Fast Online Q(λ)

@article{Wiering1998FastOQ,
  title={Fast Online Q(λ)},
  author={Marco Wiering and J{\"u}rgen Schmidhuber},
  journal={Machine Learning},
  year={1998},
  volume={33},
  pages={105-115}
}
Q(λ)-learning uses TD(λ)-methods to accelerate Q-learning. The update complexity of previous online Q(λ) implementations based on lookup tables is bounded by the size of the state/action space. Our faster algorithm's update complexity is bounded by the number of actions. The method is based on the observation that Q-value updates may be postponed until they are needed. 
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