Search results for "Divergence-from-randomness model"

showing 4 items of 4 documents

A probabilistic estimation and prediction technique for dynamic continuous social science models: The evolution of the attitude of the Basque Country…

2015

In this paper, a computational technique to deal with uncertainty in dynamic continuous models in Social Sciences is presented.Considering data from surveys,the method consists of determining the probability distribution of the survey output and this allows to sample data and fit the model to the sampled data using a goodness-of-fit criterion based the χ2-test. Taking the fitted parameters that were not rejected by the χ2-test, substituting them into the model and computing their outputs, 95% confidence intervals in each time instant capturing the uncertainty of the survey data (probabilistic estimation) is built. Using the same set of obtained model parameters, a prediction over …

FOS: Computer and information sciencesAttitude dynamicsProbabilistic predictionComputer sciencePopulationDivergence-from-randomness modelSample (statistics)computer.software_genreMachine Learning (cs.LG)Probabilistic estimationSocial scienceeducationProbabilistic relevance modeleducation.field_of_studyApplied MathematicsProbabilistic logicConfidence intervalComputer Science - LearningComputational MathematicsSocial dynamic modelsProbability distributionSurvey data collectionData miningMATEMATICA APLICADAcomputerApplied Mathematics and Computation
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Probabilistic Logic under Coherence: Complexity and Algorithms

2005

In previous work [V. Biazzo, A. Gilio, T. Lukasiewicz and G. Sanfilippo, Probabilistic logic under coherence, model-theoretic probabilistic logic, and default reasoning in System P, Journal of Applied Non-Classical Logics 12(2) (2002) 189---213.], we have explored the relationship between probabilistic reasoning under coherence and model-theoretic probabilistic reasoning. In particular, we have shown that the notions of g-coherence and of g-coherent entailment in probabilistic reasoning under coherence can be expressed by combining notions in model-theoretic probabilistic reasoning with concepts from default reasoning. In this paper, we continue this line of research. Based on the above sem…

conditional probability assessmentSettore MAT/06 - Probabilita' E Statistica MatematicaDivergence-from-randomness modelalgorithmsprobabilistic logicConditional probability assessments; probabilistic logic; g-coherence; g-coherent entailment; complexity and algorithms.Artificial IntelligenceProbabilistic logic networkprobabilistic logic under coherenceConditional probability assessmentsProbabilistic analysis of algorithmsNon-monotonic logicconditional constraintMathematicsg-coherent entailmentConditional probability assessments probabilistic logic g-coherence g-coherent entailment complexity and algorithms.Reasoning systemcomputational complexitymodel-theoretic probabilistic logicApplied Mathematicscomplexity and algorithmsProbabilistic logiclogical constraintProbabilistic argumentationg-coherenceconditional probability assessment logical constraint conditional constraint probabilistic logic under coherence model-theoretic probabilistic logic g-coherence g-coherent entailment computational complexity algorithmsProbabilistic CTLalgorithms; computational complexity; conditional constraint; conditional probability assessment; g-coherence; g-coherent entailment; logical constraint; model-theoretic probabilistic logic; probabilistic logic under coherenceAlgorithmAnnals of Mathematics and Artificial Intelligence
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Communication complexity in a 3-computer model

1996

It is proved that the probabilistic communication complexity of the identity function in a 3-computer model isO(√n).

Theoretical computer scienceGeneral Computer ScienceComputer scienceApplied MathematicsDivergence-from-randomness modelProbabilistic logicComputer Science ApplicationsProbabilistic CTLWorst-case complexityIdentity functionProbabilistic analysis of algorithmsPhysics::Chemical PhysicsCommunication complexityDecision tree modelAlgorithmica
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Probabilistic Logic under Coherence, Model-Theoretic Probabilistic Logic, and Default Reasoning

2001

We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore the relationship between coherence-based and model-theoretic probabilistic logic. Interestingly, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Crucially, we even show that probabilistic reasoning under coherence is a probabilistic generalization of default reasoning in system P. That is, we provide a new probabilistic semantics for system P, which is neither based on infinitesimal probabilities nor on atomic-bound (or also big-stepped) probabil…

Deductive reasoningSettore MAT/06 - Probabilita' E Statistica MatematicaKnowledge representation and reasoningComputer scienceDefault logicDivergence-from-randomness modelLogic modelcomputer.software_genreLogical consequenceProbabilistic logic networkConditional probability assessments conditional constraints probabilistic logic under coherence model-theoretic probabilistic logic g-coherence g-coherent entailment default reasoning from conditional knowledge bases System P conditional objectsprobabilistic logic under coherenceNon-monotonic logicProbabilistic relevance modeldefault reasoningmodel-theoretic probabilistic logicbusiness.industryProbabilistic logicProbabilistic argumentationExpert systemg-coherencesystem pProbabilistic CTLArtificial intelligencebusinesscomputerdefault reasoning; g-coherence; model-theoretic probabilistic logic; probabilistic logic under coherence; system p
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