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Evolving prediction machines: collective behaviors based on minimal surprisal

Published: 12 July 2014 Publication History

Abstract

No abstract available.

References

[1]
M. Brambilla, E. Ferrante, M. Birattari, and M. Dorigo. Swarm robotics: a review from the swarm engineering perspective. Swarm Intelligence, 7(1):1--41, 2013.
[2]
K. Friston. The free-energy principle: a unified brain theory? Nature Rev. Neuroscience, 11(2):127--138, 2010.
[3]
V. Trianni. Evolutionary Swarm Robotics, volume 108 of Studies in Comp. Intelligence. Springer, 2008.
[4]
H. von Helmholtz. Handbuch der physiologischen Optik. Ludwig Voss, Leipzig, Germany, 1867.

Cited By

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  • (2019)Engineered self-organization for resilient robot self-assembly with minimal surpriseRobotics and Autonomous Systems10.1016/j.robot.2019.103293122:COnline publication date: 1-Dec-2019
  • (2019)Self-assembly in Patterns with Minimal Surprise: Engineered Self-organization and Adaptation to the EnvironmentDistributed Autonomous Robotic Systems10.1007/978-3-030-05816-6_13(183-195)Online publication date: 30-Jan-2019
  1. Evolving prediction machines: collective behaviors based on minimal surprisal

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    cover image ACM Conferences
    GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation
    July 2014
    1524 pages
    ISBN:9781450328814
    DOI:10.1145/2598394
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 12 July 2014

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    Author Tags

    1. evolutionary robotics
    2. free-energy principle
    3. swarm behavior
    4. swarm intelligence

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    GECCO '14
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    GECCO '14: Genetic and Evolutionary Computation Conference
    July 12 - 16, 2014
    BC, Vancouver, Canada

    Acceptance Rates

    GECCO Comp '14 Paper Acceptance Rate 180 of 544 submissions, 33%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    Cited By

    View all
    • (2019)Engineered self-organization for resilient robot self-assembly with minimal surpriseRobotics and Autonomous Systems10.1016/j.robot.2019.103293122:COnline publication date: 1-Dec-2019
    • (2019)Self-assembly in Patterns with Minimal Surprise: Engineered Self-organization and Adaptation to the EnvironmentDistributed Autonomous Robotic Systems10.1007/978-3-030-05816-6_13(183-195)Online publication date: 30-Jan-2019

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