Construct · 1 fields · 1 citations

double Q-learning: a standalone construct

One name. One construct. A landmark on the map.

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Reinforcement learning (machine learning)

reducing the overestimation of action values in Q-learning by choosing the best action with one estimator and evaluating it with another.

In reinforcement learning (machine learning), double Q-learning refers to reducing the overestimation of action values in Q-learning by choosing the best action with one estimator and evaluating it with another. This meaning comes from van Hasselt (2015) in arXiv.[1]

Unit
Recovery means
Measured by

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Nearby constructs

action3 fields · 6 citationsjingle · one word, three constructs estimator2 fields · 2 citationsjingle · one word, two constructs learning6 fields · 14 citationsjingle · one name, six constructs

References

van Hasselt, H., Guez, A., & Silver, D. (2015). Deep Reinforcement Learning with Double Q-learning. arXiv. https://doi.org/10.48550/arxiv.1509.06461

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