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Cambier, N., Miletitch, R., Burraco, A. B., & Raviv, L. (2022). Prosociality in swarm robotics: A model to study self-domestication and language evolution. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (
Eds. ), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 98-100). Nijmegen: Joint Conference on Language Evolution (JCoLE). -
Raviv, L., Lupyan, G., & Green, S. C. (2022). How variability shapes learning and generalization. Trends in Cognitive Sciences, 26(6), 462-483. doi:10.1016/j.tics.2022.03.007.
Abstract
Learning is using past experiences to inform new behaviors and actions. Because all experiences are unique, learning always requires some generalization. An effective way of improving generalization is to expose learners to more variable (and thus often more representative) input. More variability tends to make initial learning more challenging, but eventually leads to more general and robust performance. This core principle has been repeatedly rediscovered and renamed in different domains (e.g., contextual diversity, desirable difficulties, variability of practice). Reviewing this basic result as it has been formulated in different domains allows us to identify key patterns, distinguish between different kinds of variability, discuss the roles of varying task-relevant versus irrelevant dimensions, and examine the effects of introducing variability at different points in training. -
Raviv, L., Jacobson, S. L., Plotnik, J. M., Bowman, J., Lynch, V., & Benítez-Burraco, A. (2022). Elephants as a new animal model for studying the evolution of language as a result of self-domestication. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (
Eds. ), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 606-608). Nijmegen: Joint Conference on Language Evolution (JCoLE). -
Raviv, L., Peckre, L. R., & Boeckx, C. (2022). What is simple is actually quite complex: A critical note on terminology in the domain of language and communication. Journal of Comparative Psychology, 136(4), 215-220. doi:10.1037/com0000328.
Abstract
On the surface, the fields of animal communication and human linguistics have arrived at conflicting theories and conclusions with respect to the effect of social complexity on communicative complexity. For example, an increase in group size is argued to have opposite consequences on human versus animal communication systems: although an increase in human community size leads to some types of language simplification, an increase in animal group size leads to an increase in signal complexity. But do human and animal communication systems really show such a fundamental discrepancy? Our key message is that the tension between these two adjacent fields is the result of (a) a focus on different levels of analysis (namely, signal variation or grammar-like rules) and (b) an inconsistent use of terminology (namely, the terms “simple” and “complex”). By disentangling and clarifying these terms with respect to different measures of communicative complexity, we show that although animal and human communication systems indeed show some contradictory effects with respect to signal variability, they actually display essentially the same patterns with respect to grammar-like structure. This is despite the fact that the definitions of complexity and simplicity are actually aligned for signal variability, but diverge for grammatical structure. We conclude by advocating for the use of more objective and descriptive terms instead of terms such as “complexity,” which can be applied uniformly for human and animal communication systems—leading to comparable descriptions of findings across species and promoting a more productive dialogue between fields. -
Raviv, L., & Arnon, I. (2016). The developmental trajectory of children's statistical learning abilities. In A. Papafragou, D. Grodner, D. Mirman, & J. Trueswell (
Eds. ), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (CogSci 2016). Austin, TX: Cognitive Science Society (pp. 1469-1474). Austin, TX: Cognitive Science Society.Abstract
Infants, children and adults are capable of implicitly extracting regularities from their environment through statistical learning (SL). SL is present from early infancy and found across tasks and modalities, raising questions about the domain generality of SL. However, little is known about its’ developmental trajectory: Is SL fully developed capacity in infancy, or does it improve with age, like other cognitive skills? While SL is well established in infants and adults, only few studies have looked at SL across development with conflicting results: some find age-related improvements while others do not. Importantly, despite its postulated role in language learning, no study has examined the developmental trajectory of auditory SL throughout childhood. Here, we conduct a large-scale study of children's auditory SL across a wide age-range (5-12y, N=115). Results show that auditory SL does not change much across development. We discuss implications for modality-based differences in SL and for its role in language acquisition.Additional information
https://mindmodeling.org/cogsci2016/papers/0260/index.html -
Raviv, L., & Arnon, I. (2016). Language evolution in the lab: The case of child learners. In A. Papagrafou, D. Grodner, D. Mirman, & J. Trueswell (
Eds. ), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (CogSci 2016). Austin, TX: Cognitive Science Society (pp. 1643-1648). Austin, TX: Cognitive Science Society.Abstract
Recent work suggests that cultural transmission can lead to the emergence of linguistic structure as speakers’ weak individual biases become amplified through iterated learning. However, to date, no published study has demonstrated a similar emergence of linguistic structure in children. This gap is problematic given that languages are mainly learned by children and that adults may bring existing linguistic biases to the task. Here, we conduct a large-scale study of iterated language learning in both children and adults, using a novel, child-friendly paradigm. The results show that while children make more mistakes overall, their languages become more learnable and show learnability biases similar to those of adults. Child languages did not show a significant increase in linguistic structure over time, but consistent mappings between meanings and signals did emerge on many occasions, as found with adults. This provides the first demonstration that cultural transmission affects the languages children and adults produce similarly.Additional information
https://mindmodeling.org/cogsci2016/papers/0289/index.html
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