scholarly journals Sinking in: the peripheral Baldwinisation of human cognition

2020 ◽  
Author(s):  
cecilia heyes ◽  
Nick Chater ◽  
Dominic Michael Dwyer

The Baldwin effect is a hypothetical process in which a learned response to environmental change evolves a genetic basis. Modelling has shown that the Baldwin effect offers a plausible, elegant explanation for the emergence of complex behavioural traits but there is little direct empirical evidence of its occurrence. Here we highlight experimental evidence of the Baldwin effect and argue that it acts preferentially on peripheral rather than central cognitive processes. Careful scrutiny of research on taste aversion and fear learning, language and imitation, indicates that their efficiency depends on adaptively specialised input and output processes – analogues of scanner and printer interfaces that feed information to core inference processes and structure their behavioural expression.

2002 ◽  
Vol 8 (4) ◽  
pp. 311-339 ◽  
Author(s):  
Steve Munroe ◽  
Angelo Cangelosi

The Baldwin effect has been explicitly used by Pinker and Bloom as an explanation of the origins of language and the evolution of a language acquisition device. This article presents new simulations of an artificial life model for the evolution of compositional languages. It specifically addresses the role of cultural variation and of learning costs in the Baldwin effect for the evolution of language. Results show that when a high cost is associated with language learning, agents gradually assimilate in their genome some explicit features (e.g., lexical properties) of the specific language they are exposed to. When the structure of the language is allowed to vary through cultural transmission, Baldwinian processes cause, instead, the assimilation of a predisposition to learn, rather than any structural properties associated with a specific language. The analysis of the mechanisms underlying such a predisposition in terms of categorical perception supports Deacon's hypothesis regarding the Baldwinian inheritance of general underlying cognitive capabilities that serve language acquisition. This is in opposition to the thesis that argues for assimilation of structural properties needed for the specification of a full-blown language acquisition device.


2006 ◽  
Vol 1 (2) ◽  
pp. 206-208
Author(s):  
Linda Van Speybroeck ◽  
Gertrudis Van de Vijver

Author(s):  
Ranya Ahmed Rashid Shaheen, Abdelrahman Mudawi Abdelrahim Al Ranya Ahmed Rashid Shaheen, Abdelrahman Mudawi Abdelrahim Al

The object of inquiry in Linguistics is the human ability to acquire and use a natural language, and the goal of linguistic theory is an explicit characterization of that ability. Looking at the communicative abilities of other species, it becomes clear that our linguistic ability is specific to our species, undoubtedly a product of our biology. But how do we go about determining the specifics of this Language faculty? _here are two primary ways in which we infer the nature of Language from the properties of individual languages: arguments from the Poverty of the Stimulus, and the search for universals that characterize every natural language. Arguments of the first sort are not easy to construct (though not as difficult as sometimes suggested), and apply only to a tiny part of Language as a whole. Arguments from universals or typological generalizations are also quite problematic. In phonology, morphology, and syntax, factors of historical development, functional underpinnings, limitations of the learning situation, among others conspire to compromise the explanatory value of arguments from observed cross-linguistic regularities. Confounding the situation is the likelihood that properties found across languages as a consequence of such external forces have been incorporated into the Language faculty evolutionarily through the ‘Baldwin Effect.’ _e conflict between the biologically based specificity of the human Language faculty and the difficulty of establishing most of its properties in a secure way cannot, however, be avoided by ignoring or denying the reality of either of its poles.


Author(s):  
Ana Marques

A generative text is a system constituted by non-conscious and conscious cognizers, digital and analogue processes, and mathematical and linguistic modes of representation. But how do algorithms cognize? And how is meaning constructed in a system where authorial intentions and readers’ experiences and interpretations are mediated by algorithmic agents? Through the analysis of How It Is In Common Tongues (Cayley and Howe, 2012), I intend to discuss the tensions that arise from the encounter between algorithmic and human cognition, and between the regimes of information and expression. Drawing on Katherine Hayles’ view on the cognitive non-conscious and Claude Shannon’s information theory I will start by establishing a distinction between information and meaning, between communication and expression, and between the regimes of information and of the literary. To reflect on the political ecology of digital mediation (situated in the informational regime of cybernetics), I will consider Matteo Pasquinelli’s perspective on the co-evolution of technology and economics, and discuss how algorithmic cognitive processes embody and reinforce the structures of contemporary cognitive capitalism. Finally, I will discuss the strategies of resistance enabled by aesthetic approaches to computation, such as the ones explored in this case study.


2020 ◽  
Vol 904 (2) ◽  
pp. 162
Author(s):  
Hiroaki Sameshima ◽  
Yuzuru Yoshii ◽  
Noriyuki Matsunaga ◽  
Naoto Kobayashi ◽  
Yuji Ikeda ◽  
...  

2019 ◽  
Author(s):  
Joseph L. Austerweil ◽  
Shi Xian Liew ◽  
Nolan Bradley Conaway ◽  
Kenneth J. Kurtz

The ability to generate new concepts and ideas is among the most fascinating aspects of human cognition, but we do not have a strong understanding of the cognitive processes and representations underlying concept generation. In this paper, we study the generation of new categories using the computational and behavioral toolkit of traditional artificial category learning. Previous work in this domain has focused on how the statistical structure of known categories generalizes to generated categories, overlooking whether (and if so, how) contrast between the known and generated categories is a factor. We report three experiments demonstrating that contrast between what is known and what is created is of fundamental importance for categorization. We propose two novel approaches to modeling category contrast: one focused on exemplar dissimilarity and another on the representativeness heuristic. Our experiments and computational analyses demonstrate that both models capture different aspects of contrast’s role in categorization.


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