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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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書目名稱Computational Modeling of Multilevel Organisational Learning and Its Control Using Self-modeling Net
編輯Gülay Canbalo?lu,Jan Treur,Anna Wiewiora
視頻videohttp://file.papertrans.cn/233/232819/232819.mp4
概述Shows mathematical formalisation and computational modeling of multilevel organisational learning in a systematic way.Includes several examples of realistic cases of multilevel organisational learning
叢書名稱Studies in Systems, Decision and Control
圖書封面Titlebook: Computational Modeling of Multilevel Organisational Learning and Its Control Using Self-modeling Net;  Gülay Canbalo?lu,Jan Treur,Anna Wiew
描述.Although there is much literature on organisational learning, mathematical formalisation and computational simulation, there is no literature that uses mathematical modelling and simulation to represent and explore different facets of multilevel learning. This book provides an overview of recent work on mathematical formalisation and computational simulation of multilevel organisational learning by exploiting the possibilities of self-modeling network models to address it.?...This isthe first book addressing mathematical formalisation and computationalmodeling of multilevel organisational learning in a systematic, principledmanner. ?..A self-modeling networkmodeling approach from AI and Network Science is used where in a reflectivemanner some of the network nodes (called self-model nodes) represent partsof the network’s own network structure characteristics.?..This is supported by adedicated software environment allowing to design and implement(higher-order) adaptive network models by specifying them in a conceptualmanner at a high level of abstraction in a standard table format, withoutany need of algorithmic specification or programming.?..This modeling approachallows to model t
出版日期Book 2023
關(guān)鍵詞Computational modeling; Organisational learning; Multilevel learning; Adaptation; Adaptive network model
版次1
doihttps://doi.org/10.1007/978-3-031-28735-0
isbn_softcover978-3-031-28737-4
isbn_ebook978-3-031-28735-0Series ISSN 2198-4182 Series E-ISSN 2198-4190
issn_series 2198-4182
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Using Self-modeling Networks to Model Organisational Learningg individual mental models (and making them explicit), a basis for formation of shared mental models for the level of the organisation is created, which after its formation can then be adopted by individuals. This provides mechanisms for organisational learning. These mechanisms have been used as a
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Organisational Learning and Usage of Mental Models for a Team of Match Officials: A Second-Order Adaearning 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
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Heuristic Context-Sensitive Control of Mental Model Aggregation for Multilevel Organisational Learnicess. 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 by adaptive networks, where the formation of a s
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Adaptive Mental Model Aggregation in Organisational Learning Using Boolean Propositions of Context F. 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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