Search results for "uncertainty"

showing 10 items of 1010 documents

Recursive and bargaining values

2021

Abstract We introduce two families of values for TU-games: the recursive and bargaining values. Bargaining values are obtained as the equilibrium payoffs of the symmetric non-cooperative bargaining game proposed by Hart and Mas-Colell (1996). We show that bargaining values have a recursive structure in their definition, and we call this property recursiveness. All efficient, linear, and symmetric values that satisfy recursiveness are called recursive values. We generalize the notions of potential, and balanced contributions property, to characterize the family of recursive values. Finally, we show that if a time discount factor is considered in the bargaining model, every bargaining value h…

Computer Science::Computer Science and Game TheoryDiscountingSociologia matemàticaProperty (philosophy)ComputingMilieux_THECOMPUTINGPROFESSIONSociology and Political ScienceGeneral Social SciencesComputingMethodologies_ARTIFICIALINTELLIGENCEEconomia socialComputer Science::Multiagent SystemsComputingMilieux_COMPUTERSANDSOCIETYMatemàtica financeraEconomia Mètodes estadísticsStatistics Probability and UncertaintyValue (mathematics)Mathematical economicsGeneral PsychologyMathematics
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Values of games with probabilistic graphs

1999

Abstract In this paper we consider games with probabilistic graphs. The model we develop is an extension of the model of games with communication restrictions by Myerson (1977) . In the Myerson model each pair of players is joined by a link in the graph if and only if these two players can communicate directly. The current paper considers a more general setting in which each pair of players has some probability of direct communication. The value is defined and characterized in this context. It is a natural extension of the Myerson value and it turns out to be the Shapley value of a modified game.

Computer Science::Computer Science and Game TheorySociology and Political ScienceIf and only ifComputingMilieux_PERSONALCOMPUTINGProbabilistic logicGeneral Social SciencesStatistics Probability and UncertaintyDirect communicationShapley valueMathematical economicsGeneral PsychologyGraphMathematics
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REPEATED GAMES WITH PROBABILISTIC HORIZON

2005

Repeated games with probabilistic horizon are defined as those games where players have a common probability structure over the length of the game's repetition, T. In particular, for each t, they assign a probability pt to the event that "the game ends in period t". In this framework we analyze Generalized Prisoners' Dilemma games in both finite stage and differentiable stage games. Our construction shows that it is possible to reach cooperative equilibria under some conditions on the distribution of the discrete random variable T even if the expected length of the game is finite. More precisely, we completely characterize the existence of sub-game perfect cooperative equilibria in finite s…

Computer Science::Computer Science and Game TheorySociology and Political ScienceSequential gameProbabilistic logicComputingMilieux_PERSONALCOMPUTINGGeneral Social SciencesPrisoner's dilemmaConvergence (routing)Repeated gameApplied mathematicsrepeated games probabilistic horizon cooperationDifferentiable functionStatistics Probability and UncertaintyMathematical economicsRandom variableGeneral PsychologyMathematicsEvent (probability theory)
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Efficient linear fusion of partial estimators

2018

Abstract Many signal processing applications require performing statistical inference on large datasets, where computational and/or memory restrictions become an issue. In this big data setting, computing an exact global centralized estimator is often either unfeasible or impractical. Hence, several authors have considered distributed inference approaches, where the data are divided among multiple workers (cores, machines or a combination of both). The computations are then performed in parallel and the resulting partial estimators are finally combined to approximate the intractable global estimator. In this paper, we focus on the scenario where no communication exists among the workers, de…

Computer scienceBayesian probabilityInferenceAsymptotic distribution02 engineering and technology01 natural sciences010104 statistics & probability[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingArtificial Intelligence0202 electrical engineering electronic engineering information engineeringStatistical inferenceFusion rules0101 mathematicsElectrical and Electronic EngineeringComputingMilieux_MISCELLANEOUSMinimum mean square errorApplied MathematicsConstrained optimizationEstimator020206 networking & telecommunicationsComputational Theory and MathematicsSignal ProcessingComputer Vision and Pattern RecognitionStatistics Probability and Uncertainty[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmDigital Signal Processing
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Temporal Binding in Multisensory and Motor-Sensory Contexts: Toward a Unified Model

2021

Our senses receive a manifold of sensory signals at any given moment in our daily lives. For a coherent and unified representation of information and precise motor control, our brain needs to temporally bind the signals emanating from a common causal event and segregate others. Traditionally, different mechanisms were proposed for the temporal binding phenomenon in multisensory and motor-sensory contexts. This paper reviews the literature on the temporal binding phenomenon in both multisensory and motor-sensory contexts and suggests future research directions for advancing the field. Moreover, by critically evaluating the recent literature, this paper suggests that common computational prin…

Computer scienceMini ReviewEvent (relativity)Sensory system050105 experimental psychologylcsh:RC321-57103 medical and health sciencesBehavioral Neuroscience0302 clinical medicinetemporal bindingPhenomenon0501 psychology and cognitive sciencescausal inferencelcsh:Neurosciences. Biological psychiatry. Neuropsychiatrymotor-sensoryBayesian modelsBiological PsychiatryUncertainty reduction theoryCognitive science05 social sciencesRepresentation (systemics)Motor controlHuman NeuroscienceUnified ModelmultisensoryPsychiatry and Mental healthNeuropsychology and Physiological PsychologyNeurologyCausal inferenceprecision030217 neurology & neurosurgeryFrontiers in Human Neuroscience
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Emulation of 2D Hydrodynamic Flood Simulations at Catchment Scale Using ANN and SVR

2021

Two-dimensional (2D) hydrodynamic models are one of the most widely used tools for flood modeling practices and risk estimation. The 2D models provide accurate results

Computer scienceProcess (engineering)Geography Planning and DevelopmentAquatic ScienceMachine learningcomputer.software_genreBiochemistrysupport vector regressionTD201-500Uncertainty analysisWater Science and TechnologyEmulationArtificial neural networkFlood mythWater supply for domestic and industrial purposesbusiness.industryDimensionality reductionHydraulic engineeringSupport vector machineemulatorsVDP::Teknologi: 500Sample size determinationerror structureArtificial intelligencetraining set sizebusinessTC1-978computerartificial neural networkWater
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Daily streamlow prediction with uncertainty in ephemeral catchments using the GLUE methodology

2009

Abstract The Generalised Likelihood Uncertainty Estimation (GLUE) approach is presented here as a tool for estimating the predictive uncertainty of a rainfall–runoff model. The GLUE methodology allows to recognise the possible equifinality of different parameter sets and assesses the likelihood of a parameters set being acceptable simulator when model predictions are compared to observed field data. The results of the GLUE methodology depend greatly on the choice of the likelihood measure and on the choice of the threshold which determines if a parameters set is behavioural or not. Moreover the sampling size has a strong influence on the uncertainty assessment of the response of a rainfall–…

Computer scienceSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaEquifinalityVariance (accounting)Measure (mathematics)GeophysicsGeochemistry and PetrologySample size determinationStatisticsEconometricsSample varianceSensitivity analysisGLUEPredictive uncertainty Rainfall-Runoff model Generalized Likelehood Uncertainty Estimation Ephemeral catchmentsUncertainty analysis
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Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)

2017

International audience; This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the pred…

Computer sciencecomputer.internet_protocol02 engineering and technologycomputer.software_genreIndustrial and Manufacturing EngineeringArticleSet (abstract data type)[SPI]Engineering Sciences [physics]Kriging020204 information systems0202 electrical engineering electronic engineering information engineeringUncertainty quantificationRepresentation (mathematics)predictive model markup language (PMML)Probabilistic logicdata miningPredictive analyticsXMLComputer Science Applicationspredictive analyticsControl and Systems EngineeringPredictive Model Markup Languagestandards020201 artificial intelligence & image processingData miningcomputerXMLGaussian process regression
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Automated Uncertainty Quantification Through Information Fusion in Manufacturing Processes

2017

International audience; Evaluation of key performance indicators (KPIs) such as energy consumption is essential for decision-making during the design and operation of smart manufacturing systems. The measurements of KPIs are strongly affected by several uncertainty sources such as input material uncertainty, the inherent variability in the manufacturing process, model uncertainty, and the uncertainty in the sensor measurements of operational data. A comprehensive understanding of the uncertainty sources and their effect on the KPIs is required to make the manufacturing processes more efficient. Towards this objective, this paper proposed an automated methodology to generate a hierarchical B…

Computer scienceinjection molding02 engineering and technologycomputer.software_genreIndustrial and Manufacturing Engineering[SPI]Engineering Sciences [physics]GME0202 electrical engineering electronic engineering information engineeringUncertainty quantificationuncertaintyautomationhierarchicalbusiness.industryBayesian network020207 software engineeringmeta-modelAutomationComputer Science ApplicationsMetamodelingInformation fusionBayesian networkControl and Systems Engineeringsemantic020201 artificial intelligence & image processingData miningbusinesscomputer
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Measurement of Simplified Single- And Three-Phase Parameters for Harmonic Emission Assessment Based on IEEE 1459-2010

2021

This article investigates the feasibility of using a simplified approach, based on the measurement of power ratio parameters, for harmonic emissions assessment at the point of common coupling (PCC). The proposed approach comes from the common concept of power factor correction and the definitions of the IEEE Std. 1459-2010, where line utilization and harmonic pollution levels are evaluated by means of ratios between the power quantities of the apparent power decomposition. In addition to the IEEE Std. 1459–2010 indicators, in this article, the behavior is studied of additional parameters that are conceptually similar to those defined by the IEEE Std. 1459-2010. The suitability of such param…

Computer sciencepower measurement02 engineering and technologyPower factorHarmonic distortionlaw.inventionHarmonic analysisElectric power systemControl theorylawpower definitions0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringInstrumentationuncertainty analysisIEEE Std. 1459-2010020208 electrical & electronic engineeringharmonic emissionAC powerpower qualityPower (physics)CapacitorThree-phaseHarmonicharmonic analysisparameter estimationSettore ING-INF/07 - Misure Elettriche E Elettroniche
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