防水
发表于 2025-3-25 07:19:03
Some Mathematical Tools for Decision Making under Partial Knowledgel tools for analysis are considered. These include subjective probabilities, lower probabilities, the Choquet integral, random sets, measure-free representation of conditionals (rules), and rule-based procedures.
acolyte
发表于 2025-3-25 07:43:32
From Bayesian Networks to Causal Networksing causal information for decision analysis. We show how complex information about external interventions can be organized and represented graphically and, conversely, how the graphical representation can be used to facilitate quantitative predictions of the effects of interventions..We first revie
NICE
发表于 2025-3-25 14:17:56
A Hyperstructure of Conditional Events for Artificial Intelligenceacterizations of logical dependence for conditional events to decide what essential information about a problem is..Beginning over the definition of conditional events as a three valued logic entity, we represent, in this paper, a family of conditional events as the result of a multivalued operation
生命
发表于 2025-3-25 17:32:50
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凹室
发表于 2025-3-25 20:32:37
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curettage
发表于 2025-3-26 03:28:31
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certain
发表于 2025-3-26 04:50:16
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Volatile-Oils
发表于 2025-3-26 11:50:23
Inconsistent Knowledge Integration in a Probabilistic Model. al., 1992). Analogously, oligodimensional distributions (i.e. distributions of dimensionality cca 1 – 5) can be considered partial knowledge. Within this framework the knowledge integration process corresponds to constructing a multidimensional distribution with the given marginals. For this purpo
轻弹
发表于 2025-3-26 13:08:13
Conditional and Comparative Probabilities in Artificial Intelligenceal Intelligence. Coherent conditional probabilities are used: this makes it possible to work with sets of events which are not necessarily ‘structured’, but which arise in a natural way from the real problems being examined. Starting from some known relations comparing events by means of conditional
有限
发表于 2025-3-26 20:27:27
ility of expert systems. The various issues dealt with in this volume concern many different approaches to the handling of partial knowledge and to the ensuing methods for reasoning and decision making under uncertainty, as applied to problems in artificial intelligence. The volume is composed of th