Literature DB >> 25497482

Manifesto for a new (computational) cognitive revolution.

Thomas L Griffiths1.   

Abstract

The cognitive revolution offered an alternative to merely analyzing human behavior, using the notion of computation to rigorously express hypotheses about the mind. Computation also gives us new tools for testing these hypotheses - large behavioral databases generated by human interactions with computers and with one another. This kind of data is typically analyzed by computer scientists, who focus on predicting people's behavior based on their history. A new cognitive revolution is needed, demonstrating the value of minds as intervening variables in these analyses and using the results to evaluate models of human cognition.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Big data; Computational modeling; Crowdsourcing

Mesh:

Year:  2014        PMID: 25497482     DOI: 10.1016/j.cognition.2014.11.026

Source DB:  PubMed          Journal:  Cognition        ISSN: 0010-0277


  17 in total

1.  Structured, uncertainty-driven exploration in real-world consumer choice.

Authors:  Eric Schulz; Rahul Bhui; Bradley C Love; Bastien Brier; Michael T Todd; Samuel J Gershman
Journal:  Proc Natl Acad Sci U S A       Date:  2019-06-24       Impact factor: 11.205

2.  Scaling up psychology via Scientific Regret Minimization.

Authors:  Mayank Agrawal; Joshua C Peterson; Thomas L Griffiths
Journal:  Proc Natl Acad Sci U S A       Date:  2020-04-02       Impact factor: 11.205

3.  Inferring latent learning factors in large-scale cognitive training data.

Authors:  Mark Steyvers; Robert J Schafer
Journal:  Nat Hum Behav       Date:  2020-08-31

4.  Hidden processes in structural representations: A reply to Abbott, Austerweil, and Griffiths (2015).

Authors:  Michael N Jones; Thomas T Hills; Peter M Todd
Journal:  Psychol Rev       Date:  2015-07       Impact factor: 8.934

5.  Association and response accuracy in the wild.

Authors:  Sudeep Bhatia; Lukasz Walasek
Journal:  Mem Cognit       Date:  2019-02

Review 6.  Cognitive computational neuroscience.

Authors:  Nikolaus Kriegeskorte; Pamela K Douglas
Journal:  Nat Neurosci       Date:  2018-08-20       Impact factor: 24.884

7.  Context-dependent choice and evaluation in real-world consumer behavior.

Authors:  Aaron M Bornstein; Kenway Louie; A Ross Otto; Sean Devine; Eric Schulz
Journal:  Sci Rep       Date:  2022-10-22       Impact factor: 4.996

8.  Finding the traces of behavioral and cognitive processes in big data and naturally occurring datasets.

Authors:  Alexandra Paxton; Thomas L Griffiths
Journal:  Behav Res Methods       Date:  2017-10

9.  Promises and pitfalls of Web-based experimentation in the advance of replicable psychological science: A reply to Plant (2015).

Authors:  Henk van Steenbergen; Bruno R Bocanegra
Journal:  Behav Res Methods       Date:  2016-12

10.  Compression in cultural evolution: Homogeneity and structure in the emergence and evolution of a large-scale online collaborative art project.

Authors:  Thomas F Müller; James Winters
Journal:  PLoS One       Date:  2018-09-05       Impact factor: 3.240

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