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Reinforcement Learning and Deep Reinforcement Learning

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Other literature type 01 Jan 2019 English Publisher:Springer International Publishing

Authors: F. Richard Yu; Ying He;

doi: 10.1007/978-3-030-10546-4_2

Reinforcement Learning and Deep Reinforcement Learning

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Abstract

In order to better understand state-of-the-art reinforcement learning agent, deep Q-network, a brief review of reinforcement learning and Q-learning are first described. Then recent advances of deep Q-network are presented, and double deep Q-network and dueling deep Q-network that go beyond deep Q-network are also given.

Related Organizations

Carleton University
Canada

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	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	6
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

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