
Agent-Based Modeling and Simulation with Swarm
Hitoshi Iba(Author)
CRC Press
1st Edition
Published on 8. November 2016
Book
Paperback/Softback
326 pages
978-1-138-03370-2 (ISBN)
Description
Swarm-based multi-agent simulation leads to better modeling of tasks in biology, engineering, economics, art, and many other areas. It also facilitates an understanding of complicated phenomena that cannot be solved analytically. Agent-Based Modeling and Simulation with Swarm provides the methodology for a multi-agent-based modeling approach that integrates computational techniques such as artificial life, cellular automata, and bio-inspired optimization.
Each chapter gives an overview of the problem, explores state-of-the-art technology in the field, and discusses multi-agent frameworks. The author describes step by step how to assemble algorithms for generating a simulation model, program, method for visualization, and further research tasks. While the book employs the commonly used Swarm system, readers can model and develop the simulations with their own simulator. To encourage hands-on exploration of emergent systems, Swarm-based software and source codes are available for download from the author's website.
A thorough overview of multi-agent simulation and supporting tools, this book shows how this type of simulation is used to acquire an understanding of complex systems and artificial life. It carefully explains how to construct a simulation program for various applications.
Each chapter gives an overview of the problem, explores state-of-the-art technology in the field, and discusses multi-agent frameworks. The author describes step by step how to assemble algorithms for generating a simulation model, program, method for visualization, and further research tasks. While the book employs the commonly used Swarm system, readers can model and develop the simulations with their own simulator. To encourage hands-on exploration of emergent systems, Swarm-based software and source codes are available for download from the author's website.
A thorough overview of multi-agent simulation and supporting tools, this book shows how this type of simulation is used to acquire an understanding of complex systems and artificial life. It carefully explains how to construct a simulation program for various applications.
Reviews / Votes
"The book is very readable and contains great illustrations. Each chapter summarizes the problems addressed and the current state of the art, and eases into a detailed discussion on why agent-based modeling sheds new light on the topic at hand. The author performs a difficult task gracefully: he explains just enough for the reader to grasp the essence of a problem, while the bulk of the chapter is spent demonstrating the relevance of agent-based modeling in addressing it."-Klaus K. Obermeier, PhD, in Computing Reviews
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Researchers and graduate students in AI, machine learning, and evolutionary computation.
Illustrations
35 s/w Tabellen, 11 farbige Abbildungen, 192 s/w Abbildungen
35 Tables, black and white; 11 Illustrations, color; 192 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Weight
600 gr
ISBN-13
978-1-138-03370-2 (9781138033702)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Hitoshi Iba
Agent-Based Modeling and Simulation with Swarm
Book
06/2013
1st Edition
CRC Press
€255.50
Shipment within 15-20 days

Hitoshi Iba
Agent-Based Modeling and Simulation with Swarm
E-Book
06/2013
1st Edition
Chapman & Hall/CRC
€81.49
Available for download

Hitoshi Iba
Agent-Based Modeling and Simulation with Swarm
E-Book
06/2013
Chapman and Hall
€81.99
Available for download
Person
Content
Introduction. Evolutionary Methods and Evolutionary Computation. Multi-Agent Simulation Based on Swarm. Evolutionary Simulation. Ant Colony-Based Simulation. Particle Swarm Simulation. Cellular Automata Simulation. Conclusion. Appendices. References. Index.