scholarly journals Naming Game and Computational Modelling of Language Evolution

2011 ◽  
Vol 17 (1) ◽  
pp. 41-51 ◽  
Author(s):  
Dorota Lipowska
Keyword(s):  
Language Evolution ◽  
Computational Modelling ◽  
Naming Game

scholarly journals Agent-based modelling using naming game for language evolution studies

2021 ◽  
Vol 127 ◽  
pp. 01014
Author(s):  
Alexander Ioilyevich Ilyinsky ◽  
Galina Vladimirovna Klimova ◽  
Evgeniy Sergeevich Smakhtin ◽  
Marina Aleksandrovna Amurskaya ◽  
Ekaterina Yurievna Rozhina
Keyword(s):  
Language Evolution ◽  
Computational Modelling ◽  
Foreign Languages ◽  
Contemporary Society ◽  
Research Papers ◽  
Naming Game ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Vast Literature ◽  
Language Emergence

The article describes approaches to applying agent-based modelling and, particularly, the case of Naming Game, in linguistic studies and within teaching foreign languages. Computational modelling implementation has become a comprehensive and ambitious field of research, as its methods are applicable to solving tasks set within various aspects of contemporary society and science. The main purpose of this paper is to perform an analysis of Naming Game implementation in language emergence and evolution studies. To achieve this purpose we set several tasks: to present a vast literature review on agent-based modelling in linguistics and other adjacent sciences; to give an overview and description of the Naming Game; to perform simulations within the Naming Game and present their outcomes. As the main methodology the article uses simulations. The paper concludes that a clear hysteresis effect is present in the dependence of the size of the population vocabulary from the size of vocabulary of its average agent. At the point where the population vocabulary transitions into the uniform distribution the average agent’s vocabulary reaches saturation and plateaus. Those dynamics also change as the population vocabulary grows and declines. Agent-based modelling is a relatively novel direction for linguistics with a modest number of research papers. Results, presented in the paper, give a fresh angle on the issues of language emergence and evolution.

Language Evolution and Development

1993 ◽  
Vol 38 (5) ◽  
pp. 520-522
Author(s):  
Richard P. Meier
Keyword(s):  
Language Evolution ◽  
Evolution And Development

SAMPL7 TrimerTrip Host-Guest Binding Poses and Binding Affinities from Spherical-Coordinates-Biased Simulations

2020 ◽  
Author(s):  
Zhaoxi Sun
Keyword(s):  
Free Energy ◽  
Computational Modelling ◽  
Free Energy Calculations ◽  
Energy Estimates ◽  
Binding Affinities ◽  
Spherical Coordinates ◽  
Collective Variables ◽  
Guest Binding ◽  
Starting Point ◽  
Sampl Challenge

Host-guest binding remains a major challenge in modern computational modelling. The newest 7<sup>th</sup> statistical assessment of the modeling of proteins and ligands (SAMPL) challenge contains a new series of host-guest systems. The TrimerTrip host binds to 16 structurally diverse guests. Previously, we have successfully employed the spherical coordinates as the collective variables coupled with the enhanced sampling technique metadynamics to enhance the sampling of the binding/unbinding event, search for possible binding poses and predict the binding affinities in all three host-guest binding cases of the 6<sup>th</sup> SAMPL challenge. In this work, we employed the same protocol to investigate the TrimerTrip host in the SAMPL7 challenge. As no binding pose is provided by the SAMPL7 host, our simulations initiate from randomly selected configurations and are proceeded long enough to obtain converged free energy estimates and search for possible binding poses. The predicted binding affinities are in good agreement with the experimental reference, and the obtained binding poses serve as a nice starting point for end-point or alchemical free energy calculations.

The Russian Language at the Turn of the Century: Semantic Capability and Development Prospects

2018 ◽  
Vol 13 (3-4) ◽  
pp. 150-169
Author(s):  
Svetlana N. Perevolochanskaya
Keyword(s):  
Information Technologies ◽  
Language Evolution ◽  
Turn Of The Century ◽  
Russian Language ◽  
First Century ◽  
Linguistic Knowledge ◽  
Current State ◽  
Linguistic Sign ◽  
Development Prospects ◽  
The Russian Language

The article considers the current state of the Russian language. Information technologies in the twenty first century present diverse forms of linguistic knowledge and modalities of knowledge quantisation in a linguistic sign. The Russian language develops from a standard, direct expression of thoughts to a nonstandard, psychologically complex, associative deep statement of thoughts. In the early nineteenth century, during the democratisation of the Russian language, a national genius, Alexander Pushkin, emerged. Thanks to him, the unique informational, cultural, and artistic evolution of the language took place. Nowadays, while democratisation and globalisation, processes which resemble the language evolution 200 years ago, are occurring. These processes suggest some patterns: overcoming stylistic disparity, changes in linguistic sign boundaries and semantic extension.

Clash of signs: Putting bilingualism back into language evolution

2020 ◽  
Author(s):  
Steven Samuel
Keyword(s):  
Language Evolution ◽  
Modern Human ◽  
Alarm Calls ◽  
Bilingual Children ◽  
Human Language ◽  
Typically Developing ◽  
Typically Developing Children ◽  
Modern Humans ◽  
The Real ◽  
Multiple Languages

Research and thinking into the cognitive aspects of language evolution has usually attempted to account for how the capacity for learning even one modern human language developed. Bilingualism has perhaps been thought of as something to think about only once the ‘real’ puzzle of monolingualism is solved, but this would assume in turn (and without evidence) that bilingualism evolved after monolingualism. All typically-developing children (and adults) are capable of learning multiple languages, and the majority of modern humans are at least bilingual. In this paper I ask whether by skipping bilingualism out of language evolution we have missed a trick. I propose that exposure to synonymous signs, such as food and alarm calls, are a necessary precondition for the abstracting away of sound from referent. In support of this possibility is evidence that modern day bilingual children are better at breaking this ‘word magic’ spell. More generally, language evolution should be viewed through the lens of bilingualism, as this is the end state we are attempting to explain.

Pollutants in Organic Chemistry and Medicinal Chemistry Education Laboratory. Experimental and Machine Learning Studies

2020 ◽  
Vol 20 (9) ◽  
pp. 720-730
Author(s):  
Iker Montes-Bageneta ◽  
Urtzi Akesolo ◽  
Sara López ◽  
Maria Merino ◽  
Eneritz Anakabe ◽  
...  
Keyword(s):  
Organic Chemistry ◽  
Machine Learning ◽  
Chemistry Education ◽  
Organic Waste ◽  
Computational Modelling ◽  
University Education ◽  
Academic Factors ◽  
Academic Year ◽  
Statistical Analysis Software

Aims: Computational modelling may help us to detect the more important factors governing this process in order to optimize it. Background: The generation of hazardous organic waste in teaching and research laboratories poses a big problem that universities have to manage. Methods: In this work, we report on the experimental measurement of waste generation on the chemical education laboratories within our department. We measured the waste generated in the teaching laboratories of the Organic Chemistry Department II (UPV/EHU), in the second semester of the 2017/2018 academic year. Likewise, to know the anthropogenic and social factors related to the generation of waste, a questionnaire has been utilized. We focused on all students of Experimentation in Organic Chemistry (EOC) and Organic Chemistry II (OC2) subjects. It helped us to know their prior knowledge about waste, awareness of the problem of separate organic waste and the correct use of the containers. These results, together with the volumetric data, have been analyzed with statistical analysis software. We obtained two Perturbation-Theory Machine Learning (PTML) models including chemical, operational, and academic factors. The dataset analyzed included 6050 cases of laboratory practices vs. practices of reference. Results: These models predict the values of acetone waste with R2 = 0.88 and non-halogenated waste with R2 = 0.91. Conclusion: This work opens a new gate to the implementation of more sustainable techniques and a circular economy with the aim of improving the quality of university education processes.

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