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Improving the Efficiency of Deep Reinforcement Learning in NetHack Using VAE and Proposing Additional Rewards.

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Title: Improving the Efficiency of Deep Reinforcement Learning in NetHack Using VAE and Proposing Additional Rewards.
Authors: Onuki, Yasuhiro1, Tahara, Yasuyuki1, Ohsuga, Akihiko1, Sei, Yuichi1, seiuny@uec.ac.jp, Deepali1, dedeepali@wiley.com
Source: International Journal of Computer Games Technology; 7/7/2026, Vol. 2026, p1-11, 11p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 195176553
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Improving the Efficiency of Deep Reinforcement Learning in NetHack Using VAE and Proposing Additional Rewards.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Computer+Games+Technology%22">International Journal of Computer Games Technology</searchLink>; 7/7/2026, Vol. 2026, p1-11, 11p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=195176553
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      – Type: doi
        Value: 10.1155/ijcg/9867761
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      – Code: eng
        Text: English
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        PageCount: 11
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      – TitleFull: Improving the Efficiency of Deep Reinforcement Learning in NetHack Using VAE and Proposing Additional Rewards.
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            NameFull: Onuki, Yasuhiro
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              Text: 7/7/2026
              Type: published
              Y: 2026
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              Value: 2026
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