Data assimilation in dynamical cognitive science
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Data assimilation in dynamical cognitive science. / Engbert, Ralf; Rabe, Maximilian M.; Schwetlick, Lisa; Seelig, Stefan A.; Reich, Sebastian; Vasishth, Shravan.
In: Trends in Cognitive Sciences, Vol. 26, No. 2, 02.2022, p. 99-102.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Data assimilation in dynamical cognitive science
AU - Engbert, Ralf
AU - Rabe, Maximilian M.
AU - Schwetlick, Lisa
AU - Seelig, Stefan A.
AU - Reich, Sebastian
AU - Vasishth, Shravan
N1 - Funding Information: This work was supported by Deutsche Forschungsgemeinschaft (DFG) via Collaborative Research Centers SFB 1294 , Project-ID 318763901 , and SFB 1287 , Project-ID 317633480 . Publisher Copyright: © 2021 Elsevier Ltd
PY - 2022/2
Y1 - 2022/2
N2 - Dynamical models make specific assumptions about cognitive processes that generate human behavior. In data assimilation, these models are tested against time-ordered data. Recent progress on Bayesian data assimilation demonstrates that this approach combines the strengths of statistical modeling of individual differences with the those of dynamical cognitive models.
AB - Dynamical models make specific assumptions about cognitive processes that generate human behavior. In data assimilation, these models are tested against time-ordered data. Recent progress on Bayesian data assimilation demonstrates that this approach combines the strengths of statistical modeling of individual differences with the those of dynamical cognitive models.
KW - data assimilation
KW - dynamical cognitive models
KW - sequential likelihood
UR - http://www.scopus.com/inward/record.url?scp=85122132751&partnerID=8YFLogxK
U2 - 10.1016/j.tics.2021.11.006
DO - 10.1016/j.tics.2021.11.006
M3 - Journal article
C2 - 34972646
AN - SCOPUS:85122132751
VL - 26
SP - 99
EP - 102
JO - Trends in Cognitive Sciences
JF - Trends in Cognitive Sciences
SN - 1364-6613
IS - 2
ER -
ID: 389895029