Search results for "Conditional random quantitie"

showing 10 items of 21 documents

Probabilities of conditionals and previsions of iterated conditionals

2019

Abstract We analyze selected iterated conditionals in the framework of conditional random quantities. We point out that it is instructive to examine Lewis's triviality result, which shows the conditions a conditional must satisfy for its probability to be the conditional probability. In our approach, however, we avoid triviality because the import-export principle is invalid. We then analyze an example of reasoning under partial knowledge where, given a conditional if A then C as information, the probability of A should intuitively increase. We explain this intuition by making some implicit background information explicit. We consider several (generalized) iterated conditionals, which allow…

Background informationSettore MAT/06 - Probabilita' E Statistica MatematicaInference02 engineering and technologyConditional probabilities and previsionTheoretical Computer ScienceConditional random quantitieAffirmation of the ConsequentArtificial Intelligence020204 information systemsFOS: Mathematics0202 electrical engineering electronic engineering information engineeringConjoined and iterated conditionalMathematicsIndependence and uncorrelation.Applied MathematicsProbability (math.PR)Conditional probabilityMathematics - LogicTrivialityIterated function020201 artificial intelligence & image processingLogic (math.LO)Mathematical economicsCoherenceSoftwareMathematics - ProbabilityIntuition
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Iterated Conditionals and Characterization of P-Entailment

2021

In this paper we deepen, in the setting of coherence, some results obtained in recent papers on the notion of p-entailment of Adams and its relationship with conjoined and iterated conditionals. We recall that conjoined and iterated conditionals are suitably defined in the framework of conditional random quantities. Given a family \(\mathcal {F}\) of n conditional events \(\{E_{1}|H_{1},\ldots , E_{n}|H_{n}\}\) we denote by \(\mathcal {C}(\mathcal {F})=(E_{1}|H_{1})\wedge \cdots \wedge (E_{n}|H_{n})\) the conjunction of the conditional events in \(\mathcal F\). We introduce the iterated conditional \(\mathcal {C}(\mathcal {F}_{2})|\mathcal {C}(\mathcal {F}_{1})\), where \(\mathcal {F}_{1}\)…

CombinatoricsPhysicsSettore MAT/06 - Probabilita' E Statistica MatematicaCoherence Conditional events Conditional random quantitiesConditional previsions Conjoined conditionals Iterated conditionalsProbabilistic entailment.Iterated functionProduct (mathematics)Characterization (mathematics)
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On general conditional prevision assessments

2009

In this paper we consider general conditional random quantities of the kind $X|Y$, where $X$ and $Y$ are finite discrete random quantities. Then, we introduce the notion of coherence for conditional prevision assessments on finite families of general conditional random quantities. Moreover, we give a compound prevision theorem and we examine the relation between the previsions of $X|Y$ and $Y|X$. Then, we give some results on random gains and, by a suitable alternative theorem, we obtain a characterization of coherence. We also propose an algorithm for the checking of coherence. Finally, we briefly examine the case of imprecise conditional prevision assessments by introducing the notions of…

Conditional random quantities; coherence; conditional prevision assessments; random gain; alternative theorems; algorithms; imprecise assessments; generalized and total coherence.Settore MAT/06 - Probabilita' E Statistica Matematicarandom gainConditional events general conditional random quantitiesgeneral conditional prevision assessments generalized compound prevision theorem generalized Bayes TheoremConditional random quantitiesalgorithmsimprecise assessmentsalternative theoremsgeneralized and total coherencecoherenceconditional prevision assessments
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Conjunction and Disjunction Among Conditional Events

2017

We generalize, in the setting of coherence, the notions of conjunction and disjunction of two conditional events to the case of n conditional events. Given a prevision assessment on the conjunction of two conditional events, we study the set of coherent extensions for the probabilities of the two conditional events. Then, we introduce by a progressive procedure the notions of conjunction and disjunction for n conditional events. Moreover, by defining the negation of conjunction and of disjunction, we show that De Morgan’s Laws still hold. We also show that the associative and commutative properties are satisfied. Finally, we examine in detail the conjunction for a family \(\mathcal F\) of t…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaComputer scienceConditional events · Conditional random quantities · Con- junction · Disjunction · Negation · Quasi conjunction · Coherent previ- sion assessments · Coherent extensions · De Morgan’s Laws02 engineering and technologyCoherence (philosophical gambling strategy)Settore MAT/01 - Logica Matematica01 natural sciencesDe Morgan's lawsConjunction (grammar)Set (abstract data type)010104 statistics & probabilitysymbols.namesakeNegation0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processing0101 mathematicsAlgorithmCommutative propertyAssociative propertyEvent (probability theory)
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Probabilistic entailment and iterated conditionals

2020

In this paper we exploit the notions of conjoined and iterated conditionals, which are defined in the setting of coherence by means of suitable conditional random quantities with values in the interval $[0,1]$. We examine the iterated conditional $(B|K)|(A|H)$, by showing that $A|H$ p-entails $B|K$ if and only if $(B|K)|(A|H) = 1$. Then, we show that a p-consistent family $\mathcal{F}=\{E_1|H_1,E_2|H_2\}$ p-entails a conditional event $E_3|H_3$ if and only if $E_3|H_3=1$, or $(E_3|H_3)|QC(\mathcal{S})=1$ for some nonempty subset $\mathcal{S}$ of $\mathcal{F}$, where $QC(\mathcal{S})$ is the quasi conjunction of the conditional events in $\mathcal{S}$. Then, we examine the inference rules $A…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaIterated functionInterval (graph theory)Settore MAT/01 - Logica MatematicaCoherence Conditional random quantities p-entailment Inference rules.MathematicsStrict conditional
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Conditional Random Quantities and Compounds of Conditionals

2013

In this paper we consider finite conditional random quantities and conditional previsions assessments in the setting of coherence. We use a suitable representation for conditional random quantities; in particular the indicator of a conditional event $E|H$ is looked at as a three-valued quantity with values 1, or 0, or $p$, where $p$ is the probability of $E|H$. We introduce a notion of iterated conditional random quantity of the form $(X|H)|K$ defined as a suitable conditional random quantity, which coincides with $X|HK$ when $H \subseteq K$. Based on a recent paper by S. Kaufmann, we introduce a notion of conjunction of two conditional events and then we analyze it in the setting of cohere…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaLogicImport–Export principleProbability (math.PR)Probabilistic logicConjunctionOf the formSettore M-FIL/02 - Logica E Filosofia Della ScienzaCoherence (philosophical gambling strategy)Conditional random quantitieConjunction (grammar)Lower/upper prevision boundsHistory and Philosophy of ScienceNegationIterated functionIterated conditioningFOS: MathematicsConditional eventRepresentation (mathematics)CoherenceDisjunctionMathematics - ProbabilityMathematicsEvent (probability theory)
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Generalized probabilistic modus ponens

2017

Modus ponens (from A and “if A then C” infer C) is one of the most basic inference rules. The probabilistic modus ponens allows for managing uncertainty by transmitting assigned uncertainties from the premises to the conclusion (i.e., from P(A) and P(C|A) infer P(C)). In this paper, we generalize the probabilistic modus ponens by replacing A by the conditional event A|H. The resulting inference rule involves iterated conditionals (formalized by conditional random quantities) and propagates previsions from the premises to the conclusion. Interestingly, the propagation rules for the lower and the upper bounds on the conclusion of the generalized probabilistic modus ponens coincide with the re…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaProbabilistic logicConjoined conditionalPrevision0102 computer and information sciences02 engineering and technologyCoherence (philosophical gambling strategy)Settore MAT/01 - Logica MatematicaModus ponen01 natural sciencesConditional random quantitieTheoretical Computer ScienceModus ponendo tollens010201 computation theory & mathematicsIterated functionComputer Science0202 electrical engineering electronic engineering information engineeringIterated conditional020201 artificial intelligence & image processingRule of inferenceModus ponensCoherenceEvent (probability theory)Mathematics
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Conditional Random Quantities and Iterated Conditioning in the Setting of Coherence

2013

We consider conditional random quantities (c.r.q.’s) in the setting of coherence. Given a numerical r.q. X and a non impossible event H, based on betting scheme we represent the c.r.q. X|H as the unconditional r.q. XH + μH c , where μ is the prevision assessed for X|H. We develop some elements for an algebra of c.r.q.’s, by giving a condition under which two c.r.q.’s X|H and Y|K coincide. We show that X|HK coincides with a suitable c.r.q. Y|K and we apply this representation to Bayesian updating of probabilities, by also deepening some aspects of Bayes’ formula. Then, we introduce a notion of iterated c.r.q. (X|H)|K, by analyzing its relationship with X|HK. Our notion of iterated conditiona…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaSettore INF/01 - Informaticaconditional random quantitiesCoherence (statistics)Bayesian inferencebayesian updatingcoherenceCombinatoricsconditional previsionsBayes' theoremIterated functionbayesian updating; conditional random quantities; betting scheme; conditional previsions; coherence; iterated conditioning; iterated conditioning.Coherence betting scheme conditional random quantities conditional previsions Bayesian updating iterated conditioning.Scheme (mathematics)iterated conditioningConditioningRepresentation (mathematics)betting schemeEvent (probability theory)Mathematics
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Generalized Logical Operations among Conditional Events

2018

We generalize, by a progressive procedure, the notions of conjunction and disjunction of two conditional events to the case of n conditional events. In our coherence-based approach, conjunctions and disjunctions are suitable conditional random quantities. We define the notion of negation, by verifying De Morgan’s Laws. We also show that conjunction and disjunction satisfy the associative and commutative properties, and a monotonicity property. Then, we give some results on coherence of prevision assessments for some families of compounded conditionals; in particular we examine the Frechet-Hoeffding bounds. Moreover, we study the reverse probabilistic inference from the conjunction $\mathcal…

FOS: Computer and information sciencesSettore MAT/06 - Probabilita' E Statistica MatematicaComputer Science - Artificial IntelligenceComputer scienceMonotonic functionProbabilistic reasoning02 engineering and technologyCommutative Algebra (math.AC)Conditional random quantitieFréchet-Hoeffding boundCoherent extensionNegationArtificial IntelligenceQuasi conjunction0202 electrical engineering electronic engineering information engineeringFOS: MathematicsCoherent prevision assessmentConditional eventNon-monotonic logicRule of inferenceCommutative propertyAssociative propertyDiscrete mathematicsProbability (math.PR)Probabilistic logicOrder (ring theory)ConjunctionMathematics - LogicCoherence (philosophical gambling strategy)p-entailmentProbabilistic inferenceMathematics - Commutative AlgebraConjunction (grammar)Artificial Intelligence (cs.AI)020201 artificial intelligence & image processingInference ruleNegationLogic (math.LO)Mathematics - ProbabilityDisjunction
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Algebraic aspects and coherence conditions for conjoined and disjoined conditionals

2019

We deepen the study of conjoined and disjoined conditional events in the setting of coherence. These objects, differently from other approaches, are defined in the framework of conditional random quantities. We show that some well known properties, valid in the case of unconditional events, still hold in our approach to logical operations among conditional events. In particular we prove a decomposition formula and a related additive property. Then, we introduce the set of conditional constituents generated by $n$ conditional events and we show that they satisfy the basic properties valid in the case of unconditional events. We obtain a generalized inclusion-exclusion formula and we prove a …

Pure mathematicsProperty (philosophy)Settore MAT/06 - Probabilita' E Statistica MatematicaDistributivityApplied MathematicsProbability (math.PR)02 engineering and technologyCoherence (statistics)Characterization (mathematics)Settore MAT/01 - Logica Matematica60Axx 03B48Theoretical Computer ScienceCoherenceConditional random quantities Conjunction and disjunction of conditionals Decomposition formula Conditional constituents Inclusion-exclusion formulaSet (abstract data type)Artificial Intelligence020204 information systemsFOS: Mathematics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingInclusion–exclusion principleAlgebraic numberMathematics - ProbabilitySoftwareCounterexampleMathematics
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