Rights statement: This is the peer reviewed version of the following article:Rebuschat, P. and Monaghan, P. (2019), Editors’ Introduction: Aligning Implicit Learning and Statistical Learning: Two Approaches, One Phenomenon. Top Cogn Sci, 11: 459-467. doi:10.1111/tops.12438 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1111/tops.12438 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
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Final published version
Research output: Contribution to Journal/Magazine › Editorial › peer-review
Research output: Contribution to Journal/Magazine › Editorial › peer-review
}
TY - JOUR
T1 - Editors' introduction: Aligning implicit learning and statistical learning: Two approaches, one phenomenon
AU - Rebuschat, Patrick
AU - Monaghan, Padraic
N1 - This is the peer reviewed version of the following article:Rebuschat, P. and Monaghan, P. (2019), Editors’ Introduction: Aligning Implicit Learning and Statistical Learning: Two Approaches, One Phenomenon. Top Cogn Sci, 11: 459-467. doi:10.1111/tops.12438 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1111/tops.12438 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
PY - 2019/7/23
Y1 - 2019/7/23
N2 - In their editors’ introduction, Rebuschat and Monaghan provide the background to the special issue. They outline the rationale for bringing together, in a single volume, leading researchers from two distinct, yet related research strands,implicit learning and statistical learning. The editors then introduce the new contributions solicited for this special issueand provide their perspective on the agenda setting that results from combining these two approaches.
AB - In their editors’ introduction, Rebuschat and Monaghan provide the background to the special issue. They outline the rationale for bringing together, in a single volume, leading researchers from two distinct, yet related research strands,implicit learning and statistical learning. The editors then introduce the new contributions solicited for this special issueand provide their perspective on the agenda setting that results from combining these two approaches.
U2 - 10.1111/tops.12438
DO - 10.1111/tops.12438
M3 - Editorial
VL - 11
SP - 459
EP - 467
JO - Topics in Cognitive Science
JF - Topics in Cognitive Science
SN - 1756-8757
IS - 3
ER -