Titlebook: Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental ; Jan Treur Book 2020 Springer Nature

预测

Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental 978-3-030-31445-3Series ISSN 2198-4182 Series E-ISSN 2198-4190

Osmosis

reflection

和蔼

Modeling Higher-Order Network Adaptation by Multilevel Network Reificationation states representing the characteristics of the structure of the base network (Connectivity, Aggregation, and Timing). In Chap. ., it was shown how this construction can be used to explicitly represent network adaptation principles within a network. In the current chapter, it is discussed how,

易怒

On the Universal Combination Function and the Universal Difference Equation for Reified Temporal-Cauy useful to model multiple orders of adaptation. Moreover, as shown in Chap. ., the universal difference equation enables that software of a very compact form can be developed, as all reification levels are handled by one computational reified network engine in the same manner. Alternatively, it is

思想上升

Lice692

软弱

Book 2020ess, too, is modeled in a neat, declarative, and conceptually transparent Network-OrientedModeling manner, like the network itself. Thanks to this approach, no procedural, algorithmic, or programming skills are needed to design complex adaptive network models. A dedicated software environment is ava

清澈

ing of midwives is of fundamental importance when considering safe maternity care. In this context, the rest of the chapter details the ASSET model that was derived from the research findings. This model features personal and system-level responsibilities to understand what midwives need to support

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