Abstract
In this chapter, key findings presented in this volume are summarised and evaluated to demonstrate the usefulness and great potential of the adaptive dynamical system approach based on self-modeling networks in providing a useful structure to formalise, analyse and simulate multilevel organisational learning processes. Moreover, future perspectives are discussed for further development and application based on what already has been achieved.
| Original language | English |
|---|---|
| Title of host publication | Computational Modeling of Multilevel Organisational Learning and its Control Using Self-Modeling Network Models |
| Editors | Gülay Canbaloğlu, Jan Treur, Anna Wiewiora |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Chapter | 18 |
| Pages | 505-511 |
| Number of pages | 7 |
| ISBN (Electronic) | 9783031287350 |
| ISBN (Print) | 9783031287343, 9783031287374 |
| DOIs | |
| Publication status | Published - 2023 |
Publication series
| Name | Studies in Systems, Decision and Control |
|---|---|
| Publisher | Springer |
| Volume | 468 |
| ISSN (Print) | 2198-4182 |
| ISSN (Electronic) | 2198-4190 |
Bibliographical note
Publisher Copyright:© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Keywords
- Adaptive dynamical systems
- Computational modeling
- Multilevel organisational learning
- Self-modeling networks
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