Title: Agent-based model for the origins of scaling in human language,
Abstract: Background/Introduction: The Zipf's law establishes that if the words of a
(large) text are ordered by decreasing frequency, the frequency versus the rank
decreases as a power law with exponent close to -1. Previous work has stressed
that this pattern arises from a conflict of interests of the participants of
communication: speakers and hearers. Methods: The challenge here is to define a
computational language game on a population of agents, playing games mainly
based on a parameter that measures the relative participant's interests.
Results: Numerical simulations suggest that at critical values of the parameter
a human-like vocabulary, exhibiting scaling properties, seems to appear.
Conclusions: The appearance of an intermediate distribution of frequencies at
some critical values of the parameter suggests that on a population of
artificial agents the emergence of scaling partly arises as a self-organized
process only from local interactions between agents.