A decentralized route to the origins of scaling in human language
Urbina, Felipe [Univ Mayor, Fac Ciencias, Ctr Invest DAiTA Lab, Santiago, Chile]
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 statistical pattern arises from a conflict of interests between the participants of communication. The challenge here is to define a computational multi-agent language game, mainly based on a parameter that measures the relative participant's interests. Numerical simulations suggest that at critical values of the parameter a human-like vocabulary, exhibiting scaling properties, seems to appear. 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 Zipfian properties partly arises from a self-organized process defined by local interactions between agents.
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