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Achieving Consensus in Robot Swarms

Design and Analysis of Strategies for the best-of-n Problem

  • Gabriele Valentini

Part of the Studies in Computational Intelligence book series (SCI, volume 706)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Gabriele Valentini
    Pages 1-5
  3. Background and Methodology

    1. Front Matter
      Pages 7-7
  4. Mathematical Modeling and Analysis

    1. Front Matter
      Pages 53-53
    2. Gabriele Valentini
      Pages 55-66
    3. Gabriele Valentini
      Pages 67-83
    4. Gabriele Valentini
      Pages 85-101
  5. Robot Experiments

    1. Front Matter
      Pages 103-103
    2. Gabriele Valentini
      Pages 105-117
    3. Gabriele Valentini
      Pages 119-131
  6. Discussion and Annexes

    1. Front Matter
      Pages 133-133
    2. Gabriele Valentini
      Pages 135-141
  7. Back Matter
    Pages 143-146

About this book

Introduction

This book focuses on the design and analysis of collective decision-making strategies for the best-of-n problem. After providing a formalization of the structure of the best-of-n problem supported by a comprehensive survey of the swarm robotics literature, it introduces the functioning of a collective decision-making strategy and identifies a set of mechanisms that are essential for a strategy to solve the best-of-n problem. The best-of-n problem is an abstraction that captures the frequent requirement of a robot swarm to choose one option from of a finite set when optimizing benefits and costs. The book leverages the identification of these mechanisms to develop a modular and model-driven methodology to design collective decision-making strategies and to analyze their performance at different level of abstractions. Lastly, the author provides a series of case studies in which the proposed methodology is used to design different strategies, using robot experiments to show how the designed strategies can be ported to different application scenarios.

Keywords

Computational Intelligence Decisions for Robot Swarms Finite Optimal Solution Self-Organization Collective Decision-making

Authors and affiliations

  • Gabriele Valentini
    • 1
  1. 1.Arizona State UniversitySchool of Earth and Space Exploration Arizona State UniversityTempe AZUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-53609-5
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-53608-8
  • Online ISBN 978-3-319-53609-5
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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