Complex Adaptive Systems and the Origins of Adaptive Structure: What Experiments Can Tell Us
Autor: LEo | Publicado: 2013-03-04T05:18:00-08:00



Complex Adaptive Systems and the Origins&nbsp;of Adaptive Structure:&nbsp;

What Experiments&nbsp;Can Tell Us



Language is a product of both biological and cultural evolution. Clues to the origins of&nbsp;key structural properties of language can be found in the process of cultural transmission&nbsp;between learners. Recent experiments have shown that iterated learning by human&nbsp;participants in the laboratory transforms an initially unstructured artificial language&nbsp;into one containing regularities that make the system more learnable and stable over&nbsp;time. Here, we explore the process of iterated learning in more detail by demonstrating&nbsp;exactly how one type of structure—compositionality—emerges over the course of these&nbsp;experiments. We introduce a method to precisely quantify the increasing ability of&nbsp;a language to systematically encode associations between individual components of&nbsp;meanings and signals over time and we examine how the system as a whole evolves to&nbsp;avoid ambiguity in these associations and generate adaptive structure.

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the very fact that language persists through multiple&nbsp;repeated instances of usage can explain the origins of key structural properties&nbsp;that are universally present in language. Because of this, taking a complex&nbsp;adaptive systems perspective on language lifts the burden of explanation for&nbsp;these properties from a putative richly structured domain-specific substrate,&nbsp;of the sort assumed by much of generative linguistics (e.g., Chomsky, 1965).



Much of the work over the past 20 years or so in modeling the evolution&nbsp;of language has taken this complex adaptive systems perspective (see, e.g.,&nbsp;Brighton, Smith, &amp; Kirby, 2005; Kirby, 2002b; Steels, 2003, for review). One&nbsp;particular strand of work has focused on the adaptation of language through&nbsp;a repeated cycle of learning and use within and across generations, where&nbsp;adaptation is taken to mean a process of optimization or fitting of the structure&nbsp;of language to the mechanisms of transmission (Kirby, 1999).



(...) One of the ways in which a language can evolve to become more&nbsp;learnable is by becoming structured.



"alien" language... chain learning



First, by looking at the learning errors made between adjacent&nbsp;generations, it was shown that the languages in both conditions were being&nbsp;acquired significantly more faithfully toward the end of the chains than they&nbsp;were at the beginning. Second, this increase in learnability over time occurred&nbsp;as a result of the languages becoming more structured over time.



Summary

Kirby et al. (2008) found that the languages that emerge through a repeated cycle&nbsp;of learning and production in a laboratory setting show evidence of adaptation&nbsp;to the bottleneck placed on their transmission. Making even minor changes&nbsp;to the way in which language is culturally transmitted can produce radically&nbsp;different types of structures. Given only a bottleneck on transmission preventing&nbsp;a proportion of the language from being seen by the next generation, language&nbsp;can adapt in such a way that ensures that it is stably transmitted to future&nbsp;generations. However, this occurs at the expense of being able to uniquely refer&nbsp;to every meaning. When they introduced the additional pressure of having to&nbsp;use a unique signal for each meaning, the language once again adapted to cope&nbsp;with these new transmission constraints, this time by becoming compositional.&nbsp;Having a compositional system ensures that both signals and meanings survive&nbsp;the bottleneck.



Because the participants could not know which condition they were in, it is&nbsp;impossible that the resulting languages were intentionally designed as adaptive&nbsp;solutions to the transmission bottleneck. Rather, the best explanation for the&nbsp;result is that in these experiments, just as in the computational models, linguistic&nbsp;adaptation is an inevitable consequence of the transmission of linguistic variants&nbsp;under particular constraints on replication. The result is apparent design, but&nbsp;without an intentional designer.

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It seems clear from all of this that, first, cultural transmission alone is&nbsp;capable of explaining the emergence of languages that exhibit that appearance&nbsp;of design and, second, experimental studies of the iterated learning of artificial&nbsp;languages are a potentially useful methodological tool for those interested in&nbsp;studying cultural evolution.



Conclusion

This article has extended previous work on iterated language learning experiments by showing, using data obtained from an earlier study, exactly how&nbsp;compositional structure emerges over time as a result of cultural transmission.&nbsp;Using a recently developed analytical technique that calculates the regularity of&nbsp;mapping between signal and meaning elements (Tamariz &amp; Smith, 2008), we&nbsp;were able to precisely quantify changes in the language’s ability to systematically encode such associations between meaning and signal components. From&nbsp;this we were able to explain the amplification effect the bottleneck seems tohave on systematicity in language, arguing that the sampling of smaller subsets&nbsp;of the language for training input to the next generation tends to make weaker&nbsp;patterns that are not visible at the level of the entire language appear stronger&nbsp;locally.