Truncating Temporal Differences: On the Efficient Implementation of TD(lambda) for Reinforcement Learning

@article{Cichosz1995TruncatingTD,
  title={Truncating Temporal Differences: On the Efficient Implementation of TD(lambda) for Reinforcement Learning},
  author={Pawel Cichosz},
  journal={J. Artif. Intell. Res.},
  year={1995},
  volume={2},
  pages={287-318}
}
Temporal diierence (TD) methods constitute a class of methods for learning predictions in multi-step prediction problems, parameterized by a recency factor. Currently the most important application of these methods is to temporal credit assignment in reinforcement learning. Well known reinforcement learning algorithms, such as AHC or Q-learning, may be viewed as instances of TD learning. This paper examines the issues of the eecient and general implementation of TD() for arbitrary , for use… CONTINUE READING
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