© 2012


Physics-Based Swarm Intelligence

  • William M. Spears
  • Diana F. Spears

Table of contents

  1. Front Matter
    Pages I-XXX
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. William M. Spears
      Pages 3-25
    3. William M. Spears
      Pages 27-53
    4. William M. Spears
      Pages 55-92
    5. William M. Spears
      Pages 93-125
  3. Robotic Swarm Applications

    1. Front Matter
      Pages 127-127
    2. Andrea Bravi, Paolo Corradi, Florian Schlachter, Arianna Menciassi
      Pages 129-144
    3. Christer Karlsson, Charles Lee Frey, Dimitri V. Zarzhitsky, Diana F. Spears, Edith A. Widder
      Pages 145-191
    4. Diana F. Spears, David R. Thayer, Dimitri V. Zarzhitsky
      Pages 223-249
  4. Physicomimetics on Hardware Robots

    1. Front Matter
      Pages 299-299
    2. Paul M. Maxim
      Pages 301-339
    3. Paul M. Maxim
      Pages 341-366
    4. Paul M. Maxim
      Pages 367-412
    5. Thomas B. Apker, Mitchell A. Potter
      Pages 413-437
  5. Prediction, Adaptation, and Swarm Engineering

    1. Front Matter
      Pages 439-439
    2. Diana F. Spears, Richard Anderson-Sprecher, Aleksey Kletsov, Antons Rebguns
      Pages 475-503

About this book


Standard approaches to understanding swarms rely on inspiration from biology and are generally covered by the term “biomimetics”. This book focuses on a different, complementary inspiration, namely physics. The editors have introduced the term "physicomimetics" to refer to physics-based swarm approaches, which offer two advantages. First, they capture the notion that “nature is lazy", meaning that physics-based systems always perform the minimal amount of work necessary, which is an especially important advantage in swarm robotics. Second, physics is the most predictive science, and can reduce complex systems to simple concepts and equations that codify emergent behavior and help us to design and understand swarms.


The editors consolidated over a decade of work on swarm intelligence and swarm robotics, organizing the book into 19 chapters as follows. Part I introduces the concept of swarms and offers the reader a physics tutorial; Part II deals with applications of physicomimetics, in order of increased complexity; Part III examines the hardware requirements of the presented algorithms and demonstrates real robot implementations; Part IV demonstrates how the theory can be used to design swarms from first principles and provides a novel algorithm that handles changing environments; finally, Part V shows that physicomimetics can be used for function optimization, moving the reader from issues of swarm robotics to swarm intelligence. The text is supported with a downloadable package containing simulation code and videos of working robots.


This book is suitable for talented high school and undergraduate students, as well as researchers and graduate students in the areas of artificial intelligence and robotics.


Adaptive learning Adaptive systems Agents Artificial physics Biomimetics Fluid physics Mimetics Optimization Physicomimetics Robots Swarm engineering Swarm robotics

Editors and affiliations

  • William M. Spears
    • 1
  • Diana F. Spears
    • 2
  1. 1.Swarmotics LLCLaramieUSA
  2. 2.Swarmotics LLCLaramieUSA

About the editors

Dr. William Spears is the CEO of Swarmotics LLC, a company that provides consulting expertise in distributed agents, sensing networks, artificial intelligence, machine learning, optimization, and swarm robotics; he was formerly a professor in the Dept. of Computer Science at the University of Wyoming, Laramie. Dr. Diana Spears was a professor in the Dept. of Computer Science at the University of Wyoming, Laramie, and is currently a director of Swarmotics, LLC.

Bibliographic information

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