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%0 Conference Proceedings
%T Dialog policy optimization for low resource setting using Self-play and Reward based Sampling
%A Madusanka, Tharindu
%A Langappuli, Durashi
%A Welmilla, Thisara
%A Thayasivam, Uthayasanker
%A Jayasena, Sanath
%Y Nguyen, Minh Le
%Y Luong, Mai Chi
%Y Song, Sanghoun
%S Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation
%D 2020
%8 October
%I Association for Computational Linguistics
%C Hanoi, Vietnam
%F madusanka-etal-2020-dialog
%U https://aclanthology.org/2020.paclic-1.21
%P 178-187

Markdown (Informal)

[Dialog policy optimization for low resource setting using Self-play and Reward based Sampling](https://aclanthology.org/2020.paclic-1.21) (Madusanka et al., PACLIC 2020)

• Dialog policy optimization for low resource setting using Self-play and Reward based Sampling (Madusanka et al., PACLIC 2020)

ACL

• Tharindu Madusanka, Durashi Langappuli, Thisara Welmilla, Uthayasanker Thayasivam, and Sanath Jayasena. 2020. Dialog policy optimization for low resource setting using Self-play and Reward based Sampling. In Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation, pages 178–187, Hanoi, Vietnam. Association for Computational Linguistics.