Confronting the challenge of learning a flexible neural controller for a diversity of morphologies

@inproceedings{Risi2013ConfrontingTC,
  title={Confronting the challenge of learning a flexible neural controller for a diversity of morphologies},
  author={Sebastian Risi and Kenneth O. Stanley},
  booktitle={GECCO '13},
  year={2013}
}
The ambulatory capabilities of legged robots offer the potential for access to dangerous and uneven terrain without a risk to human life. However, while machine learning has proven effective at training such robots to walk, a significant limitation of such approaches is that controllers trained for a specific robot are likely to fail when transferred to a robot with a slightly different morphology. This paper confronts this challenge with a novel strategy: Instead of training a controller for a… 

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