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27 lines
1.3 KiB
ReStructuredText
27 lines
1.3 KiB
ReStructuredText
Dueling DQN
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===========
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**Actions space:** Discrete
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**References:** `Dueling Network Architectures for Deep Reinforcement Learning <https://arxiv.org/abs/1511.06581>`_
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Network Structure
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-----------------
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.. image:: /_static/img/design_imgs/dueling_dqn.png
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:align: center
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General Description
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-------------------
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Dueling DQN presents a change in the network structure comparing to DQN.
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Dueling DQN uses a specialized *Dueling Q Head* in order to separate :math:`Q` to an :math:`A` (advantage)
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stream and a :math:`V` stream. Adding this type of structure to the network head allows the network to better differentiate
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actions from one another, and significantly improves the learning.
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In many states, the values of the different actions are very similar, and it is less important which action to take.
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This is especially important in environments where there are many actions to choose from. In DQN, on each training
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iteration, for each of the states in the batch, we update the :ath:`Q` values only for the specific actions taken in
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those states. This results in slower learning as we do not learn the :math:`Q` values for actions that were not taken yet.
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On dueling architecture, on the other hand, learning is faster - as we start learning the state-value even if only a
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single action has been taken at this state. |