1st Edition

Agent-Based Modeling and Simulation with Swarm

By Hitoshi Iba Copyright 2013
    317 Pages 11 Color & 192 B/W Illustrations
    by Chapman & Hall

    326 Pages 11 Color & 192 B/W Illustrations
    by Chapman & Hall

    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.

    What is simulation?
    Simulation of intelligence
    Criticism of simulation
    Swarm and the Santa Fe Institute

    Evolutionary Methods and Evolutionary Computation
    What is evolutionary computation?
    What are genetic algorithms?
    What is genetic programming?
    What is interactive evolutionary computation?

    Multi-Agent Simulation Based on Swarm
    Overview of Swarm

    Evolutionary Simulation
    Simulation of sexual selection
    Swarm-based simulation of sexual selection
    Simulation of the prisoner’s dilemma
    Evolving artificial creatures and artificial life

    Ant Colony-Based Simulation
    Collective behaviors of ants
    Swarm simulation of the pheromone trails of ants
    Ant colony optimization (ACO)
    Ant-clustering algorithms
    Swarm-based simulation of ant-clustering
    Ant colony-based approach to the network routing problem
    Ant-based job separation
    Emergent cooperation of army ants

    Particle Swarm Simulation
    Boids and flocking behaviors
    Simulating boids with Swarm
    Swarm chemistry
    PSO: particle swarm optimization
    ABC algorithm
    BUGS: a bug-based search strategy
    BUGS in Swarm

    Cellular Automata Simulation
    Game of life
    Conway class with Swarm
    Program that replicates itself
    Simulating forest fires with Swarm
    Segregation model simulation with Swarm
    Lattice gas automaton
    Turing model and morphogenesis simulation
    Simulating percolation with Swarm
    Silicon traffic and its control
    The world of Sugarscape


    Appendix A: GUI Systems and Source Code
    Appendix B: Installing Swarm



    Swarm Index

    Name Index


    Hitoshi Iba

    "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