Consilience of Reductionism and Complexity Theory in Language Research: Adaptive Weight Model

Reductionism and complexity theory are two paradigms frequently found in language research. There exist a number of conflicts in terms of concepts and methodologies between reductionism and complexity theory, which are not conducive to creating a unified language research framework. This paper start...

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Main Author: Chao Zhang
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2022/4216206
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author Chao Zhang
author_facet Chao Zhang
author_sort Chao Zhang
collection DOAJ
description Reductionism and complexity theory are two paradigms frequently found in language research. There exist a number of conflicts in terms of concepts and methodologies between reductionism and complexity theory, which are not conducive to creating a unified language research framework. This paper starts by discussing the adaptability of complex dynamic systems and combines cognitive processing model and artificial neural networks to construct and verify an adaptive weight model, showing that the study of reductionism is induction of high-weight elements and the study of complexity theory is a discussion of system complexity from adaptability, meaning that there is a good fit between the two frameworks. The adaptive weight model is conducive to developing a unified interpretation of language research results.
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spelling doaj-art-ddeb3afeb1ed4ea48443a8e4dc9af8b52025-02-03T06:05:31ZengWileyComplexity1099-05262022-01-01202210.1155/2022/4216206Consilience of Reductionism and Complexity Theory in Language Research: Adaptive Weight ModelChao Zhang0College of Chinese Language and LiteratureReductionism and complexity theory are two paradigms frequently found in language research. There exist a number of conflicts in terms of concepts and methodologies between reductionism and complexity theory, which are not conducive to creating a unified language research framework. This paper starts by discussing the adaptability of complex dynamic systems and combines cognitive processing model and artificial neural networks to construct and verify an adaptive weight model, showing that the study of reductionism is induction of high-weight elements and the study of complexity theory is a discussion of system complexity from adaptability, meaning that there is a good fit between the two frameworks. The adaptive weight model is conducive to developing a unified interpretation of language research results.http://dx.doi.org/10.1155/2022/4216206
spellingShingle Chao Zhang
Consilience of Reductionism and Complexity Theory in Language Research: Adaptive Weight Model
Complexity
title Consilience of Reductionism and Complexity Theory in Language Research: Adaptive Weight Model
title_full Consilience of Reductionism and Complexity Theory in Language Research: Adaptive Weight Model
title_fullStr Consilience of Reductionism and Complexity Theory in Language Research: Adaptive Weight Model
title_full_unstemmed Consilience of Reductionism and Complexity Theory in Language Research: Adaptive Weight Model
title_short Consilience of Reductionism and Complexity Theory in Language Research: Adaptive Weight Model
title_sort consilience of reductionism and complexity theory in language research adaptive weight model
url http://dx.doi.org/10.1155/2022/4216206
work_keys_str_mv AT chaozhang consilienceofreductionismandcomplexitytheoryinlanguageresearchadaptiveweightmodel