Volume 30, Issue 1
  • ISSN 0774-5141
  • E-ISSN: 1569-9676
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In the context of cultural evolution, we propose a multi-agent model that allows, through pair-wise interactions between homogeneous individuals of a population, to simulate the shift from a syntactic towards a semantic pronominal agreement system. We explore various gender mapping and learning mechanisms that can allow the agents to form a new agreement system using their semantic knowledge about the world. We investigate whether our strategies can yield cohesive clusterings over the semantic space. We notice that the system reaches full convergence in terms of gender preference at population level and that there are multiple successful ways of dividing the semantic space, including one that reflects the so-called , a case attested by a study of a spoken language data.


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