Multidisciplinary learning through collective performance favors decentralization

Many models of learning in teams assume that team members can share solutions or learn concurrently. However, these assumptions break down in multidisciplinary teams where team members often complete distinct, interrelated pieces of larger tasks. Such contexts make it difficult for individuals to se...

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Veröffentlicht in:	arXiv.org 2023-08
Hauptverfasser:	Meluso, John, Hébert-Dufresne, Laurent
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Multiagent Systems Computer Science - Social and Information Networks Learning Multidisciplinary teams Physics - Adaptation and Self-Organizing Systems Physics - Physics and Society Searching Teams
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