The emergence of linguistic structure: an overview of the iterated learning model
Simulating the evolution of language
Landscapes, learning costs, and genetic assimilation
Evolutionary Computation
Coevolution of multiple species through niche construction modifying shared environments
Artificial Life and Robotics
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Deacon has suggested that one of the key factors of language evolution is not characterized by an increase in genetic contribution, often known as the Baldwin effect, but rather by a decrease. This process effectively increases linguistic learning capability by organizing a novel synergy of multiple lower-order functions previously irrelevant to the process of language acquisition. Deacon posits that this transition is not caused by natural selection. Rather, it is due to the relaxation of natural selection. While there are some cases in which relaxation caused by some external factors indeed induces the transition, we do not know what kind of relaxation has worked in language evolution. In this article, a genetic-algorithm-based computer simulation is used to investigate how the niche-constructing aspect of linguistic behavior may trigger the degradation of genetic predisposition related to language learning. The results show that agents initially increase their genetic predisposition for language learning-the Baldwin effect. They create a highly uniform sociolinguistic environment-a linguistic niche construction. This means that later generations constantly receive very similar inputs from adult agents, and subsequently the selective pressure to retain the genetic predisposition is relaxed.