the reasons that have been put forward to justify more complex modeling, and review some of the techniques that have been proposed to obtain models of such preferences.

调味品

Fuzzy Description Logics – A Survey the Fuzzy Set Theory of Zadeh [.]. Their purpose is to model vagueness or imprecision in the real world, by introducing new . as additional shades of gray between the Boolean . and .. For example, one can express the distinction between a person . having a . or a . as the degree of truth of the log

Middle-Ear

Using k-Specificity for the Management of Count Restrictions in Flexible Queryingll-known measures of specificity. This has been done, for example, to be able to measure the level of uncertainty associated with the fuzzy set or, also, to be able to determine the discriminatory power of the property associated with the fuzzy set in a given context. This concept was extended to th

侵略主义

恫吓

领袖气质

-Nearest Neighbour Classification for Interval-Valued Data we adopt an optimistic approach to replace the ill-known values, that requires to compute sets of possible and necessary neighbours of an instance. We provide an easy way to compute such sets, as well as the decision rule that follows from them. Our approach is then compared to a simple imputation

LUDE

Estimating Conditional Probabilities by Mixtures of Low Order Conditional Distributionsparameters increases in an exponential way with the number of conditional variables. Some models, such as noisy-or gates make assumptions about the relationships between the variables that assume that the number of parameters is linear. However, there are cases in which these hypothesis do not make

中和

Closed-Form Solutions in Learning Probabilistic Logic Programs by Exact Score Maximizationk learning. Specifically, we focus on score-based learning and on exact maximum likelihood computations. Our main contribution is to show that by restricting any rule body to contain at most two literals, most needed optimization steps can be solved exactly. We describe experiments indicating that o

玩笑

Fault Tolerant Direct NAT Structure Extraction from Pairwise Causal Interaction Patternsyesian networks (BNs). A CPT may be directly expressed as a NAT model or compressed into a NAT model. Once CPTs are NAT-modeled, efficiency of BN inference (both space and time) can be significantly improved. The most important operation in NAT modeling CPTs is extracting NAT structures from interac

肥料

The Altruistic Robot: Do What I Want, Not Just What I Sayments. To escape the requirement for exhaustive instruction and stipulated preference ordering, a robot’s operation must involve choices between alternative actions, guided by goals. We describe a robot that learns these goals from humans by considering the timeliness and context of instructions and