Skip to main content

Virtual Spatiality in Agent Controllers: Encoding Compartmentalization

  • Conference paper
Applications of Evolutionary Computation (EvoApplications 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7835))

Included in the following conference series:

  • 2863 Accesses

Abstract

Applying methods of artificial evolution to synthesize robot controllers for complex tasks is still a challenging endeavor. We report an approach which might have the potential to improve the performance of evolutionary algorithms in the context of evolutionary robotics. We apply a controller concept that is inspired by signaling networks found in nature. The implementation of spatial features is based on Voronoi diagrams that describe a compartmentalization of the agent’s inner body. These compartments establish a virtual embodiment, including sensors and actuators, and influence the dynamics of virtual hormones. We report results for an exploring task and an object discrimination task. These results indicate that the controller, that determines the principle hormone dynamics, can successfully be evolved in parallel with the compartmentalizations, that determine the spatial features of the sensors, actuators, and hormones.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Alberts, B.: Molecular biology of the cell. Garland Pub. (1989)

    Google Scholar 

  2. Aurenhammer, F.: Voronoi diagrams — a survey of a fundamental geometric data structure. ACM Computing Surveys 23(3), 345–405 (1991)

    Article  Google Scholar 

  3. Beer, R.D.: The dynamics of active categorical perception in an evolved model agent. Adaptive Behavior 11(4), 209–243 (2003)

    Article  Google Scholar 

  4. Beer, R.D., Gallagher, J.C.: Evolving dynamical neural networks for adaptive behavior. Adaptive Behavior 1(1), 91–122 (1992)

    Article  Google Scholar 

  5. Bray, D.: Wetware: A Computer in Every Living Cell. Yale University Press (2009)

    Google Scholar 

  6. Dale, K., Husbands, P.: The evolution of reaction-diffusion controllers for minimally cognitive agents. Artificial Life 16(1), 1–19 (2010)

    Article  Google Scholar 

  7. Hamann, H., Schmickl, T., Crailsheim, K.: A hormone-based controller for evaluation-minimal evolution in decentrally controlled systems. Artificial Life 18(2), 165–198 (2012)

    Article  MathSciNet  Google Scholar 

  8. Lodish, H., Berk, A., Zipursky, L.S., Matsudaira, P., Baltimore, D., Darnell, J.E.: Molecular Cell Biology, 5th edn. W.H. Freeman and Company (2003)

    Google Scholar 

  9. Moioli, R., Vargas, P.A., Husbands, P.: Exploring the kuramoto model of coupled oscillators in minimally cognitive evolutionary robotics tasks. In: WCCI 2010 IEEE World Congress on Computational Intelligence - CEC IEEE, pp. 2483–2490 (2010)

    Google Scholar 

  10. Nelson, A.L., Barlow, G.J., Doitsidis, L.: Fitness functions in evolutionary robotics: A survey and analysis. Robotics and Autonomous Systems 57, 345–370 (2009)

    Article  Google Scholar 

  11. Nolfi, S., Floreano, D.: Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines. MIT Press (2000)

    Google Scholar 

  12. Schmickl, T., Hamann, H., Crailsheim, K.: Modelling a hormone-inspired controller for individual- and multi-modular robotic systems. Mathematical and Computer Modelling of Dynamical Systems 17(3), 221–242 (2011)

    Article  MATH  Google Scholar 

  13. Schmickl, T., Hamann, H., Stradner, J., Crailsheim, K.: Hormone-based control for multi-modular robotics. In: Levi, P., et al. (eds.) Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution, pp. 240–263. Springer (2010)

    Google Scholar 

  14. Schoenauer, M., Kallel, L., Jouve, F.: Mechanical inclusions identification by evolutionary computation (1996)

    Google Scholar 

  15. Stradner, J., Hamann, H., Schmickl, T., Crailsheim, K.: Analysis and implementation of an artificial homeostatic hormone system: A first case study in robotic hardware. In: The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009), pp. 595–600. IEEE Press (2009)

    Google Scholar 

  16. Voronoi, G.: Nouvelles applications des paramétres continus à la théorie des formes quadratiques. Journal für Reine und Angewandte Mathematik 133, 97–178 (1907)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Stradner, J., Hamann, H., Schwarzer, C.S.F., Michiels, N.K., Schmickl, T. (2013). Virtual Spatiality in Agent Controllers: Encoding Compartmentalization. In: Esparcia-Alcázar, A.I. (eds) Applications of Evolutionary Computation. EvoApplications 2013. Lecture Notes in Computer Science, vol 7835. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37192-9_58

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37192-9_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37191-2

  • Online ISBN: 978-3-642-37192-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics