Adaptive Behavior Control with Self-regulating Neurons

  • Keyan Zahedi
  • Frank Pasemann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4850)


It is claimed that synaptic plasticity of neural controllers for autonomous robots can enhance the behavioral properties of these systems. Based on homeostatic properties of so called self-regulating neurons, the presented mechanism will vary the synaptic strength during the robot interaction with the environment, due to driving sensor inputs and motor outputs. This is exemplarily shown for an obstacle avoidance behavior in simulation.


Obstacle Avoidance Synaptic Weight Synaptic Strength Autonomous Robot Inhibitory Connection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Keyan Zahedi
    • 1
  • Frank Pasemann
    • 2
  1. 1.MPI for Mathematics in the Sciences, Inselstrasse 22, 04103 LeipzigGermany
  2. 2.Fraunhofer Institute IAIS, Schloss Birlinghoven, 53754 Sankt AugustinGermany

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