Search results for "0102 Applied Mathematics"

showing 3 items of 3 documents

Quadratically Tight Relations for Randomized Query Complexity

2020

In this work we investigate the problem of quadratically tightly approximating the randomized query complexity of Boolean functions R(f). The certificate complexity C(f) is such a complexity measure for the zero-error randomized query complexity R0(f): C(f) ≤R0(f) ≤C(f)2. In the first part of the paper we introduce a new complexity measure, expectational certificate complexity EC(f), which is also a quadratically tight bound on R0(f): EC(f) ≤R0(f) = O(EC(f)2). For R(f), we prove that EC2/3 ≤R(f). We then prove that EC(f) ≤C(f) ≤EC(f)2 and show that there is a quadratic separation between the two, thus EC(f) gives a tighter upper bound for R0(f). The measure is also related to the fractional…

Quadratic growth[INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC]0209 industrial biotechnology0102 computer and information sciences02 engineering and technologyMeasure (mathematics)Upper and lower bounds01 natural sciencesACM: F.: Theory of ComputationSquare (algebra)Computation Theory & MathematicsTheoretical Computer ScienceCombinatoricsQuadratic equation020901 industrial engineering & automationComputational Theory and Mathematics010201 computation theory & mathematicsTheory of computationInformation complexity[INFO]Computer Science [cs]0102 Applied Mathematics 0802 Computation Theory and Mathematics 0805 Distributed ComputingCommunication complexityBoolean functionComputingMilieux_MISCELLANEOUSMathematics
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Modeling crowd dynamics through coarse-grained data analysis

2018

International audience; Understanding and predicting the collective behaviour of crowds is essential to improve the efficiency of pedestrian flows in urban areas and minimize the risks of accidents at mass events. We advocate for the development of crowd traffic management systems, whereby observations of crowds can be coupled to fast and reliable models to produce rapid predictions of the crowd movement and eventually help crowd managers choose between tailored optimization strategies. Here, we propose a Bi-directional Macroscopic (BM) model as the core of such a system. Its key input is the fundamental diagram for bi-directional flows, i.e. the relation between the pedestrian fluxes and d…

Data AnalysisOperations researchComputer scienceFLOW[INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR]macroscopic model0904 Chemical EngineeringTransportation02 engineering and technologycomputer.software_genre01 natural sciences010305 fluids & plasmas[SHS]Humanities and Social Sciences[SCCO]Cognitive scienceCrowds0903 Biomedical Engineering0102 Applied Mathematics11. Sustainability0202 electrical engineering electronic engineering information engineeringCluster AnalysisApplied Mathematicsbi-directional fluxcollective behaviourGeneral Medicine[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]Computational MathematicsCore (game theory)Modeling and Simulation[SCCO.PSYC]Cognitive science/Psychology020201 artificial intelligence & image processingGeneral Agricultural and Biological SciencesLife Sciences & BiomedicineBEHAVIORCrowd dynamicsRelation (database)Bioinformatics[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS]BioengineeringPedestrianModels PsychologicalMachine learningAdvanced Traffic Management SystemPedestrian traffic0103 physical sciencesHumansComputer Simulation[NLIN.NLIN-AO]Nonlinear Sciences [physics]/Adaptation and Self-Organizing Systems [nlin.AO]Block (data storage)Science & Technologybusiness.industryMathematical ConceptsSIMULATIONSdata-based modelingCrowdingKey (cryptography)Artificial intelligenceMathematical & Computational Biologybusinesscomputer
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Crowd-Averse Robust Mean-Field Games: Approximation via State Space Extension

2016

We consider a population of dynamic agents, also referred to as players. The state of each player evolves according to a linear stochastic differential equation driven by a Brownian motion and under the influence of a control and an adversarial disturbance. Every player minimizes a cost functional which involves quadratic terms on state and control plus a cross-coupling mean-field term measuring the congestion resulting from the collective behavior, which motivates the term “crowd-averse.” Motivations for this model are analyzed and discussed in three main contexts: a stock market application, a production engineering example, and a dynamic demand management problem in power systems. For th…

0209 industrial biotechnologyStochastic stabilityMathematical optimizationCollective behaviorTechnologyComputer sciencePopulationcontrol designcrowd-averse robust mean-field games state space extension dynamic agents linear stochastic differential equation Brownian motion adversarial disturbance cost functional cross-coupling mean-field term collective behavior stock market application production engineering example dynamic demand management problem robust mean-field game approximation error stochastic stability microscopic dynamics macroscopic dynamicscontrol engineering02 engineering and technology01 natural sciencesStochastic differential equationoptimal control020901 industrial engineering & automationQuadratic equationAutomation & Control SystemsEngineeringClosed loop systemsSettore ING-INF/04 - AutomaticaApproximation errorRobustness (computer science)Control theory0102 Applied MathematicsState space0101 mathematicsElectrical and Electronic EngineeringeducationBrownian motioneducation.field_of_studyScience & TechnologyStochastic process010102 general mathematicsRelaxation (iterative method)Engineering Electrical & ElectronicOptimal controlComputer Science Applications0906 Electrical and Electronic EngineeringIndustrial Engineering & AutomationMean field theoryControl and Systems EngineeringSettore MAT/09 - Ricerca Operativa0913 Mechanical Engineering
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