Abstract
Self-organizing processes are not only crucial for the development of living beings, but can also spur new developments in robotics, e. g. to increase fault tolerance and enhance flexibility, provided that the prescribed goals can be realized at the same time. This combination of an externally specified objective and autonomous exploratory behavior is very interesting for practical applications of robot learning. In this chapter, we will present several forms of guided self-organization in robots based on homeokinesis.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Amari, S.: Natural gradients work efficiently in learning. Neural Computation 10 (1998)
Bongard, J.C., Zykov, V., Lipson, H.: Resilient machines through continuous self-modeling. Science 314, 1118–1121 (2006)
Butera, F.M.: Urban development as a guided self-organisation process. In: The City and Its Sciences, pp. 225–242. Springer (1998)
Cannon, W.B.: The wisdom of the body. Norton, New York (1939)
Chemova, S., Veloso, M.: An evolutionary approach to gait learning for four-legged robots. In: Proc. IEEE IROS 2004, vol. 3, pp. 2562–2567 (2004)
Choi, J., Wehrspohn, R.B., Gösele, U.: Mechanism of guided self-organization producing quasi-monodomain porous alumina. Electrochimica Acta 50(13), 2591–2595 (2005)
Cruse, H., Dürr, V., Schmitz, J., Schneider, A.: Control of hexapod walking in biological systems. In: Adaptive Motion of Animals and Machines, pp. 17–29. Springer (2006)
de Margerie, E., Mouret, J.-B., Doncieux, S., Meyer, J.-A.: Artificial evolution of the morphology and kinematics in a flapping-wing mini UAV. Bioinspiration and Biomimetics 2, 65–82 (2007)
Der, R.: Self-organized acquisition of situated behaviors. Theory Biosci. 120, 179–187 (2001)
Der, R., Liebscher, R.: True autonomy from self-organized adaptivity. In: Proc. Workshop Biologically Inspired Robotics, Bristol (2002)
Der, R., Martius, G.: The Playful Machine - Theoretical Foundation and Practical Realization of Self-Organizing Robots. Springer (2012)
Der, R., Martius, G.: Behavior as broken symmetry in embodied self-organizing robots. In: Advances in Artificial Life, ECAL 2013 (accepted, 2013)
Dongyong, Y., Jingping, J., Yuzo, Y.: Distal supervised learning control and its application to CSTRsystems. In: SICE 2000. Proc. of the 39th SICE Annual Conference, pp. 209–214 (2000)
Ijspeert, A.J., Hallam, J., Willshaw, D.: Evolving Swimming Controllers for a Simulated Lamprey with Inspiration from Neurobiology. Adaptive Behavior 7(2), 151–172 (1999)
Jordan, M.I., Rumelhart, D.E.: Forward models: Supervised learning with a distal teacher. Cognitive Science 16(3), 307–354 (1992)
Klyubin, A.S., Polani, D., Nehaniv, C.L.: Empowerment: a universal agent-centric measure of control. In: IEEE Congress on Evolutionary Computation, pp. 128–135. IEEE (2005)
Martius, G.: Robustness of guided self-organization against sensorimotor disruptions. Advances in Complex Systems 16(02n03), 1350001 (2013)
Martius, G., Der, R., Ay, N.: Information driven self-organization of complex robotic behaviors. PLoS ONE 8(5), e63400 (2013)
Martius, G., Herrmann, J.M.: Taming the beast: Guided self-organization of behavior in autonomous robots. In: Doncieux, S., Girard, B., Guillot, A., Hallam, J., Meyer, J.-A., Mouret, J.-B. (eds.) SAB 2010. LNCS, vol. 6226, pp. 50–61. Springer, Heidelberg (2010)
Martius, G., Herrmann, J.M.: Tipping the scales: Guidance and intrinsically motivated behavior. In: Advances in Artificial Life, ECAL 2011, pp. 506–513. MIT Press (2011)
Martius, G., Herrmann, J.M.: Variants of guided self-organization for robot control. Theory in Biosci. 131(3), 129–137 (2012)
Martius, G., Herrmann, J.M., Der, R.: Guided self-organisation for autonomous robot development. In: Almeida e Costa, F., Rocha, L.M., Costa, E., Harvey, I., Coutinho, A. (eds.) ECAL 2007. LNCS (LNAI), vol. 4648, pp. 766–775. Springer, Heidelberg (2007)
Martius, G., Hesse, F., Güttler, F., Der, R.: LpzRobots: A free and powerful robot simulator (2012), http://robot.informatik.uni-leipzig.de/software
Mazzapioda, M., Nolfi, S.: Synchronization and gait adaptation in evolving hexapod robots. In: Nolfi, S., Baldassarre, G., Calabretta, R., Hallam, J.C.T., Marocco, D., Meyer, J.-A., Miglino, O., Parisi, D. (eds.) SAB 2006. LNCS (LNAI), vol. 4095, pp. 113–125. Springer, Heidelberg (2006)
Nolfi, S., Floreano, D.: Evolutionary Robotics. The Biology, Intelligence, and Technology of Self-organizing Machines. MIT Press, Cambridge (2000) (1st print) (2001) (2nd print)
Ott, E., Grebogi, C., Yorke, J.: Controlling chaos. Phys. Rev. Lett. 64, 1196–1199 (1990)
Pearson, K., Gordon, J.: Spinal reflexes. In: Kandel, E., Schwartz, J.H., Jessell, T.M. (eds.) Principles of Neural Science, 4th edn., pp. 713–736. McGraw-Hill, New York (2000)
Peters, J., Schaal, S.: Natural Actor-Critic. Neurocomputing 71(7-9), 1180–1190 (2008)
Popp, J.: Spherical robots (2004), http://www.sphericalrobots.com
Prokopenko, M.: Design vs self-organization. In: Prokopenko, M. (ed.) Advances in Applied Self-organizing Systems, pp. 3–17. Springer (2008)
Prokopenko, M.: Guided self-organization. HFSP Journal 3(5), 287–289 (2009)
Rodriguez, A.: Guided Self-Organizing Particle Systems for Basic Problem Solving. PhD thesis, University of Maryland (College Park, Md., USA) (2007)
Santello, M., Soechting, J.F.: Force synergies for multifingered grasping. Experimental Brain Research 133(4), 457–467 (2000)
Schaal, S., Ijspeert, A., Billard, A.: Computational approaches to motor learning by imitation, vol. 1431, pp. 199–218. Oxford University Press (2004)
Smith, S.C., Herrmann, J.M.: Homeokinetic reinforcement learning. In: Schwenker, F., Trentin, E. (eds.) PSL 2011. LNCS, vol. 7081, pp. 82–91. Springer, Heidelberg (2012)
Stitt, S., Zheng, Y.F.: Distal learning applied to biped robots. In: Proc. of the IEEE Intl. Conf. on Robotics and Automation, pp. 137–142. IEEE Computer Society (1994)
Sutton, R.S.: Reinforcement learning: Past, present and future. In: McKay, B., Yao, X., Newton, C.S., Kim, J.-H., Furuhashi, T. (eds.) SEAL 1998. LNCS (LNAI), vol. 1585, p. 195. Springer, Heidelberg (1999)
Wikipedia (2013). Homeostasis — wikipedia, the free encyclopedia (Online accessed July 23, 2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Martius, G., Der, R., Herrmann, J.M. (2014). Robot Learning by Guided Self-Organization. In: Prokopenko, M. (eds) Guided Self-Organization: Inception. Emergence, Complexity and Computation, vol 9. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53734-9_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-53734-9_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-53733-2
Online ISBN: 978-3-642-53734-9
eBook Packages: EngineeringEngineering (R0)