Multi-Agent-Based Simulation XXIII

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Details

This book constitutes the thoroughly refereed and revised selected papers from the 22nd International Workshop on Multi-Agent-Based Simulation, MABS 2022, which took place virtually during May 89, 2022. The conference was originally planned to take place in Auckland, New Zealand, but had to change to an online format due to the COVID-19 pandemic.
The 11 papers included in these proceedings were carefully reviewed and selected from 17 submissions. They focus on finding efficient solutions to model complex social systems, in areas such as economics, management, organisational and social sciences in general.

Klappentext

Land use management using Multi-Agent Based Simulation in a watershed in south of the Brazil.- Replacing Method for Multi-Agent Crowd Simulation by Convolutional Neural Network.- An agent-based model of horizontal mergers.- The influence of national culture on evacuation response behaviour and time: An agent-based approach.- Simulating Work Teams using MBTI agents.- Reconsidering an Agent-Based Model of Food Web Evolution.- Surrogate Modeling of Agent-based Airport Terminal Operations.- School's Out? Simulating Schooling Strategies During COVID-19.- Generating Explanatory Saliency Maps for Mixed Traffic Flow using a Behaviour Cloning Model.- Challenges for Multi-Agent Based Agricultural Workforce Management.- Agents dealing with Norms and Regulations.


Inhalt
Land use management using Multi-Agent Based Simulation in a watershed in south of the Brazil.- Replacing Method for Multi-Agent Crowd Simulation by Convolutional Neural Network.- An agent-based model of horizontal mergers.- The influence of national culture on evacuation response behaviour and time: An agent-based approach.- Simulating Work Teams using MBTI agents.- Reconsidering an Agent-Based Model of Food Web Evolution.- Surrogate Modeling of Agent-based Airport Terminal Operations.- School's Out? Simulating Schooling Strategies During COVID-19.- Generating Explanatory Saliency Maps for Mixed Traffic Flow using a Behaviour Cloning Model.- Challenges for Multi-Agent Based Agricultural Workforce Management.- Agents dealing with Norms and Regulations.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783031229466
    • Genre Information Technology
    • Auflage 1st ed. 2023
    • Editor Fabian Lorig, Emma Norling
    • Lesemotiv Verstehen
    • Anzahl Seiten 147
    • Größe H8mm x B155mm x T235mm
    • Jahr 2023
    • EAN 9783031229466
    • Format Kartonierter Einband
    • ISBN 978-3-031-22946-6
    • Titel Multi-Agent-Based Simulation XXIII
    • Untertitel 23rd International Workshop, MABS 2022, Virtual Event, May 8-9, 2022, Revised Selected Papers
    • Herausgeber Springer
    • Sprache Englisch

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