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.

Self-reproduction via description is discussed in a network model of machines and description tapes. Tapes consist of bit strings, which encode the machines' function. A tape is replicated when it is read by adequate machines. Generally, a machine rewrites a tape without doing correct replication. The variation in a reproduced tape is taken as mutation. Because this mutation is caused by a machine's program, we call it active mutation . Which machine is translated from a given tape is dependent on what kind of a machine reads the tape. External noise is introduced in a machine's reading process to make errors. A new reaction pathway is induced by external noise via a machine's error action. We find that the induced pathways will be mimicked deterministically in an emerging core structure. This core structure will remain stable after turning off external noise. Low external noise develops a core structure of a minimal self-replicative loop. When external noise is elevated, a more complex network evolves. Machines containing a complex core network, which has been bred in high external noise, will actively rewrite tapes rather than just replicate them. Self-replication not as an individual but as a network now becomes important.