Search results for " reasoning"

showing 10 items of 357 documents

Quasi Conjunction and Inclusion Relation in Probabilistic Default Reasoning

2011

We study the quasi conjunction and the Goodman & Nguyen inclusion relation for conditional events, in the setting of probabilistic default reasoning under coherence. We deepen two recent results given in (Gilio and Sanfilippo, 2010): the first result concerns p-entailment from a family F of conditional events to the quasi conjunction C(S) associated with each nonempty subset S of F; the second result, among other aspects, analyzes the equivalence between p-entailment from F and p-entailment from C(S), where S is some nonempty subset of F. We also characterize p-entailment by some alternative theorems. Finally, we deepen the connections between p-entailment and the Goodman & Nguyen inclusion…

Discrete mathematicsClass (set theory)goodman & nguyen inclusion relationSettore MAT/06 - Probabilita' E Statistica MatematicaSettore INF/01 - Informaticap-entailment.; quasi conjunction; goodman & nguyen inclusion relation; qand rule; coherence; probabilistic default reasoning; p-entailmentProbabilistic logicqand ruleprobabilistic default reasoningConsistency (knowledge bases)Coherence (philosophical gambling strategy)p-entailmentCoherence probabilistic default reasoning quasi conjunction Goodman & Nguyen inclusion relation QAND rule p-entailment.coherenceConjunction (grammar)Default reasoningquasi conjunctionGreatest elementAlgorithmEquivalence (measure theory)Mathematics
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Application of kolmogorov complexity to inductive inference with limited memory

1995

A b s t r a c t . We consider inductive inference with limited memory[l]. We show that there exists a set U of total recursive functions such that U can be learned with linear long-term memory (and no short-term memory); U can be learned with logarithmic long-term memory (and some amount of short-term memory); if U is learned with sublinear long-term memory, then the short-term memory exceeds arbitrary recursive function. Thus an open problem posed by Freivalds, Kinber and Smith[l] is solved. To prove our result, we use Kolmogorov complexity.

Discrete mathematicsHardware_MEMORYSTRUCTURESKolmogorov complexityLogarithmSublinear functionKolmogorov structure functionChain rule for Kolmogorov complexityOpen problemInductive probabilityInductive reasoningMathematics
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Kolmogorov numberings and minimal identification

1995

Identification of programs for computable functions from their graphs by algorithmic devices is a well studied problem in learning theory. Freivalds and Chen consider identification of ‘minimal’ and ‘nearly minimal’ programs for functions from their graphs. To address certain problems in minimal identification for Godel numberings, Freivalds later considered minimal identification in Kolmogorov Numberings. Kolmogorov numberings are in some sense optimal numberings and have some nice properties. We prove certain hierarchy results for minimal identification in every Kolmogorov numbering. In addition we also compare minimal identification in Godel numbering versus minimal identification in Kol…

Discrete mathematicsIdentification (information)Computable functionHierarchy (mathematics)Gödel numberingRecursive functionsInductive reasoningNumberingMathematics
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Parsimony hierarchies for inductive inference

2004

AbstractFreivalds defined an acceptable programming system independent criterion for learning programs for functions in which the final programs were required to be both correct and “nearly” minimal size. i.e.. within a computable function of being purely minimal size. Kinber showed that this parsimony requirement on final programs limits learning power. However, in scientific inference, parsimony is considered highly desirable. Alim-computable functionis (by definition) one calculable by a total procedure allowed to change its mind finitely many times about its output. Investigated is the possibility of assuaging somewhat the limitation on learning power resulting from requiring parsimonio…

Discrete mathematicsLogic68Q32limiting computable functionComputational learning theoryFunction (mathematics)Inductive reasoningNotationminimal size programConstructivePhilosophyComputable functionComputational learning theoryBounded functionArithmeticOrdinal notationconstructive ordinal notationsMathematics
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General inductive inference types based on linearly-ordered sets

1996

In this paper, we reconsider the definitions of procrastinating learning machines. In the original definition of Freivalds and Smith [FS93], constructive ordinals are used to bound mindchanges. We investigate the possibility of using arbitrary linearly ordered sets to bound mindchanges in a similar way. It turns out that using certain ordered sets it is possible to define inductive inference types more general than the previously known ones. We investigate properties of the new inductive inference types and compare them to other types.

Discrete mathematicsOrdered setRecursive functionsInductive reasoningConstructiveMaximal elementMathematics
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Learning with confidence

1996

Herein we investigate learning in the limit where confidence in the current conjecture accrues with time. Confidence levels are given by rational numbers between 0 and 1. The traditional requirement that for learning in the limit is that a device must converge (in the limit) to a correct answer. We further demand that the associated confidence in the answer (monotonically) approach 1 in the limit. In addition to being a more realistic model of learning, our new notion turns out to be a more powerful as well. In addition, we give precise characterizations of the classes of functions that are learnable in our new model(s).

Discrete mathematicsRational numberConjectureCurrent (mathematics)Recursive functionsMonotonic functionLimit (mathematics)Inductive reasoningMathematics
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Probability Propagation in Selected Aristotelian Syllogisms

2019

This paper continues our work on a coherence-based probability semantics for Aristotelian syllogisms (Gilio, Pfeifer, and Sanfilippo, 2016; Pfeifer and Sanfilippo, 2018) by studying Figure III under coherence. We interpret the syllogistic sentence types by suitable conditional probability assessments. Since the probabilistic inference of $P|S$ from the premise set ${P|M, S|M}$ is not informative, we add $p(M|(S ee M))>0$ as a probabilistic constraint (i.e., an ``existential import assumption'') to obtain probabilistic informativeness. We show how to propagate the assigned premise probabilities to the conclusion. Thereby, we give a probabilistic meaning to all syllogisms of Figure~III. We…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica Matematica05 social sciencesProbabilistic logicSyllogismConditional probability02 engineering and technologyCoherence (statistics)Settore MAT/01 - Logica MatematicaImprecise probabilityAristotelian syllogismFigure III050105 experimental psychologyConstraint (information theory)Premise0202 electrical engineering electronic engineering information engineeringImprecise probability020201 artificial intelligence & image processing0501 psychology and cognitive sciencesConditional eventDefault reasoningCoherenceSentenceMathematics
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Transitive Reasoning with Imprecise Probabilities

2015

We study probabilistically informative (weak) versions of transitivity by using suitable definitions of defaults and negated defaults in the setting of coherence and imprecise probabilities. We represent \(\text{ p-consistent }\) sequences of defaults and/or negated defaults by g-coherent imprecise probability assessments on the respective sequences of conditional events. Finally, we present the coherent probability propagation rules for Weak Transitivity and the validity of selected inference patterns by proving p-entailment of the associated knowledge bases.

Discrete mathematicsTransitive relationSettore MAT/06 - Probabilita' E Statistica MatematicaSettore INF/01 - Informaticabusiness.industryProbabilistic logicSyllogismInferenceCoherence (philosophical gambling strategy)Settore M-FIL/02 - Logica E Filosofia Della ScienzaComputer Science::Artificial IntelligenceImprecise probabilityCoherence default imprecise probability knowledge base p-consistency p-entailment reasoning syllogism weak transitivityProbability propagationKnowledge basebusinessMathematics
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A Hypergraph Based Framework for Intelligent Tutoring of Algebraic Reasoning

2013

The translation of word problems into equations is one of the major difficulties for students regarding problem solving. This paper describes both a domain-specific knowledge representation and an inference engine based on hypergraphs that permits intelligent student supervision of this stage of the solving process. The framework presented makes it possible to simultaneously: a) represent all potential algebraic solutions to a given word problem; b) keep track of the student’s actions; c) provide automatic remediation; and d) determine the current state of the resolution process univocally. Starting from these ideas, we have designed an intelligent tutoring system (ITS). An experimental eva…

Discrete mathematicsWord problem (mathematics education)HypergraphTheoretical computer scienceKnowledge representation and reasoningComputer sciencePhysics::Physics EducationAlgebraic numberInference engineIntelligent tutoring systemAlgebraic reasoning
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Relación entre complejidad y dificultad en tareas con patrones lineales reiterativos en estudiantes de 5 años

2018

Una de las finalidades de la enseñanza de las matemáticas en Educación Infantil es fomentar el pensamiento lógico, la creatividad y la capacidad para resolver problemas de los estudiantes. Entre las actividades escolares propias de estas edades es habitual encontrar tareas de identificación y continuación de patrones lineales de repetición. Esta actividad puede ser estudiada desde un contexto de resolución de problemas en el que el estudiante debe discriminar la información superflua de aquella que le permite obtener la regla de generación de la serie y resolver la tarea. Diferentes variables como la longitud del núcleo de repetición, el número de descriptores, su naturaleza o la aparición …

Early childhood educationIdentification (information)Repetition (rhetorical device)Logical reasoningmedia_common.quotation_subjectContext (language use)General MedicineCreativityAffect (psychology)Cognitive psychologyTask (project management)media_commonRevista de Educación de la Universidad de Granada
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