Language Evolution and Computation Bibliography

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Maxi Sun Miguel
2008
Modelling Language Competition: Bilingualism and Complex Social NetworksPDF
Proceedings of the 7th International Conference on the Evolution of Language, pages 59-66, 2008
In the general context of dynamics of social consensus, we study an agent based model for the competition between two socially equivalent languages, addressing the role of bilingualism and social structure. In a regular network, we study the formation of linguistic domains and ...MORE ⇓
In the general context of dynamics of social consensus, we study an agent based model for the competition between two socially equivalent languages, addressing the role of bilingualism and social structure. In a regular network, we study the formation of linguistic domains and their interaction across the boundaries. We also analyse the dynamics on a small world network and on a network with community structure. In all cases, a final scenario of dominance of one language and extinction of the other is obtained (dominance-extinction state). In comparison with the regular network, smaller times for extinction are found in the small world network. In the network with communities instead, the average time for extinction does not give a characteristic time for the dynamics, and metastable states are observed at all time scales.
2007
Physica A: Statistical Mechanics and its Applications 374(2):835-842, 2007
The differential equation of Abrams and Strogatz for the competition between two languages is compared with agent-based Monte Carlo simulations for fully connected networks as well as for lattices in one, two and three dimensions, with up to 10(9) agents. In the case of socially ...MORE ⇓
The differential equation of Abrams and Strogatz for the competition between two languages is compared with agent-based Monte Carlo simulations for fully connected networks as well as for lattices in one, two and three dimensions, with up to 10(9) agents. In the case of socially equivalent languages, agent-based models and a mean-field approximation give grossly different results.