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On the Role of Embodiment for Self-Organizing Robots: Behavior As Broken Symmetry

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Book cover Guided Self-Organization: Inception

Part of the book series: Emergence, Complexity and Computation ((ECC,volume 9))

Abstract

Embodiment and SO form two cornerstones of both modern robotics and the understanding of human and animal intelligence. In particular, the role of the embodiment for the behavior of both artificial and natural beings has become of much and increasing interest in recent times. In robotics, there are essentially two attitudes towards the physical embodiment. On the one hand, with rule based systems and/or systems intended to execute a given motion plan, embodiment is more or less considered as a (nasty) problem opposing the execution of the plan. On the other hand, it is well believed and verified by many examples that living beings are taking much advantage from the physico-mechanical properties of their bodies in order to create natural motion patterns.

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References

  • Anthony, T., Polani, D., Nehaniv, C.L.: Impoverished empowerment: ‘Meaningful’ action sequence generation through bandwidth limitation. In: Kampis, G., Karsai, I., Szathmáry, E. (eds.) ECAL 2009, Part II. LNCS, vol. 5778, pp. 294–301. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  • Ay, N., Bernigau, H., Der, R., Prokopenko, M.: Information driven self-organization: The dynamical systems approach to autonomous robot behavior. Theory Biosci. (2012)

    Google Scholar 

  • Ay, N., Bertschinger, N., Der, R., Güttler, F., Olbrich, E.: Predictive information and explorative behavior of autonomous robots. The European Physical Journal B - Condensed Matter and Complex Systems 63(3), 329–339 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  • Behnisch, M., Haschke, R., Ritter, H., Gienger, M., Humanoids: Deformable trees - exploiting local obstacle avoidance. In: Humanoids, pp. 658–663 (2011)

    Google Scholar 

  • Bell, A.J., Sejnowski, T.J.: An information-maximisation approach to blind separation and blind deconvolution. Neural Computation 7, 1129–1159 (1995)

    Article  Google Scholar 

  • Braitenberg, V.: Vehicles: Experiments in Synthetic Psychology. MIT Press (1984)

    Google Scholar 

  • Butko, N.J., Triesch, J.: Exploring the role of intrinsic plasticity for the learning of sensory representations. In: ESANN 2006 Proceedings - 14th European Symposium on Artificial Neural Networks Bruges, pp. 467–472. Neurocomputing (2005)

    Google Scholar 

  • Der, R.: Self-organized acquisition of situated behaviors. Theory in Biosciences 120, 179–187 (2001)

    Google Scholar 

  • Der, R., Güttler, F., Ay, N.: Predictive information and emergent cooperativity in a chain of mobile robots. In: Artificial Life XI. MIT Press (2008)

    Google Scholar 

  • Der, R., Liebscher, R.: True autonomy from self-organized adaptivity. In: Proc. of EPSRC/BBSRC Intl. Workshop on Biologically Inspired Robotics. HP Labs Bristol (2002)

    Google Scholar 

  • Der, R., Martius, G.: The Playful Machine - Theoretical Foundation and Practical Realization of Self-Organizing Robots. Springer (2012)

    Google Scholar 

  • Elbrechter, C., Haschke, R., Ritter, H.: Bi-manual robotic paper manipulation based on real-time marker tracking and physical modelling. In: IROS, pp. 1427–1432 (2011)

    Google Scholar 

  • Friston, K.: The free-energy principle: a unified brain theory? Nature Reviews. Neuroscience 11(2), 127–138 (2010)

    Article  Google Scholar 

  • Friston, K., Adams, R.A., Perrinet, L., Breakspear, M.: Perceptions as Hypotheses: Saccades as Experiments. Frontiers in Psychology, 3 (2012)

    Google Scholar 

  • Friston, K.J.: A free energy principle for biological systems. Entropy 14(11), 2100–2121 (2012)

    MathSciNet  Google Scholar 

  • Friston, K.J., Stephan, K.E.: Free-energy and the brain. Synthese 159(3), 417–458 (2007)

    Article  Google Scholar 

  • Grossekathofer, U., Barchunova, A., Haschke, R., Hermann, T., Franzius, M., Ritter, H.: Learning of object manipulation operations from continuous multimodal input. In: Humanoids, pp. 507–512 (2011)

    Google Scholar 

  • Hauser, H., Ijspeert, A.J., Füchslin, R.M., Pfeifer, R., Maass, W.: Towards a theoretical foundation for morphological computation with compliant bodies. Biological Cybernetics 105(5-6), 355–370 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  • Hauser, H., Ijspeert, A.J., Füchslin, R.M., Pfeifer, R., Maass, W.: The role of feedback in morphological computation with compliant bodies. Biological Cybernetics 106(10), 595–613 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  • Jung, T., Polani, D., Stone, P.: Empowerment for continuous agent-environment systems. CoRR, abs/1201.6583 (2012)

    Google Scholar 

  • Klyubin, A.S., Polani, D., Nehaniv, C.L.: Empowerment: a universal agent-centric measure of control. In: Congress on Evolutionary Computation, pp. 128–135 (2005)

    Google Scholar 

  • Klyubin, A.S., Polani, D., Nehaniv, C.L.: Representations of space and time in the maximization of information flow in the perception-action loop. Neural Computation 19, 2387–2432 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  • Kolodziejski, C., Porr, B., Tamosiunaite, M., Wörgötter, F.: On the asymptotic equivalence between differential hebbian and temporal difference learning using a local third factor. In: Advances in Neural Information Processing Systems (2009)

    Google Scholar 

  • Kolodziejski, C., Porr, B., Wörgötter, F.: Mathematical properties of neuronal td-rules and differential hebbian learning: a comparison. Biological Cybernetics (2008)

    Google Scholar 

  • Kulvicius, T., Kolodziejski, C., Tamosiunaite, M., Porr, B., Wörgötter, F.: Behavioral analysis of differential hebbian learning in closed-loop systems. Biological Cybernetics (2010)

    Google Scholar 

  • Lazar, A., Pipa, G., Triesch, J.: The combination of STDP and intrinsic plasticity yields complex dynamics in recurrent spiking networks. In: ESANN, pp. 647–652 (2006)

    Google Scholar 

  • Lazar, A., Pipa, G., Triesch, J.: Emerging bayesian priors in a self-organizing recurrent network. In: Honkela, T. (ed.) ICANN 2011, Part II. LNCS, vol. 6792, pp. 127–134. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  • Markovic, D., Gros, C.: Self-Organized chaos through polyhomeostatic optimization. Physical Review Letters 105(6), 068702 (2010)

    Google Scholar 

  • Markovic, D., Gros, C.: Intrinsic adaptation in autonomous recurrent neural networks. Neural Computation 24(2), 523–540 (2012)

    Article  MathSciNet  Google Scholar 

  • Martius, G., Der, R., Ay, N.: Information driven self-organization of complex robotic behavior. PLOS ONE (in press, 2013)

    Google Scholar 

  • Maycock, J., Dornbusch, D., Elbrechter, C., Haschke, R., Schack, T., Ritter, H.: Approaching manual intelligence. KI 24(4), 287–294 (2010)

    Google Scholar 

  • Pfeifer, R.: ”Morphological computation” - self-organization, embodiment, and biological inspiration. In: IJCCI (2012)

    Google Scholar 

  • Pfeifer, R., Bongard, J.C.: How the Body Shapes the Way We Think: A New View of Intelligence. MIT Press, Cambridge (2006)

    Google Scholar 

  • Pfeifer, R., Gomez, G.: Understanding Intelligence (1999)

    Google Scholar 

  • Pfeifer, R.: Morphological computation – connecting brain, body, and environment. In: Sattar, A., Kang, B.-H. (eds.) AI 2006. LNCS (LNAI), vol. 4304, pp. 3–4. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  • Pfeifer, R., Lungarella, M., Iida, F.: Self-organization, embodiment, and biologically inspired robotics. Science 318, 1088–1093 (2007)

    Article  Google Scholar 

  • Prokopenko, M. (ed.): Foundations and Formalizations of Self-organization. Springer (2008)

    Google Scholar 

  • Prokopenko, M.: Information and self-organization: A macroscopic approach to complex systems. Artificial Life 15(3), 377–383 (2009)

    Article  Google Scholar 

  • Prokopenko, M., Boschetti, F., Ryan, A.J.: An information-theoretic primer on complexity, self-organization, and emergence. Complexity 15(1), 11–28 (2009)

    Article  MathSciNet  Google Scholar 

  • Ritter, H., Haschke, R., Steil, J.J.: Trying to grasp a sketch of a brain for grasping. In: Sendhoff, B., Körner, E., Sporns, O., Ritter, H., Doya, K. (eds.) Creating Brain-Like Intelligence. LNCS, vol. 5436, pp. 84–102. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  • Steffen, J., Elbrechter, C., Haschke, R., Ritter, H.J.: Bio-inspired motion strategies for a bimanual manipulation task. In: Humanoids, pp. 625–630 (2010)

    Google Scholar 

  • Triesch, J.: A gradient rule for the plasticity of a neuron’s intrinsic excitability. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds.) ICANN 2005. LNCS, vol. 3696, pp. 65–70. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  • Triesch, J.: Synergies between intrinsic and synaptic plasticity mechanisms. Neural Computation 19(4), 885–909 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  • Zahedi, K., Ay, N., Der, R.: Higher coordination with less control – A result of information maximization in the sensorimotor loop. Adaptive Behavior 18(3-4), 338–355 (2010)

    Article  Google Scholar 

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Der, R. (2014). On the Role of Embodiment for Self-Organizing Robots: Behavior As Broken Symmetry. 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_7

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  • DOI: https://doi.org/10.1007/978-3-642-53734-9_7

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