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SimpleDS: A Simple Deep Reinforcement Le...

Cuayáhuitl, Heriber...

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SimpleDS: A Simple Deep Reinforcement Learning Dialogue System by Cuayáhuitl, Heriberto ( Author )

Content Provider	Lemonjar Open Access
Publisher	N.A
Publication Date	02-08-2023
Summary	This paper presents 'SimpleDS', a simple and publicly available dialogue system trained with deep reinforcement learning. In contrast to previous reinforcement learning dialogue systems, this system avoids manual feature engineering by performing action selection directly from raw text of the last system and (noisy) user responses. Our initial results, in the restaurant domain, show that it is indeed possible to induce reasonable dialogue behaviour with an approach that aims for high levels of automation in dialogue control for intelligent interactive agents.
ISBN	-
Item Type	Article
File Type	pdf
File Size	37.08 KB
Language	English
Subjects	-
Unlimited	MYR 0.01
Total read	-
URL	http://arxiv.org/abs/1601.04574

Citation

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AMA 11th EditionReferences

Cuayáhuitl, Heriberto. SimpleDS: A Simple Deep Reinforcement Learning Dialogue System. N.A. August 02, 2023. Accessed October 02, 2025. https://online.provdatabase.com/cite/11664

APA 7th EditionReferences

Cuayáhuitl, Heriberto. (2023). SimpleDS: A Simple Deep Reinforcement Learning Dialogue System. N.A. https://online.provdatabase.com/cite/11664

Chicago 17th EditionReferences

Cuayáhuitl, Heriberto. SimpleDS: A Simple Deep Reinforcement Learning Dialogue System. N.A. 2023. https://online.provdatabase.com/cite/11664

HarvardReferences

Cuayáhuitl, Heriberto. (2023). SimpleDS: A Simple Deep Reinforcement Learning Dialogue System. [Online]. N.A. Available from: https://online.provdatabase.com/cite/11664. (Accessed 02 October 2025).

Harvard AustraliaReferences

Cuayáhuitl, Heriberto, 2023, SimpleDS: A Simple Deep Reinforcement Learning Dialogue System, N.A, viewed 02 October 2025, <https://online.provdatabase.com/cite/11664>

MLA 9th EditionWorks Cited

Cuayáhuitl, Heriberto. SimpleDS: A Simple Deep Reinforcement Learning Dialogue System. N.A, 2023. PROV Database, https://online.provdatabase.com/cite/11664.

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