Skip to main content

Evolving Reactive Controller for a Modular Robot: Benefits of the Property of State-Switching in Fractal Gene Regulatory Networks

  • Conference paper
From Animals to Animats 12 (SAB 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7426))

Included in the following conference series:

Abstract

In this paper, we study Fractal Gene Regulatory Networks (FGRNs) evolved as local controllers for a modular robot in snake topology that reacts adaptively to environment. The task is to have the robot moving in a specific direction until it reaches a randomly placed target-zone and stays there. We point to a characteristic of FGRN model, namely “state-switching property” and demonstrate it as a beneficial property in evolving reactive controllers.

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

Access this chapter

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.

References

  1. Banzhaf, W.: Artificial regulatory networks and genetic programming. In: Genetic Programming Theory and Practice, pp. 43–62. Kluwer (2003)

    Google Scholar 

  2. Bentley, P.J.: Adaptive fractal gene regulatory networks for robot control. In: Workshop on Regeneration and Learning in Developmental Systems in the Genetic and Evolutionary Computation Conference, GECCO 2004 (2004)

    Google Scholar 

  3. Bentley, P.J.: Fractal proteins. J. Genet. Program Evol. Mach. (5), 71–101 (2004)

    Google Scholar 

  4. Bongard, J.C., Pfeifer, R.: Repeated structure and dissociation of genotypic and phenotypic complexity in artificial ontogeny, pp. 829–836. Morgan Kaufmann (2001)

    Google Scholar 

  5. Eggenberger, P.: Evolving morphologies of simulated 3d organisms based on differential gene expression. In: Proceedings of the Fourth European Conference on Artificial Life, pp. 205–213. MIT Press (1997)

    Google Scholar 

  6. Haasdijk, E., Rusu, A.A., Eiben, A.E.: HyperNEAT for Locomotion Control in Modular Robots. In: Tempesti, G., Tyrrell, A.M., Miller, J.F. (eds.) ICES 2010. LNCS, vol. 6274, pp. 169–180. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  7. Hamann, H., Stradner, J., Schmickl, T., Crailsheim, K.: Artificial hormone reaction networks: Towards higher evolvability in evolutionary multi-modular robotics. In: Proc. of the ALife XII Conference, pp. 773–780 (2010)

    Google Scholar 

  8. Harada, K., Corradi, P., Popesku, S., Liedke, J.: Reconfigurable heterogeneous mechanical modules. In: Levi, P., Kernbach, S. (eds.) Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution, Springer (2010)

    Google Scholar 

  9. Krohn, J., Gorse, D.: Fractal Gene Regulatory Networks for Control of Nonlinear Systems. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds.) PPSN XI, Part II. LNCS, vol. 6239, pp. 209–218. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

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

    Google Scholar 

  11. Manoonpong, P., Pasemann, F., Roth, H.: Modular reactive neurocontrol for biologically-inspired walking machines. The International Journal of Robotics Research 26, 301–331 (2007)

    Article  Google Scholar 

  12. REPLICATOR: Project website (2011), http://www.replicators.eu

  13. Roggen, D., Federici, D.: Multi-cellular Development: Is There Scalability and Robustness to Gain? In: Yao, X., Burke, E.K., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J.E., Tiňo, P., Kabán, A., Schwefel, H.-P. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 391–400. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  14. 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 

  15. SYMBRION: Project website (2011), http://www.symbrion.eu

  16. Winkler, L., Wörn, H.: Symbricator3D – A Distributed Simulation Environment for Modular Robots. In: Xie, M., Xiong, Y., Xiong, C., Liu, H., Hu, Z. (eds.) ICIRA 2009. LNCS, vol. 5928, pp. 1266–1277. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  17. Zahadat, P., Christensen, D.J., Schultz, U.P., Katebi, S., Stoy, K.: Fractal Gene Regulatory Networks for Robust Locomotion Control of Modular Robots. In: Doncieux, S., Girard, B., Guillot, A., Hallam, J., Meyer, J.-A., Mouret, J.-B. (eds.) SAB 2010. LNCS, vol. 6226, pp. 544–554. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  18. Zahadat, P., Katebi, S.D.: Tartarus and fractal gene regulatory networks with inputs. Advances in Complex Systems (ACS) 11(06), 803–829 (2008)

    Article  Google Scholar 

  19. Zahadat, P., Støy, K.: An alternative representation of fractal gene regulatory networks facilitating analysis and interpretation. Annals of Mathematics and Artificial Intelligence (submitted)

    Google Scholar 

  20. Ziemke, T., Thieme, M.: Neuromodulation of Reactive Sensorimotor Mappings as a Short-Term Memory Mechanism in Delayed Response Tasks. Adaptive Behavior 10(3-4), 185–199 (2002)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zahadat, P., Schmickl, T., Crailsheim, K. (2012). Evolving Reactive Controller for a Modular Robot: Benefits of the Property of State-Switching in Fractal Gene Regulatory Networks. In: Ziemke, T., Balkenius, C., Hallam, J. (eds) From Animals to Animats 12. SAB 2012. Lecture Notes in Computer Science(), vol 7426. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33093-3_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-33093-3_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33092-6

  • Online ISBN: 978-3-642-33093-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics