Bayesian computation and mechanism: Theoretical pluralism drives scientific emergence

David K. Sewell; Daniel R. Little; Stephan Lewandowsky

doi:10.1017/S0140525X11000392

Bayesian computation and mechanism: Theoretical pluralism drives scientific emergence

David K. Sewell^*, Daniel R. Little, Stephan Lewandowsky

^*Corresponding author for this work

Research output: Contribution to journal › Editorial (Academic Journal) › peer-review

Abstract

The breadth-first search adopted by Bayesian researchers to map out the conceptual space and identify what the framework can do is beneficial for science and reflective of its collaborative and incremental nature. Theoretical pluralism among researchers facilitates refinement of models within various levels of analysis, which ultimately enables effective cross-talk between different levels of analysis.

Original language	English
Pages (from-to)	212-+
Number of pages	3
Journal	Behavioral and Brain Sciences
Volume	34
Issue number	4
DOIs	https://doi.org/10.1017/S0140525X11000392
Publication status	Published - Aug 2011

Structured keywords

Memory

Keywords

INDUCTIVE BIASES
EXEMPLAR MODELS
ET-AL.
KNOWLEDGE
CATEGORIZATION
COGNITION

Access to Document

10.1017/S0140525X11000392

Cite this

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title = "Bayesian computation and mechanism: Theoretical pluralism drives scientific emergence",

abstract = "The breadth-first search adopted by Bayesian researchers to map out the conceptual space and identify what the framework can do is beneficial for science and reflective of its collaborative and incremental nature. Theoretical pluralism among researchers facilitates refinement of models within various levels of analysis, which ultimately enables effective cross-talk between different levels of analysis.",

keywords = "INDUCTIVE BIASES, EXEMPLAR MODELS, ET-AL., KNOWLEDGE, CATEGORIZATION, COGNITION",

author = "Sewell, {David K.} and Little, {Daniel R.} and Stephan Lewandowsky",

year = "2011",

month = aug,

doi = "10.1017/S0140525X11000392",

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volume = "34",

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journal = "Behavioral and Brain Sciences",

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AU - Sewell, David K.

AU - Little, Daniel R.

AU - Lewandowsky, Stephan

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N2 - The breadth-first search adopted by Bayesian researchers to map out the conceptual space and identify what the framework can do is beneficial for science and reflective of its collaborative and incremental nature. Theoretical pluralism among researchers facilitates refinement of models within various levels of analysis, which ultimately enables effective cross-talk between different levels of analysis.

AB - The breadth-first search adopted by Bayesian researchers to map out the conceptual space and identify what the framework can do is beneficial for science and reflective of its collaborative and incremental nature. Theoretical pluralism among researchers facilitates refinement of models within various levels of analysis, which ultimately enables effective cross-talk between different levels of analysis.

KW - INDUCTIVE BIASES

KW - EXEMPLAR MODELS

KW - ET-AL.

KW - KNOWLEDGE

KW - CATEGORIZATION

KW - COGNITION

U2 - 10.1017/S0140525X11000392

DO - 10.1017/S0140525X11000392

M3 - Editorial (Academic Journal)

VL - 34

SP - 212-+

JO - Behavioral and Brain Sciences

JF - Behavioral and Brain Sciences

SN - 0140-525X

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ER -