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Agent-Based Modeling and Simulation with Swarm

By Hitoshi Iba

Chapman and Hall/CRC – 2013 – 317 pages

Series: Chapman & Hall/CRC Studies in Informatics Series

Purchasing Options:

  • Add to CartHardback: $119.95
    978-1-46-656234-9
    June 24th 2013

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.

Contents

Introduction

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

Tutorial

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

Conclusion

Appendix A: GUI Systems and Source Code

Appendix B: Installing Swarm

References

Index

Swarm Index

Name Index

Name: Agent-Based Modeling and Simulation with Swarm (Hardback)Chapman and Hall/CRC 
Description: By Hitoshi Iba. 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...
Categories: Machine Learning, Algorithms & Complexity, Intelligent Systems