@article{b,
title = {Exploring the roles of complex networks in linguistic categorization},
author = {Tao Gong and Andrea Baronchelli and Andrea Puglisi and Vittorio Loreto},
url = {http://www.mitpressjournals.org/doi/abs/10.1162/artl_a_00051
http://www.scopus.com/inward/record.url?eid=2-s2.0-84455212316&partnerID=65&md5=758e5307761080b1252443baf9d08abf
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=000298413600005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=0c7ff228ccbaaa74236f48834a34396a
http://socialdynamics.it/vittorioloreto/PAPERS/2012/Gongetal(2012)-ALife-CatGameNetwork.pdf},
year = {2012},
date = {2012-01-01},
journal = {ARTIFICIAL LIFE},
volume = {18 (1)},
pages = {107--121},
publisher = {MIT PRESS, 55 HAYWARD STREET, CAMBRIDGE, MA 02142 USA},
abstract = {This article adopts the category game model, which simulates the origins and evolution of linguistic categories in a group of artificial agents, to evaluate the effect of social structure on linguistic categorization. Based on the simulation results in a number of typical networks, we examine the isolating and collective effects of some structural features, including average degree, shortcuts, and level of centrality, on the categorization process. This study extends the previous simulations mainly on lexical evolution, and illustrates a general framework to systematically explore the effect of social structure on language evolution.},
keywords = {baronchelli, gong, language_dynamics, loreto, puglisi},
pubstate = {published},
tppubtype = {article}
}
This article adopts the category game model, which simulates the origins and evolution of linguistic categories in a group of artificial agents, to evaluate the effect of social structure on linguistic categorization. Based on the simulation results in a number of typical networks, we examine the isolating and collective effects of some structural features, including average degree, shortcuts, and level of centrality, on the categorization process. This study extends the previous simulations mainly on lexical evolution, and illustrates a general framework to systematically explore the effect of social structure on language evolution.
@article{b,
title = {Modeling the emergence of universality in color naming patterns},
author = {Andrea Baronchelli and Tao Gong and Aandrea Puglisi and Vittorio Loreto},
url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-77349119009&partnerID=65&md5=6cdcb665c28403d74f0a0437b8e4c0cf
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=000274408100011&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=0c7ff228ccbaaa74236f48834a34396a
http://socialdynamics.it/vittorioloreto/PAPERS/2010/Baronchelli_PNAS_2010.pdf},
year = {2010},
date = {2010-01-01},
journal = {PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (PNAS)},
volume = {107},
pages = {2403--2407},
publisher = {NATL ACAD SCIENCES},
abstract = {The empirical evidence that human color categorization exhibits some universal patterns beyond superficial discrepancies across different cultures is a major breakthrough in cognitive science. As observed in the World Color Survey (WCS), indeed, any two groups of individuals develop quite different categorization patterns, but some universal properties can be identified by a statistical analysis over a large number of populations. Here, we reproduce the WCS in a numerical model in which different populations develop independently their own categorization systems by playing elementary language games. We find that a simple perceptual constraint shared by all humans, namely the human Just Noticeable Difference (JND), is sufficient to trigger the emergence of universal patterns that unconstrained cultural interaction fails to produce. We test the results of our experiment against real data by performing the same statistical analysis proposed to quantify the universal tendencies shown in the WCS [Kay P & Regier T. (2003) Proc. Natl. Acad. Sci. USA 100: 9085-9089], and obtain an excellent quantitative agreement. This work confirms that synthetic modeling has nowadays reached the maturity to contribute significantly to the ongoing debate in cognitive science.},
keywords = {baronchelli, gong, language_dynamics, loreto, puglisi},
pubstate = {published},
tppubtype = {article}
}
The empirical evidence that human color categorization exhibits some universal patterns beyond superficial discrepancies across different cultures is a major breakthrough in cognitive science. As observed in the World Color Survey (WCS), indeed, any two groups of individuals develop quite different categorization patterns, but some universal properties can be identified by a statistical analysis over a large number of populations. Here, we reproduce the WCS in a numerical model in which different populations develop independently their own categorization systems by playing elementary language games. We find that a simple perceptual constraint shared by all humans, namely the human Just Noticeable Difference (JND), is sufficient to trigger the emergence of universal patterns that unconstrained cultural interaction fails to produce. We test the results of our experiment against real data by performing the same statistical analysis proposed to quantify the universal tendencies shown in the WCS [Kay P & Regier T. (2003) Proc. Natl. Acad. Sci. USA 100: 9085-9089], and obtain an excellent quantitative agreement. This work confirms that synthetic modeling has nowadays reached the maturity to contribute significantly to the ongoing debate in cognitive science.
@article{b,
title = {Conventionalization of linguistic knowledge under communicative constraints},
author = {Tao Gong and Andrea Puglisi and Vittorio Loreto and William S.-Y. Wang},
year = {2008},
date = {2008-01-01},
journal = {BIOLOGICAL THEORY},
volume = {3},
pages = {154--163},
publisher = {Cambridge, MA, USA, MIT Press Journals},
keywords = {gong, language_dynamics, loreto, puglisi, wang},
pubstate = {published},
tppubtype = {article}
}
