Two ways into complexity
Publication year
2016Author(s)
Publisher
Cham : Springer
Series
Lecture Notes in Morphogenesis
ISBN
9783319294810
In
La Mantia, F.; Licata, I.; Perconti, P. (ed.), Language in complexity: The emergence of meaning, pp. 148-158Publication type
Part of book or chapter of book
Display more detailsDisplay less details
Editor(s)
La Mantia, F.
Licata, I.
Perconti, P.
Organization
SW OZ DCC AI
Languages used
English (eng)
Book title
La Mantia, F.; Licata, I.; Perconti, P. (ed.), Language in complexity: The emergence of meaning
Page start
p. 148
Page end
p. 158
Subject
Lecture Notes in Morphogenesis; Cognitive artificial intelligence; DI-BCB_DCC_Theme 1: Language and CommunicationAbstract
The Dynamic Hypothesis (DH) about cognition has often been presented as an alternative to the widely popular Computational Hypothesis (CH) in cognitive science. While the theoretical distance that separates these two approaches may seem to be significant, there are rea-sons, we argue, to reconsider the relationship between the dynamical and computational ways of understanding cognition. Here we'll claim that CH and DH, rather than being competitors, are complementary framework in the explanation of cognition. This, we suggest, becomes evident when we consider that the two different notion of complexity that these hypothesis about cognition can be related to are very different indeed, but not contradictory. DH, we re-cognize, uses a notion of complexity derived from dynamical systems theory that seems to points toward psychological plausibility. On the other hand, CH may appeals to a computational notion of complexity that introduces elements of cognitive plausibility in the theoretical framework of cognitive science. In the following paragraphs, in order to test this last hypothe-sis, we will proceed as follows:
First we will consider how the debate between dynamicists and computationalists, started in the first place and what are the main features of DH and of its notion of complexity;
Then we'll see how CH evolved and consider how complexity can be recognized inside the CH framework;
Then we will see how computational complexity applies to cognition by linking computa-tional tractability with cognitive plausibility;
In the end we will argue that if we take the two different notions of complexity by compari-son there are elements to consider them not adversary on the same ground, but as complemen-tary model of explanation.
This item appears in the following Collection(s)
- Academic publications [245262]
- Faculty of Social Sciences [30344]
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