<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="wu-etal-2021-gaussian">
    <titleInfo>
        <title>Gaussian Process based Deep Dyna-Q approach for Dialogue Policy Learning</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Guanlin</namePart>
        <namePart type="family">Wu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Wenqi</namePart>
        <namePart type="family">Fang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ji</namePart>
        <namePart type="family">Wang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Jiang</namePart>
        <namePart type="family">Cao</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Weidong</namePart>
        <namePart type="family">Bao</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Yang</namePart>
        <namePart type="family">Ping</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Xiaomin</namePart>
        <namePart type="family">Zhu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Zheng</namePart>
        <namePart type="family">Wang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Chengqing</namePart>
            <namePart type="family">Zong</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Fei</namePart>
            <namePart type="family">Xia</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Wenjie</namePart>
            <namePart type="family">Li</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Roberto</namePart>
            <namePart type="family">Navigli</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Online</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <identifier type="citekey">wu-etal-2021-gaussian</identifier>
    <identifier type="doi">10.18653/v1/2021.findings-acl.156</identifier>
    <location>
        <url>https://aclanthology.org/2021.findings-acl.156</url>
    </location>
    <part>
        <date>2021-08</date>
        <extent unit="page">
            <start>1786</start>
            <end>1795</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Gaussian Process based Deep Dyna-Q approach for Dialogue Policy Learning
%A Wu, Guanlin
%A Fang, Wenqi
%A Wang, Ji
%A Cao, Jiang
%A Bao, Weidong
%A Ping, Yang
%A Zhu, Xiaomin
%A Wang, Zheng
%Y Zong, Chengqing
%Y Xia, Fei
%Y Li, Wenjie
%Y Navigli, Roberto
%S Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F wu-etal-2021-gaussian
%R 10.18653/v1/2021.findings-acl.156
%U https://aclanthology.org/2021.findings-acl.156
%U https://doi.org/10.18653/v1/2021.findings-acl.156
%P 1786-1795

Markdown (Informal)

[Gaussian Process based Deep Dyna-Q approach for Dialogue Policy Learning](https://aclanthology.org/2021.findings-acl.156) (Wu et al., Findings 2021)

• Gaussian Process based Deep Dyna-Q approach for Dialogue Policy Learning (Wu et al., Findings 2021)

ACL

• Guanlin Wu, Wenqi Fang, Ji Wang, Jiang Cao, Weidong Bao, Yang Ping, Xiaomin Zhu, and Zheng Wang. 2021. Gaussian Process based Deep Dyna-Q approach for Dialogue Policy Learning. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 1786–1795, Online. Association for Computational Linguistics.