£127.06

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£127 today · previous high £127 · all-time low £103

Springer Computational Modeling Multilevel Organisational Learning - AI Systems

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£127.06 £100.59 £106.37 £112.14 £117.92 £123.69 £129.47 28 July 2026 14 August 2026 01 September 2026 19 September 2026 07 October 2026
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Description

This advanced text explores computational approaches to modelling multilevel organisational learning through self-modeling network models, offering researchers and practitioners a comprehensive framework for understanding complex adaptive systems within organisations. Part of Springer's authoritative Studies in Systems, Decision and Control series (volume 468), the book bridges artificial intelligence, systems theory, and organisational behaviour by presenting sophisticated mathematical and computational techniques for capturing how learning emerges across multiple hierarchical levels within institutional settings. The work addresses critical challenges in designing control mechanisms for dynamic organisational environments, making it essential for computer scientists, systems engineers, and organisational researchers seeking to apply cutting-edge AI methodologies to real-world learning systems. Through detailed analysis of self-modeling network architectures, the publication provides both theoretical foundations and practical applications for professionals working in artificial intelligence, adaptive systems, and organisational development.

Key Features

Explores self-modeling network models applied to organisational learning across multiple hierarchical levels within modern institutions.

Published by Springer as volume 468 in the Studies in Systems, Decision and Control series, ensuring peer-reviewed academic rigour.

Integrates computational modelling techniques with organisational theory to address complex adaptive systems and control mechanisms.

Provides advanced methodologies for artificial intelligence researchers and systems engineers working on adaptive organisational frameworks.

Offers both theoretical foundations and practical applications relevant to AI, systems design, and institutional learning development.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
17 June 2023
Listed Since
21 February 2023

Barcode

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