Search results for "Intelligence"

showing 10 items of 6959 documents

Reordering Method and Hierarchies for Quantum and Classical Ordered Binary Decision Diagrams

2017

We consider Quantum OBDD model. It is restricted version of read-once Quantum Branching Programs, with respect to “width” complexity. It is known that maximal complexity gap between deterministic and quantum model is exponential. But there are few examples of such functions. We present method (called “reordering”), which allows to build Boolean function g from Boolean Function f, such that if for f we have gap between quantum and deterministic OBDD complexity for natural order of variables, then we have almost the same gap for function g, but for any order. Using it we construct the total function REQ which deterministic OBDD complexity is \(2^{\varOmega (n/log n)}\) and present quantum OBD…

Discrete mathematicsComputational complexity theoryImplicit functionBinary decision diagram010102 general mathematics0102 computer and information sciencesFunction (mathematics)Computer Science::Artificial IntelligenceComputer Science::Computational Complexity01 natural sciencesCombinatorics010201 computation theory & mathematicsComputer Science::Logic in Computer ScienceComplexity class0101 mathematicsBoolean functionQuantum complexity theoryQuantum computerMathematics
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A Potential Field Function for Overlapping Point Set and Graph Cluster Visualization

2015

In this paper we address the problem of visualizing overlapping sets of points with a fixed positioning in a comprehensible way. A standard visualization technique is to enclose the point sets in isocontours generated by bounding a potential field function. The most commonly used functions are various approximations of the Gaussian distribution. Such an approach produces smooth and appealing shapes, however it may produce an incorrect point nesting in generated regions, e.g. some point is contained inside a foreign set region. We introduce a different potential field function that keeps the desired properties of Gaussian distribution, and in addition guarantees that every point belongs to a…

Discrete mathematicsComputer sciencebusiness.industryGaussianGraph of a functionMixed graphFunction (mathematics)Strength of a graphGraphSet (abstract data type)symbols.namesakesymbolsGraph (abstract data type)Point (geometry)Artificial intelligencebusinessAlgorithm
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Sensitivity Versus Certificate Complexity of Boolean Functions

2016

Sensitivity, block sensitivity and certificate complexity are basic complexity measures of Boolean functions. The famous sensitivity conjecture claims that sensitivity is polynomially related to block sensitivity. However, it has been notoriously hard to obtain even exponential bounds. Since block sensitivity is known to be polynomially related to certificate complexity, an equivalent of proving this conjecture would be showing that the certificate complexity is polynomially related to sensitivity. Previously, it has been shown that $$bsf \le Cf \le 2^{sf-1} sf - sf-1$$. In this work, we give a better upper bound of $$bsf \le Cf \le \max \left 2^{sf-1}\left sf-\frac{1}{3}\right , sf\right $…

Discrete mathematicsConjectureStructure (category theory)Block (permutation group theory)0102 computer and information sciences02 engineering and technologyFunction (mathematics)01 natural sciencesUpper and lower boundsExponential functionCombinatorics010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSensitivity (control systems)Boolean functionMathematics
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A formal proof of the ε-optimality of absorbing continuous pursuit algorithms using the theory of regular functions

2014

Published version of an article from the journal: Applied Intelligence. Also available on Springerlink: http://dx.doi.org/10.1007/s10489-014-0541-1 The most difficult part in the design and analysis of Learning Automata (LA) consists of the formal proofs of their convergence accuracies. The mathematical techniques used for the different families (Fixed Structure, Variable Structure, Discretized etc.) are quite distinct. Among the families of LA, Estimator Algorithms (EAs) are certainly the fastest, and within this family, the set of Pursuit algorithms have been considered to be the pioneering schemes. Informally, if the environment is stationary, their ε-optimality is defined as their abili…

Discrete mathematicsDiscretizationLearning automataAbsorbing CPAComputer scienceEstimatorMonotonic functionVDP::Technology: 500::Information and communication technology: 550Mathematical proofFormal proofCPAArbitrarily largeArtificial Intelligenceε-optimalityMartingale (probability theory)Pursuit algorithmsAlgorithm
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On the computational power of affine automata

2017

We investigate the computational power of affine automata (AfAs) introduced in [4]. In particular, we present a simpler proof for how to change the cutpoint for any affine language and a method how to reduce error in bounded error case. Moreover, we address to the question of [4] by showing that any affine language can be recognized by an AfA with certain limitation on the entries of affine states and transition matrices. Lastly, we present the first languages shown to be not recognized by AfAs with bounded-error.

Discrete mathematicsFOS: Computer and information sciencesComputer scienceFormal Languages and Automata Theory (cs.FL)Computer Science - Formal Languages and Automata Theory0102 computer and information sciences02 engineering and technologyerror reduction[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]01 natural sciencesBounded errorPower (physics)Automatonaffine automata[INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineeringnon-classical models of automatacutpoint languages020201 artificial intelligence & image processingTransition matricesAffine transformationcompact setsbounded error
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On a Conjecture by Christian Choffrut

2017

It is one of the most famous open problems to determine the minimum amount of states required by a deterministic finite automaton to distinguish a pair of strings, which was stated by Christian Choffrut more than thirty years ago. We investigate the same question for different automata models and we obtain new upper and lower bounds for some of them including alternating, ultrametric, quantum, and affine finite automata.

Discrete mathematicsFinite-state machineConjecture010102 general mathematics02 engineering and technology01 natural sciencesUpper and lower boundsAutomatonDeterministic finite automatonCounting problem0202 electrical engineering electronic engineering information engineeringComputer Science (miscellaneous)020201 artificial intelligence & image processingAffine transformation0101 mathematicsUltrametric spaceMathematicsInternational Journal of Foundations of Computer Science
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Superiority Of One-Way And Realtime Quantum Machines

2012

In automata theory, quantum computation has been widely examined for finite state machines, known as quantum finite automata (QFAs), and less attention has been given to QFAs augmented with counters or stacks. In this paper, we focus on such generalizations of QFAs where the input head operates in one-way or realtime mode, and present some new results regarding their superiority over their classical counterparts. Our first result is about the nondeterministic acceptance mode: Each quantum model architecturally intermediate between realtime finite state automaton and one-way pushdown automaton (one-way finite automaton, realtime and one-way finite automata with one-counter, and realtime push…

Discrete mathematicsFinite-state machineTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESGeneral MathematicsPushdown automaton0102 computer and information sciences02 engineering and technologyω-automaton01 natural sciencesComputer Science ApplicationsNondeterministic algorithmTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineeringQuantum finite automataAutomata theory020201 artificial intelligence & image processingAlgorithmSoftwareComputer Science::Formal Languages and Automata TheoryQuantum cellular automatonMathematicsQuantum computer
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On a Category of Extensional Fuzzy Rough Approximation L-valued Spaces

2016

We establish extensionality of some upper and lower fuzzy rough approximation operators on an L-valued set. Taking as the ground basic properties of these operators, we introduce the concept of an (extensional) fuzzy rough approximation L-valued space. We apply fuzzy functions satisfying certain continuity-type conditions, as morphisms between such spaces, and in the result obtain a category \(\mathcal{FRA}{} \mathbf{SPA}(L)\) of fuzzy rough approximation L-valued spaces. An interpretation of fuzzy rough approximation L-valued spaces as L-fuzzy (di)topological spaces is presented and applied for constructing examples in category \(\mathcal{FRA}{} \mathbf{SPA}(L)\).

Discrete mathematicsFuzzy classificationMathematics::General Mathematics05 social sciences050301 education02 engineering and technologyTopological spaceSpace (mathematics)Fuzzy logicMorphismMathematics::Category TheoryFuzzy mathematics0202 electrical engineering electronic engineering information engineeringFuzzy numberCategory of topological spaces020201 artificial intelligence & image processing0503 educationMathematics
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On block pumpable languages

2016

Ehrenfeucht, Parikh and Rozenberg gave an interesting characterisation of the regular languages called the block pumping property. When requiring this property only with respect to members of the language but not with respect to nonmembers, one gets the notion of block pumpable languages. It is shown that these block pumpable are a more general concept than regular languages and that they are an interesting notion of their own: they are closed under intersection, union and homomorphism by transducers; they admit multiple pumping; they have either polynomial or exponential growth.

Discrete mathematicsGeneral Computer ScienceAbstract family of languagesComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)0102 computer and information sciences02 engineering and technology01 natural sciencesCone (formal languages)Pumping lemma for regular languagesTheoretical Computer ScienceCombinatoricsRegular languageIntersection010201 computation theory & mathematicsBlock (programming)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingHomomorphismPumping lemma for context-free languagesComputer Science::Formal Languages and Automata TheoryMathematicsTheoretical Computer Science
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Machine-Independent Characterizations and Complete Problems for Deterministic Linear Time

2002

This article presents two algebraic characterizations and two related complete problems for the complexity class DLIN that was introduced in [E. Grandjean, Ann. Math. Artif. Intell., 16 (1996), pp. 183--236]. DLIN is essentially the class of all functions that can be computed in linear time on a Random Access Machine which uses only numbers of linear value during its computations. The algebraic characterizations are in terms of recursion schemes that define unary functions. One of these schemes defines several functions simultaneously, while the other one defines only one function. From the algebraic characterizations, we derive two complete problems for DLIN under new, very strict, and mac…

Discrete mathematicsGeneral Computer ScienceUnary operationGeneral Mathematics[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Recursion (computer science)[INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]0102 computer and information sciences02 engineering and technologyFunction (mathematics)01 natural sciencesRandom-access machine010201 computation theory & mathematicsCompleteness (order theory)0202 electrical engineering electronic engineering information engineeringComplexity class020201 artificial intelligence & image processingAlgebraic numberTime complexityMathematics
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