Author: "Pittarelli, Michael" / Language: english - Searchworks@Jio Institute Digital Library Search Results

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Author: Pittarelli, Michael
Subjects: FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence
Abstract: Measures of uncertainty and divergence are introduced for interval-valued probability distributions and are shown to have desirable mathematical properties. A maximum uncertainty inference procedure for marginal interval distributions is presented. A technique for reconstruction of interval distributions from projections is developed based on this inference procedure, Appears in Proceedings of the Fifth Conference on Uncertainty in Artificial Intelligence (UAI1989)
Published: 2013

Author: Pittarelli, Michael
Subjects: LOGIC, PROBABILITY theory, SEMANTICS, REASONING, SENTENCES (Grammar), INTELLECT
Abstract: The article discusses about "probabilistic logic" which is typically used to refer to systems of logic that permit the attachment of probabilities to the premises and the conclusion of an argument. Systems of probabilistic logic vary with respect to how the uncertainty associated with the premises of an argument is propagated to the conclusion. The worlds in a given set are equivalent with respect to the truth values of the sentences. The sets of possible worlds are mutually exclusive and exhaustive. Nilsson's method for identifying the sets of possible worlds which involves constructing a semantic tree is discussed.
Published: 1999

Author: Pittarelli, Michael
Subjects: DATABASES, PROBABILITY theory, STATISTICAL correlation, RELATIONAL databases, DECISION making, INFORMATION storage & retrieval systems
Abstract: A probabilistic database is defined in a previous article [R. Cavallo and M. Pittarelli, Proc. 13th Int. Conf. on Very Large Databases (VLDB); 1987; see Ref. 9J as a collection of probability distributions over Cartesian products of finite variable domains. The concept is extended here to accommodate interval-valued probabilities. Algebraic operations for both real- and interval-valued probabilities databases analogous to those for relational databases are defined. Techniques for making inferences regarding joint distributions on subsets of the variables over which a probabilistic database is defined are developed. `These are illustrated through application to a problem of decision analysis under partial uncertainty. Connections between the probabilistic database formalism and other forms of data representation are discussed. [ABSTRACT FROM AUTHOR]
Published: 1990
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