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Evolved Controllers for Simulated Locomotion

  • Brian F. Allen
  • Petros Faloutsos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5884)

Abstract

We present a system for automatically evolving neural networks as physics-based locomotion controllers for humanoid characters. Our approach provides two key features: (a) the topology of the neural network controller gradually grows in size to allow increasingly complex behavior, and (b) the evolutionary process requires only the physical properties of the character model and a simple fitness function. No a priori knowledge of the appropriate cycles or patterns of motion is needed.

Keywords

Central Pattern Generator Neural Network Controller Bipedal Walking Biped Locomotion Walk Cycle 
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 2009

Authors and Affiliations

  • Brian F. Allen
    • 1
  • Petros Faloutsos
    • 1
  1. 1.University of CaliforniaLos AngelesUSA

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