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From Conditioning of a Non Specific Sensor to Emotional Regulation of Behavior

  • Conference paper
Artificial Neural Networks – ICANN 2010 (ICANN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6353))

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Abstract

Inspired by the emotional conditionings performed by the amygdala, we describe a simulated neural network able to learn the meaning of a previously neutral stimulation. A robot using this neural network can learn the conditioning of a non specific sensor activated by the experimentator and its internal state of pain or pleasure. This biologically inspired adaptative and natural way to interact with the robot is tested with a mobile robot learning navigation tasks in a real environment.

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References

  1. Arleo, A., Gerstner, W.: Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity. Biol. Cybern. (2000)

    Google Scholar 

  2. Balkenius, C., Moren, J., Winberg, S.: Interactions between motivation, emotion and attention: From biology to robotics. In: Proceedings of the Ninth International Conference on Epigenetic Robotics (2009)

    Google Scholar 

  3. Balkenius, C., Winberg, S.: Fast learning in an actor-critic architecture with reward and punishment. In: Tenth Scandinavian Conference on Artificial Intelligence, SCAI 2008 (2008)

    Google Scholar 

  4. Balleine, B.W., Killcross, S.A.: Parallel incentive processing: an integrated view of amygdala function. Trends in Neuroscience (2006)

    Google Scholar 

  5. Baxter, M.G., Murray, E.A.: The amygdala and reward. Nature Review of Neuroscience (2002)

    Google Scholar 

  6. Blair, H.T., Sotres-Bayon, F., Moita, M.A.P., Leadoux, J.E.: The lateral amygdala processes the value of conditioned and unconditioned aversive stimuli. Neuroscience (2005)

    Google Scholar 

  7. Donnart, J.Y., Meyer, J.A.: Learning reactive and planning rules in a motivationally autonomous animat. IEEE Transactions on Systems Man and Cybernetics, Part B (1996)

    Google Scholar 

  8. Doya, K.: Reinforcement learning in continuous time and space. Neural Computation (2008)

    Google Scholar 

  9. Dunsmoor, J., Schmajuk, N.: Interpreting patterns of brain activation in human fear conditioning with an attentionalassociative learning model. Behavioral Neuroscience (2009)

    Google Scholar 

  10. Gallistel, C.R., Cramer, A.E.: Computations on metric maps in mammals: getting oriented and choosing a multi-destination route. Journal of experimental biology (1996)

    Google Scholar 

  11. Gaussier, P., Joulain, C., Banquet, J.P., Leprêtre, S., Revel, A.: The visual homing problem: an example of robotics/biology cross fertilization. In: Robotics and autonomous system (2000)

    Google Scholar 

  12. Giovannangeli, C., Gaussier, P.: Interactive teaching for vision-based mobile robot: a sensory-motor approach. IEEE Transactions on Man, Systems and Cybernetics, Part A: Systems and humans (2010)

    Google Scholar 

  13. Grossberg, S., Bullock, D., Dranias, M.: Neural dynamics underlying impaired autonomic and conditioned responses following amygdala and orbitofrontal lesions. Behavioral Neuroscience (2008)

    Google Scholar 

  14. Mannella, F., Zappacosta, S., Mirolli, M., Baldassarre, G.: A computational model of the amygdala nuclei’s role in second order conditioning. In: From animals to animats, vol. 10 (2008)

    Google Scholar 

  15. O’Keefe, J., Nadel, L.: The Hippocampus as a Cognitive Map. Oxford University Press, Oxford (1978)

    Google Scholar 

  16. Oudeyer, P.-Y., Kaplan, F., Hafner, V.: Intrinsic motivation systems for autonomous mental development. IEEE Transactions on Evolutionary Computation (2007)

    Google Scholar 

  17. Paton, J.J., Belova, M.A., Morrison, S.E., Salzman, C.D.: The primate amygdala represents the positive and the negative value of visual stimuli during learning. Nature (2006)

    Google Scholar 

  18. Pitkanen, A., Jolkkonen, E., Kemppainen, S.: Anatomic heterogeneity of the rat amygdaloid complex. Folia Morphologica (2000)

    Google Scholar 

  19. Rescorla, R.A., Wagner, A.R.: A theory of pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. Classical conditioning II: Current research and theory (1972)

    Google Scholar 

  20. Schmajuk, N.: Computational models of classical conditioning. Scholarpedia (2008)

    Google Scholar 

  21. Widrow, B., Hoff, M.E.: Adaptive switching circuits. In: IRE WESCON (1960)

    Google Scholar 

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Hasson, C., Gaussier, P. (2010). From Conditioning of a Non Specific Sensor to Emotional Regulation of Behavior. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15822-3_39

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  • DOI: https://doi.org/10.1007/978-3-642-15822-3_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15821-6

  • Online ISBN: 978-3-642-15822-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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