Self-generated dynamic landscape: The message-receiver interaction case

In the present work we present a model, based on a particular differential stochastic equation, to study the interaction between an incoming message and its interpreter. The particular stochastic dynamic used to understand such process is written using a delayed Langevin equation with white noise. T...

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Autores principales: Fuentes, M.A., Miguel, H.
Formato: JOUR
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Acceso en línea:http://hdl.handle.net/20.500.12110/paper_03784371_v392_n10_p2492_Fuentes
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spelling todo:paper_03784371_v392_n10_p2492_Fuentes2023-10-03T15:33:01Z Self-generated dynamic landscape: The message-receiver interaction case Fuentes, M.A. Miguel, H. Categorization Conceptual network Dynamic landscape Interpretation Learning Stochastic Categorization Interpretation Langevin equation Learning Stochastic Stochastic dynamics Stochastic equations Differential equations Stochastic systems White noise Stochastic models In the present work we present a model, based on a particular differential stochastic equation, to study the interaction between an incoming message and its interpreter. The particular stochastic dynamic used to understand such process is written using a delayed Langevin equation with white noise. The results of this kind of interaction can be understood in a general framework that we name the self generated dynamic landscape. © 2013 Elsevier B.V. All rights reserved. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03784371_v392_n10_p2492_Fuentes
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Categorization
Conceptual network
Dynamic landscape
Interpretation
Learning
Stochastic
Categorization
Interpretation
Langevin equation
Learning
Stochastic
Stochastic dynamics
Stochastic equations
Differential equations
Stochastic systems
White noise
Stochastic models
spellingShingle Categorization
Conceptual network
Dynamic landscape
Interpretation
Learning
Stochastic
Categorization
Interpretation
Langevin equation
Learning
Stochastic
Stochastic dynamics
Stochastic equations
Differential equations
Stochastic systems
White noise
Stochastic models
Fuentes, M.A.
Miguel, H.
Self-generated dynamic landscape: The message-receiver interaction case
topic_facet Categorization
Conceptual network
Dynamic landscape
Interpretation
Learning
Stochastic
Categorization
Interpretation
Langevin equation
Learning
Stochastic
Stochastic dynamics
Stochastic equations
Differential equations
Stochastic systems
White noise
Stochastic models
description In the present work we present a model, based on a particular differential stochastic equation, to study the interaction between an incoming message and its interpreter. The particular stochastic dynamic used to understand such process is written using a delayed Langevin equation with white noise. The results of this kind of interaction can be understood in a general framework that we name the self generated dynamic landscape. © 2013 Elsevier B.V. All rights reserved.
format JOUR
author Fuentes, M.A.
Miguel, H.
author_facet Fuentes, M.A.
Miguel, H.
author_sort Fuentes, M.A.
title Self-generated dynamic landscape: The message-receiver interaction case
title_short Self-generated dynamic landscape: The message-receiver interaction case
title_full Self-generated dynamic landscape: The message-receiver interaction case
title_fullStr Self-generated dynamic landscape: The message-receiver interaction case
title_full_unstemmed Self-generated dynamic landscape: The message-receiver interaction case
title_sort self-generated dynamic landscape: the message-receiver interaction case
url http://hdl.handle.net/20.500.12110/paper_03784371_v392_n10_p2492_Fuentes
work_keys_str_mv AT fuentesma selfgenerateddynamiclandscapethemessagereceiverinteractioncase
AT miguelh selfgenerateddynamiclandscapethemessagereceiverinteractioncase
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