Biological evolution’s use of representational redescription

2021 ◽  
pp. 76-93
Author(s):  
Aaron Sloman
Keyword(s):  
Representational Redescription

scholarly journals Representational redescription and cognitive architectures

1994 ◽  
Vol 17 (4) ◽  
pp. 711-712 ◽  
Author(s):  
Antonella Carassa ◽  
Maurizio Tirassa
Keyword(s):  
Cognitive Architectures ◽  
Representational Redescription

Promissory notes, genetic clocks, and epigenetic outcomes

1997 ◽  
Vol 20 (2) ◽  
pp. 355-359 ◽  
Author(s):  
Annette Karmiloff-Smith
Keyword(s):  
Brain Development ◽  
Developmental Timing ◽  
Human Intelligence ◽  
Postnatal Brain ◽  
Genes And Environment ◽  
Representational Redescription

I respond to three continuing commentaries on Beyond modularity, two concerning the representational redescription (RR) framework and its attempts to account for the growing flexibility of human intelligence, and one relating to the putative mysteries of developmental timing. I discuss misunderstandings about the RR framework as well as some of its shortcomings. I strongly reject the notion of a genetic clock and go on to argue for epigenetic outcomes in which genes and environment interact during the protracted period of postnatal brain development.

Closing the symbolic reference gap to support flexible reasoning about the passage of time

2019 ◽  
Vol 42 ◽  
Author(s):  
Danielle DeNigris ◽  
Patricia J. Brooks
Keyword(s):  
Cognitive Development ◽  
Dual Systems ◽  
Developmental Processes ◽  
Time Line ◽  
Systems Perspective ◽  
Mental Time Line ◽  
Representational Redescription

Abstract This commentary relates Hoerl & McCormack's dual systems perspective to models of cognitive development emphasizing representational redescription and the role of culturally constructed tools, including language, in providing flexible formats for thinking. We describe developmental processes that enable children to construct a mental time line, situate themselves in time, and overcome the primacy of the here and now.

scholarly journals Relational learning re-examined

1997 ◽  
Vol 20 (1) ◽  
pp. 83-83
Author(s):  
Chris Thornton ◽  
Andy Clark
Keyword(s):  
Incremental Learning ◽  
Relational Learning ◽  
Learning Algorithms ◽  
Trade Off ◽  
Call Type ◽  
Computational Search ◽  
Representational Redescription

We argue that existing learning algorithms are often poorly equipped to solve problems involving a certain type of important and widespread regularity that we call “type-2 regularity.” The solution in these cases is to trade achieved representation against computational search. We investigate several ways in which such a trade-off may be pursued including simple incremental learning, modular connectionism, and the developmental hypothesis of “representational redescription.”

Sign in / Sign up

Export Citation Format

Share Document