Social adaptation in multi-agent model of linguistic categorization is affected by network information flow
| Autor: | Dariusz Plewczynski, Michał Denkiewicz, Joanna Rączaszek-Leonardi, Przemysław Wróblewski, Julian Zubek, Juliusz Barański |
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| Rok vydání: | 2017 |
| Předmět: |
Computer science
Social Sciences lcsh:Medicine Systems Science Vocabulary 0302 clinical medicine Agent-Based Modeling Sociology Information system Centrality Psychology lcsh:Science Language Multidisciplinary Simulation and Modeling 05 social sciences Social Communication Linguistics Social Networks Categorization Physical Sciences Games Social Adjustment Network Analysis Research Article Computer and Information Sciences Topology (electrical circuits) Research and Analysis Methods Phonology Network topology Affect (psychology) 050105 experimental psychology 03 medical and health sciences Humans 0501 psychology and cognitive sciences Information Services Behavior Evolutionary Linguistics Social adaptation lcsh:R Cognitive Psychology Biology and Life Sciences Models Theoretical Communications Recreation Cognitive Science lcsh:Q Mathematics 030217 neurology & neurosurgery Neuroscience |
| Zdroj: | PLoS ONE, Vol 12, Iss 8, p e0182490 (2017) PLoS ONE |
| ISSN: | 1932-6203 |
| Popis: | This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems. |
| Databáze: | OpenAIRE |
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