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Non-representational Sensorimotor Knowledge

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8575))

Abstract

The sensorimotor approach argues that in order to perceive one needs to first “master” the relevant sensorimotor contingencies, and then exercise the acquired practical know-how to become “attuned” to the actual and potential contingencies a particular situation entails. But the approach provides no further detail about how this mastery is achieved or what precisely it means to become attuned to a situation. We here present an agent-based model to show how sensorimotor attunement can be understood as a dynamic and non-representational process in which a particular sensorimotor coordination is enacted as a response to a given environmental context, without requiring deliberative action selection.

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References

  1. O’Regan, J., Noë, A.: A sensorimotor account of vision and visual consciousness. Behavioral and Brain Sciences 24, 939–1031 (2001)

    Article  Google Scholar 

  2. Merleau-Ponty, M.: Phenomenology of Perception, 2nd edn. Routledge (2002)

    Google Scholar 

  3. Dreyfus, H.L.: Intelligence without representation. Merleau-Ponty’s Critique of Mental Representation. Phenomenology and the Cognitive Sciences 1(4), 367–383 (2002)

    Article  Google Scholar 

  4. Kelly, S.D.: Merleau-Ponty on the body. Ratio 15(4), 376–391 (2002)

    Article  Google Scholar 

  5. Beer, R.D.: On the dynamics of small continuous-time recurrent neural networks. Adapt. Behav. 3(4), 469–509 (1995)

    Article  MathSciNet  Google Scholar 

  6. Hollerbach, M.J., Flash, T.: Dynamic interactions between limb segments during planar arm movement. Biological Cybernetics 44(1), 67–77 (1982)

    Article  Google Scholar 

  7. Harvey, I.: The microbial genetic algorithm. In: Kampis, G., Karsai, I., Szathmáry, E. (eds.) ECAL 2009, Part II. LNCS, vol. 5778, pp. 126–133. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  8. Beer, R., Williams, P.: Information processing and dynamics in minimally cognitive agents. To appear in Cognitive Science (2014)

    Google Scholar 

  9. Izquierdo, E., Buhrmann, T.: Analysis of a dynamical recurrent neural network evolved for two qualitatively different tasks: Walking and chemotaxis. In: Bullock, S., et al. (eds.) Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems, pp. 257–264. MIT Press, Cambridge (2008)

    Google Scholar 

  10. Buhrmann, T., Di Paolo, E.A., Barandiaran, X.E.: A dynamical systems account of sensorimotor contingencies. Frontiers in Cognition 4(285) (2013)

    Google Scholar 

  11. Hutto, D.D., Myin, E.: Radicalizing enactivism: Basic minds without content. MIT Press, Cambridge (2013)

    Google Scholar 

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© 2014 Springer International Publishing Switzerland

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Buhrmann, T., Di Paolo, E. (2014). Non-representational Sensorimotor Knowledge. In: del Pobil, A.P., Chinellato, E., Martinez-Martin, E., Hallam, J., Cervera, E., Morales, A. (eds) From Animals to Animats 13. SAB 2014. Lecture Notes in Computer Science(), vol 8575. Springer, Cham. https://doi.org/10.1007/978-3-319-08864-8_3

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  • DOI: https://doi.org/10.1007/978-3-319-08864-8_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08863-1

  • Online ISBN: 978-3-319-08864-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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