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Cognitive Agent-based Computing-I [electronic resource] : A Unified Framework for Modeling Complex Adaptive Systems using Agent-based & Complex Network-based Methods / by Muaz A Niazi, Amir Hussain.

By: Contributor(s): Material type: TextTextSeries: SpringerBriefs in Cognitive Computation ; 1Publisher: Dordrecht : Springer Netherlands : Imprint: Springer, 2013Description: XIV, 55 p. 9 illus., 7 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9789400738522
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 612.8 23
LOC classification:
  • RC321-580
Online resources: In: Springer eBooksSummary: Complex Systems are made up of numerous interacting sub-components. Non-linear interactions of these components or agents give rise to emergent behavior observable at the global scale. Agent-based modeling and simulation is a proven paradigm which has previously been used for effective computational modeling of complex systems in various domains. Because of its popular use across different scientific domains, research in agent-based modeling has primarily been vertical in nature. The goal of this book is to provide a single hands-on guide to developing cognitive agent-based models for the exploration of emergence across various types of complex systems. We present practical ideas and examples for researchers and practitioners for the building of agent-based models using a horizontal approach - applications are demonstrated in a number of exciting domains as diverse as wireless sensors networks, peer-to-peer networks, complex social systems, research networks and epidemiological HIV.
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Complex Systems are made up of numerous interacting sub-components. Non-linear interactions of these components or agents give rise to emergent behavior observable at the global scale. Agent-based modeling and simulation is a proven paradigm which has previously been used for effective computational modeling of complex systems in various domains. Because of its popular use across different scientific domains, research in agent-based modeling has primarily been vertical in nature. The goal of this book is to provide a single hands-on guide to developing cognitive agent-based models for the exploration of emergence across various types of complex systems. We present practical ideas and examples for researchers and practitioners for the building of agent-based models using a horizontal approach - applications are demonstrated in a number of exciting domains as diverse as wireless sensors networks, peer-to-peer networks, complex social systems, research networks and epidemiological HIV.

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