Co-evolution of Intelligent Socio-technical Systems : Modelling and Applications in Large Scale Emergency and Transport Domains. 1st ed. 2013

種類:

電子ブック

責任表示:

edited by Evangelia Mitleton-Kelly

出版情報:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013

著者名:

• Mitleton-Kelly, Evangelia.
• SpringerLink (Online service)

シリーズ名:

Understanding Complex Systems ;

ISBN:

9783642366147 [3642366147]    

注記:

Part I : Introduction and literature reviews -- The Socionical FP7 Project and an outline of the volume -- Enhancing Crowd Evacuation & Traffic Management, through AmI technologies - A Review of the Literature --  A The Concept of ‘Co-evolution’ and its Application in the Social Sciences – A Review of the literature -- Part II: EMERGENCY -- Using mobile technology and a participatory sensing approach for crowd monitoring during large-scale mass gatherings -- Agent-based Modelling of Social Emotional Decision Making in Emergency Situations,- Designing Complex Socio-technical Systems: Empirically Grounded Simulations as Tools for Experience-based Design Space Explorations -- Part III:  TRANSPORT -- Enhancing Future Mass ICT with Social Capabilities -- Emerging Phenomena During Driving Interactions -- Effective Assessment of AmI Intervention in Traffic Through Quantitative Measures -- Part IV: CITY SCALE -- City Scale Evacuation Simulation: A High-Performance Multi-Agent Simulation Framework.
As the interconnectivity between humans through technical devices is becoming ubiquitous, the next step is already in the making: ambient intelligence, i.e. smart (technical) environments, which will eventually play the same active role in communication as the human players, leading to a co-evolution in all domains where real-time communication is essential. This topical volume, based on the findings of the Socionical European research project, gives equal attention to two highly relevant domains of applications: transport, specifically traffic, dynamics from the viewpoint of a socio-technical interaction and evacuation scenarios for large-scale emergency situations. Care was taken to investigate as much as possible the limits of scalability and to combine the modeling using complex systems science approaches with relevant data analysis.

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