Search results for "dynamics"

showing 10 items of 9782 documents

A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning

2016

Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies n…

Computer Networks and CommunicationsComputer scienceDecision MakingModels NeurologicalAction PotentialsContext (language use)Insect mushroom bodies bio-inspired control spiking neurons02 engineering and technologyVariation (game tree)Motor Activitybio-inspired control03 medical and health sciences0302 clinical medicineRewardSubsequence0202 electrical engineering electronic engineering information engineeringAnimalsLearningComputer SimulationMushroom BodiesTRACE (psycholinguistics)NeuronsSequencebio-inspired control; Insect mushroom bodies; learning; neural model; resonant neurons; spiking neurons; Action Potentials; Animals; Computer Simulation; Decision Making; Drosophila melanogaster; Learning; Motor Activity; Mushroom Bodies; Neurons; Perception; Reward; Robotics; Models Neurological; Neural Networks Computerspiking neuronsbusiness.industryRoboticsGeneral MedicineInsect mushroom bodiesComplex dynamicsDrosophila melanogasterMushroom bodiesPerception020201 artificial intelligence & image processingNeural Networks ComputerArtificial intelligenceSequence learningbusiness030217 neurology & neurosurgery
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The Mediation of Politics through Twitter: An Analysis of Messages posted during the Campaign for the German Federal Election 2013

2015

Patterns found in digital trace data are increasingly used as evidence of social phenomena. Still, the role of digital services not as mirrors but instead as mediators of social reality has been neglected. We identify characteristics of this mediation process by analyzing Twitter messages referring to politics during the campaign for the German federal election 2013 and comparing the thus emerging image of political reality with established measurements of political reality. We focus on the relationship between temporal dynamics in politically relevant Twitter messages and crucial campaign events, comparing dominant topics in politically relevant tweets with topics prominent in surveys and …

Computer Networks and CommunicationsSocial reality05 social sciencesMedia studiesComputingMilieux_LEGALASPECTSOFCOMPUTING050801 communication & media studieslanguage.human_language0506 political scienceComputer Science ApplicationsGermanTrace (semiology)Politics0508 media and communicationsDynamics (music)Political scienceMediation050602 political science & public administrationlanguageComputational sociologyFederal electionSocial psychologyJournal of Computer-Mediated Communication
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Consensus in opinion dynamics as a repeated game

2018

Abstract We study an n -agent averaging process with dynamics subject to controls and adversarial disturbances. The model arises in multi-population opinion dynamics with macroscopic and microscopic intertwined dynamics. The averaging process describes the influence from neighbouring populations, whereas the input term indicates how the distribution of opinions in the population changes as a result of dynamical evolutions at a microscopic level (individuals’ changing opinions). The input term is obtained as the vector payoff of a two player repeated game. We study conditions under which the agents achieve robust consensus to some predefined target set. Such conditions build upon the approac…

Computer Science::Computer Science and Game Theory0209 industrial biotechnologyeducation.field_of_studyComputer scienceStochastic gamePopulation02 engineering and technologyApproachability01 natural sciences010305 fluids & plasmasTerm (time)020901 industrial engineering & automationControl and Systems EngineeringDynamics (music)0103 physical sciencesRepeated gameElectrical and Electronic EngineeringSet (psychology)educationMathematical economicsGame theoryAutomatica
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The erosion of personal norms and cognitive dissonance

2016

ABSTRACTIn this article, we study how personal norms and behaviour interact and evolve when agents try to reduce cognitive dissonance, and how this dynamic relates to Nash equilibrium. We find that in long run, agents play, and norms prescribe, Nash equilibrium in material payoffs (in the absence of norms). Our model captures two main facts: (i) norms erode along the play of the game; (ii) the erosion of norms depends on the set of possible economic choices, so that the policy maker can potentially influence them.

Computer Science::Computer Science and Game TheoryEconomics and EconometricsSelf-justification05 social sciencesPolicy makerCognitive dissonancenorm dynamicsSettore SECS-P/01 - ECONOMIA POLITICA050105 experimental psychologyNash equilibrium0506 political scienceMicroeconomicssymbols.namesakeNash equilibriumCognitive dissonance; dominant strategies; Nash equilibrium; norm dynamics; Economics and Econometricsdominant strategies050602 political science & public administrationsymbolsCognitive dissonanceEconomics0501 psychology and cognitive sciencesSet (psychology)Mathematical economics
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Magnetic fields in heavy ion collisions: flow and charge transport

2020

At the earliest times after a heavy-ion collision, the magnetic field created by the spectator nucleons will generate an extremely strong, albeit rapidly decreasing in time, magnetic field. The impact of this magnetic field may have detectable consequences, and is believed to drive anomalous transport effects like the Chiral Magnetic Effect (CME). We detail an exploratory study on the effects of a dynamical magnetic field on the hydrodynamic medium created in the collisions of two ultrarelativistic heavy-ions, using the framework of numerical ideal MagnetoHydroDynamics (MHD) with the ECHO-QGP code. In this study, we consider a magnetic field captured in a conducting medium, where the conduc…

Computer Science::Machine LearningParticle physicsPhysics and Astronomy (miscellaneous)Nuclear Theoryheavy ion collisionsFOS: Physical scienceslcsh:Astrophysicsmagnetic fieldshiukkasfysiikkamagneettikentätComputer Science::Digital Libraries01 natural sciencesElectric charge530Nuclear Theory (nucl-th)Statistics::Machine LearningHigh Energy Physics - Phenomenology (hep-ph)0103 physical scienceslcsh:QB460-466ddc:530lcsh:Nuclear and particle physics. Atomic energy. RadioactivityNuclear Experiment (nucl-ex)010306 general physicsNuclear ExperimentEngineering (miscellaneous)Nuclear ExperimentPhysicsCharge conservation010308 nuclear & particles physicsElliptic flowCharge (physics)FermionMagnetic fieldDipoleHigh Energy Physics - PhenomenologyQuantum electrodynamicsComputer Science::Mathematical Softwarelcsh:QC770-798MagnetohydrodynamicsThe European Physical Journal C
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Thermodynamics of the Classical Planar Ferromagnet Close to the Zero-Temperature Critical Point: A Many-Body Approach

2012

We explore the low-temperature thermodynamic properties and crossovers of ad-dimensional classical planar Heisenberg ferromagnet in a longitudinal magnetic field close to its field-induced zero-temperature critical point by employing the two-time Green’s function formalism in classical statistical mechanics. By means of a classical Callen-like method for the magnetization and the Tyablikov-like decoupling procedure, we obtain, for anyd, a low-temperature critical scenario which is quite similar to the one found for the quantum counterpart. Remarkably, ford>2the discrimination between the two cases is found to be related to the different values of the shift exponent which governs the beha…

Computer Science::Machine LearningPhysicsArticle SubjectCondensed matter physicsThermodynamicsStatistical mechanicsCondensed Matter PhysicsComputer Science::Digital Librarieslcsh:QC1-999Statistics::Machine LearningReduced propertiesCritical point (thermodynamics)Critical lineComputer Science::Mathematical SoftwareExponentCritical exponentQuantumlcsh:PhysicsPhase diagramAdvances in Condensed Matter Physics
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Upport vector machines for nonlinear kernel ARMA system identification.

2006

Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA 2k) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based syste…

Computer Science::Machine LearningStatistics::TheoryComputer Networks and CommunicationsBiomedical signal processingInformation Storage and RetrievalMachine learningcomputer.software_genrePattern Recognition AutomatedStatistics::Machine LearningArtificial IntelligenceApplied mathematicsStatistics::MethodologyAutoregressive–moving-average modelComputer SimulationMathematicsTelecomunicacionesHardware_MEMORYSTRUCTURESSupport vector machinesModels StatisticalNonlinear system identificationbusiness.industryAutocorrelationSystem identificationSignal Processing Computer-AssistedGeneral MedicineComputer Science ApplicationsSupport vector machineNonlinear systemKernelAutoregressive modelNonlinear DynamicsARMA modelling3325 Tecnología de las TelecomunicacionesArtificial intelligenceNeural Networks ComputerbusinesscomputerSoftwareAlgorithmsReproducing kernel Hilbert spaceIEEE transactions on neural networks
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Calibrating a Motion Model Based on Reinforcement Learning for Pedestrian Simulation

2012

In this paper, the calibration of a framework based in Multi-agent Reinforcement Learning (RL) for generating motion simulations of pedestrian groups is presented. The framework sets a group of autonomous embodied agents that learn to control individually its instant velocity vector in scenarios with collisions and friction forces. The result of the process is a different learned motion controller for each agent. The calibration of both, the physical properties involved in the motion of our embodied agents and the corresponding dynamics, is an important issue for a realistic simulation. The physics engine used has been calibrated with values taken from real pedestrian dynamics. Two experime…

Computer Science::Multiagent SystemsComputer scienceDynamics (mechanics)DiagramComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCalibrationProcess (computing)Reinforcement learningMotion controllerPhysics engineSimulationMotion (physics)
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Visualization_1.mp4

2018

Images obtained with a Walsh Zone Plate and with the equivalent periodic zone plate of the same resolution.

Computer Science::PerformancePhysics::Fluid DynamicsPhysics::Instrumentation and DetectorsMathematics::Classical Analysis and ODEsAstrophysics::Earth and Planetary Astrophysics
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Visualization_1.mp4

2018

Images obtained with a Walsh Zone Plate and with the equivalent periodic zone plate of the same resolution.

Computer Science::PerformancePhysics::Fluid DynamicsPhysics::Instrumentation and DetectorsMathematics::Classical Analysis and ODEsAstrophysics::Earth and Planetary Astrophysics
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