Article

Genetic evolution of hierarchical behavior structures

Authors:

Brian G. Woolley,

Gilbert L. PetersonAuthors Info & Claims

GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation

Pages 1731 - 1738

https://doi.org/10.1145/1276958.1277296

Published: 07 July 2007 Publication History

Abstract

The development of coherent and dynamic behaviors for mobile robots is an exceedingly complex endeavor ruled by task objectives, environmental dynamics and the interactions within the behavior structure. This paper discusses the use of genetic programming techniques and the unified behavior framework to develop effective control hierarchies using interchangeable behaviors and arbitration components. Given the number of possible variations provided by the framework, evolutionary programming is used to evolve the overall behavior design. Competitive evolution of the behavior population incrementally develops feasible solutions for the domain through competitive ranking. By developing and implementing many simple behaviors independently and then evolving a complex behavior structure suited to the domain, this approach allows for the reuse of elemental behaviors and eases the complexity of development for a given domain. Additionally, this approach has the ability to locate a behavior structure which a developer may not have previously considered, and whose ability exceeds expectations. The evolution of the behavior structure is demonstrated using agents in the Robocode environment, with the evolved structures performing up to 122 percent better than one crafted by an expert.

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Cited By

Desplenter TTrejos A(2020)A Control Software Framework for Wearable Mechatronic DevicesJournal of Intelligent & Robotic Systems10.1007/s10846-019-01144-5Online publication date: 21-Jan-2020
https://doi.org/10.1007/s10846-019-01144-5
Gomes JChristensen A(2018)Comparing Approaches for Evolving High-Level Robot Control Based on Behaviour Repertoires2018 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2018.8477699(1-6)Online publication date: Jul-2018
https://doi.org/10.1109/CEC.2018.8477699

Index Terms

Genetic evolution of hierarchical behavior structures
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Robotics
      1. Robotic autonomy
2. Software and its engineering
  1. Software creation and management
    1. Software development techniques
      1. Software prototyping
    2. Software post-development issues
      1. Software evolution

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cover image ACM Conferences

GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation

July 2007

2313 pages

ISBN:9781595936974

DOI:10.1145/1276958

General Chair:
Hod Lipson
Cornell University, USA

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 07 July 2007

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GECCO07: Genetic and Evolutionary Computation Conference

July 7 - 11, 2007

London, England

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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Desplenter TTrejos A(2020)A Control Software Framework for Wearable Mechatronic DevicesJournal of Intelligent & Robotic Systems10.1007/s10846-019-01144-5Online publication date: 21-Jan-2020
https://doi.org/10.1007/s10846-019-01144-5
Gomes JChristensen A(2018)Comparing Approaches for Evolving High-Level Robot Control Based on Behaviour Repertoires2018 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2018.8477699(1-6)Online publication date: Jul-2018
https://doi.org/10.1109/CEC.2018.8477699

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