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Titlebook: Computational Modeling of Multilevel Organisational Learning and Its Control Using Self-modeling Net; Gülay Canbalo?lu,Jan Treur,Anna Wiew

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樓主: sesamoiditis
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發(fā)表于 2025-3-25 03:35:02 | 只看該作者
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發(fā)表于 2025-3-25 09:30:45 | 只看該作者
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發(fā)表于 2025-3-25 13:32:08 | 只看該作者
https://doi.org/10.1007/978-3-7643-8710-5f learning mechanisms that can either promote or restrict the transfer of learning between the levels. This chapter introduces the reader to the notion of organisational learning and multilevel learning. It explains complexities of the learning processes within organisations and mechanisms that trig
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發(fā)表于 2025-3-25 18:43:24 | 只看該作者
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發(fā)表于 2025-3-25 22:21:01 | 只看該作者
, History of the Suizhou Meteorite,adaptation. Metacognition is applied to control use and adaptating in a context-sensitive manner. In this chapter, a second-order adaptive network model for handling mental models, covering their use, adaptation and control, is discussed and used to illustrate these processes.
26#
發(fā)表于 2025-3-26 02:55:29 | 只看該作者
Interaktionsprobleme mit Suizidentenea of organisational learning. It is discussed how various conceptual mechanisms in multilevel organisational learning as identified in the literature, can be formalised by computational mechanisms which provide mathematical formalisations that enable computer simulation. The formalisations have bee
27#
發(fā)表于 2025-3-26 08:02:04 | 只看該作者
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發(fā)表于 2025-3-26 09:57:49 | 只看該作者
Interaktionsprobleme mit Suizidentenearning in team-related performances. The chapter describes the value of using shared mental models to illustrate the concept of organisational learning, and factors that influence team performances by using the analogy of a team of match officials during a game of football and show their behavior i
29#
發(fā)表于 2025-3-26 13:14:00 | 只看該作者
30#
發(fā)表于 2025-3-26 19:22:09 | 只看該作者
https://doi.org/10.1007/978-3-642-68093-9. This aggregation process usually does not only depend on the mental models used as input for it, but also on several context factors that may vary over circumstances and time. This means that for computational modeling of organisational learning the aggregation process better can be modeled as an
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