Shimon Whiteson's Publications

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Neuroevolutionary Reinforcement Learning for Generalized Helicopter Control

Rogier Koppejan and Shimon Whiteson. Neuroevolutionary Reinforcement Learning for Generalized Helicopter Control. In GECCO 2009: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 145–152, July 2009.

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Abstract

Helicopter hovering is an important challenge problem in the field of reinforcement learning. This paper considers several neuroevolutionary approaches to discovering robust controllers for a generalized version of the problem used in the 2008 Reinforcement Learning Competition, in which wind in the helicopter's environment varies from run to run. We present the simple model-free strategy that won first place in the competition and also describe several more complex model-based approaches. Our empirical results demonstrate that neuroevolution is effective at optimizing the weights of multi-layer perceptrons, that linear regression is faster and more effective than evolution for learning models, and that model-based approaches can outperform the simple model-free strategy, especially if prior knowledge is used to aid model learning.

BibTeX Entry

@InProceedings{koppejan:gecco09,
  author       = "Rogier Koppejan and Shimon Whiteson",
  title	       = "Neuroevolutionary Reinforcement Learning for Generalized Helicopter Control",
  booktitle    = "GECCO 2009: Proceedings of the Genetic and
                  Evolutionary Computation Conference",
  pages = "145-152",
  month	       = "July",
  year	       = 2009,
}

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