Agent-Based Modeling and Simulation with Swarm

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A01=Hitoshi Iba
ABC Algorithm
Ac Ti
adaption of complex systems
Agent Based Modeling
algorithm
algorithms for a simulation model
and bio-inspired optimization
Army Ants
artificial life
Artificial Societies
Atm Network
Author_Hitoshi Iba
automata
Bad Initialization
bio-inspired computation
Category=UYM
cellular
Cellular Automata
cellular automata methods
Chain Formation System
complex systems modeling
computation
computational biology
emergent behavior simulation techniques
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
evolutionary
evolutionary algorithms
evolutionary computation
Gaussian Mutation
genetic
Initial Individuals
intelligence
Interactive GA
Midi Piano
multi-agent modeling
Non-terminal Nodes
Onlooker Bees
Pheromone Concentration
Pheromone Trail
problem
PSO Algorithm
PSO Search
Red Tribe
salesman
Santa Fe Institute
Simulated Breeding
Standard GP
swarm intelligence applications
Swarm-based multi-agent simulation
Swarm-based software
traveling
Traveling Salesman Problem
understanding complex systems and artificial life
White Cells

Product details

  • ISBN 9781466562349
  • Weight: 760g
  • Dimensions: 156 x 234mm
  • Publication Date: 24 Jun 2013
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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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.

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