Compositional Hierarchical Structure Evolves through Cultural Transmission: An Experimental Study

Saldana, Carmen; Kirby, Simon; Truswell, Robert; Smith, Kenny

doi:10.1093/jole/lzz002

Cited by 13 publications

(19 citation statements)

References 60 publications

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“…However, these results are at odds with the prior research into iterated learning, which has repeatedly shown that learners have a bias for simplicity-not informativenessand that iterated learning therefore gives rise to simple, degenerate, uninformative languages. Informative languages only emerge in the presence of a shared communicative task (e.g., Carr et al, 2017;Kirby et al, 2015;Motamedi et al, 2019;Raviv et al, 2018;Saldana et al, 2019;Winters et al, 2018) or an artificial analog of such a task (Beckner et al, 2017;Kirby et al, 2008), neither of which was present in the two studies described by Carstensen et al (2015). One reason why learners might be biased toward simplicity is that, when learners are faced with understanding the world, the best strategy-given that they have no expectations about how the world is structured-is to apply Occam's razor; all things being equal, simpler hypotheses should be preferred over more complex ones (Li & Vitányi, 2008;Rissanen, 1978;Solomonoff, 1964).…”

Section: )mentioning

confidence: 97%

Simplicity and informativeness in semantic category systems

et al. 2020

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Recent research has shown that semantic category systems, such as color and kinship terms, find an optimal balance between simplicity and informativeness. We argue that this situation arises through pressure for simplicity from learning and pressure for informativeness from communicative interaction, two distinct pressures that often (but not always) pull in opposite directions. Another account argues that learning might also act as a pressure for informativeness, that learners might be biased toward inferring informative systems. This results in two competing hypotheses about the human inductive bias. We formalize these competing hypotheses in a Bayesian iterated learning model in order to simulate what kinds of languages are expected to emerge under each. We then test this model experimentally to investigate whether learners' biases, isolated from any communicative task, are better characterized as favoring simplicity or informativeness. We find strong evidence to support the simplicity account. Furthermore, we show how the application of a simplicity principle in learning can give the impression of a bias for informativeness, even when no such bias is present. Our findings suggest that semantic categories are learned through domain-general principles, negating the need to posit a domain-specific mechanism.

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Section: )mentioning

confidence: 97%

Simplicity and informativeness in semantic category systems

et al. 2020

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“…(2017) or Saldana et al. (2019), much larger sets of signals were presented three times each. Again, methodological feasibility seems to determine the overall amount of training, but these different training regimens make it difficult to disentangle the effects of presentation frequency from effects of structural complexity.…”

Section: Combinatorial and Compositional Structurementioning

confidence: 99%

Amount of Learning and Signal Stability Modulate Emergence of Structure and Iconicity in Novel Signaling Systems

et al. 2021

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Iterated language learning experiments that explore the emergence of linguistic structure in the laboratory vary considerably in methodological implementation, limiting the generalizability of findings. Most studies also restrict themselves to exploring the emergence of combinatorial and compositional structure in isolation. Here, we use a novel signal space comprising binary auditory and visual sequences and manipulate the amount of learning and temporal stability of these signals. Participants had to learn signals for meanings differing in size, shape, and brightness; their productions in the test phase were transmitted to the next participant. Across transmission chains of 10 generations each, Experiment 1 varied how much learning of auditory signals took place, and Experiment 2 varied temporal stability of visual signals. We found that combinatorial structure emerged only for auditory signals, and iconicity emerged when the amount of learning was reduced, as an opportunity for rote‐memorization hampers the exploration of the iconic affordances of the signal space. In addition, compositionality followed an inverted u‐shaped trajectory raising across several generations before declining again toward the end of the transmission chains. This suggests that detection of systematic form‐meaning linkages requires stable combinatorial units that can guide learners toward the structural properties of signals, but these combinatorial units had not yet emerged in these unfamiliar systems. Our findings underscore the importance of systematically manipulating training conditions and signal characteristics in iterated language learning experiments to study the interactions between the emergence of iconicity, combinatorial and compositional structure in novel signaling systems.

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“…Whereas some researchers insist that symbol-trained apes have basically no understanding of ordering principles in communicative utterances at all (e.g. Terrace et al, 1979;Anderson, 2006), other researchers have presented evidence that apes such as Kanzi at least possess some kind of ordering structure in comprehension and production and at least minimal grammatical competence, possibly even some kind of semantic ordering principles (Rumbaugh et al, 1993;Hurford, 2012;Hurford, 2012;Lyn, 2012). There also has been keen interest in studying artificial grammar learning in a wide range of animals, especially birds and primates (see, e.g., ten Cate, 2017; ten Cate & Petkov, 2019 for reviews).…”

Section: Artificial Communication Systemsmentioning

confidence: 99%

Construction grammar for monkeys?

Pleyer

Hartmann

2020

ELT

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In recent years, multiple researchers working on the evolution of language have put forward the idea that the theoretical framework of usage-based approaches and Construction Grammar is highly suitable for modelling the emergence of human language from pre-linguistic or proto-linguistic communication systems. This also raises the question of whether usage-based and constructionist approaches can be integrated with the analysis of animal communication systems. In this paper, we review possible avenues where usage-based, constructionist approaches can make contact with animal communication research, which in turn also has implications for theories of language evolution. To this end, we first give an overview of key assumptions of usage-based and constructionist approaches before reviewing some key issues in animal communication research through the lens of usage-based, constructionist approaches. Specifically, we will discuss how research on alarm calls, gestural communication and symbol-trained animals can be brought into contact with usage-based, constructionist theorizing. We argue that a constructionist view of animal communication can yield new perspectives on its relation to human language, which in turn has important implications regarding the evolution of language. Importantly, this theoretical approach also generates hypotheses that have the potential of complementing and extending results from the more formalist approaches that often underlie current animal communication research.

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Compositional Hierarchical Structure Evolves through Cultural Transmission: An Experimental Study

Cited by 13 publications

References 60 publications

Simplicity and informativeness in semantic category systems

Simplicity and informativeness in semantic category systems

Amount of Learning and Signal Stability Modulate Emergence of Structure and Iconicity in Novel Signaling Systems

Construction grammar for monkeys?

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