<?xml version="1.0" encoding="utf-8"?>
<TEI xmlns="http://www.tei-c.org/ns/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:hal="http://hal.archives-ouvertes.fr/" xmlns:gml="http://www.opengis.net/gml/3.3/" xmlns:gmlce="http://www.opengis.net/gml/3.3/ce" version="1.1" xsi:schemaLocation="http://www.tei-c.org/ns/1.0 http://api.archives-ouvertes.fr/documents/aofr-sword.xsd">
  <teiHeader>
    <fileDesc>
      <titleStmt>
        <title>HAL TEI export of hal-00869801</title>
      </titleStmt>
      <publicationStmt>
        <distributor>CCSD</distributor>
        <availability status="restricted">
          <licence target="https://creativecommons.org/publicdomain/zero/1.0/">CC0 1.0 - Universal</licence>
        </availability>
        <date when="2026-05-20T00:37:26+02:00"/>
      </publicationStmt>
      <sourceDesc>
        <p part="N">HAL API Platform</p>
      </sourceDesc>
    </fileDesc>
  </teiHeader>
  <text>
    <body>
      <listBibl>
        <biblFull>
          <titleStmt>
            <title xml:lang="en">Learning from Demonstrations: Is It Worth Estimating a Reward Function?</title>
            <author role="aut">
              <persName>
                <forename type="first">Bilal</forename>
                <surname>Piot</surname>
              </persName>
              <idno type="halauthorid">638076-0</idno>
              <affiliation ref="#struct-160692"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Matthieu</forename>
                <surname>Geist</surname>
              </persName>
              <email type="md5">c025140e3cc06ac39e7de0f0db2a4b70</email>
              <email type="domain">univ-lorraine.fr</email>
              <idno type="idhal" notation="string">matthieu-geist</idno>
              <idno type="idhal" notation="numeric">6945</idno>
              <idno type="halauthorid" notation="string">7492-6945</idno>
              <affiliation ref="#struct-160692"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Olivier</forename>
                <surname>Pietquin</surname>
              </persName>
              <email type="md5">d7ca8400327f875d5b916c43fee3b2c5</email>
              <email type="domain">univ-lille1.fr</email>
              <idno type="idhal" notation="string">olivier-pietquin</idno>
              <idno type="idhal" notation="numeric">4024</idno>
              <idno type="halauthorid" notation="string">23089-4024</idno>
              <idno type="IDREF">https://www.idref.fr/142821861</idno>
              <idno type="ORCID">https://orcid.org/0000-0002-5386-465X</idno>
              <affiliation ref="#struct-160692"/>
            </author>
            <editor role="depositor">
              <persName>
                <forename>Sébastien</forename>
                <surname>Van Luchene</surname>
              </persName>
              <email type="md5">983556412cb0e7fb6d6508a01ac9cf46</email>
              <email type="domain">supelec.fr</email>
            </editor>
          </titleStmt>
          <editionStmt>
            <edition n="v1" type="current">
              <date type="whenSubmitted">2017-11-06 17:42:19</date>
              <date type="whenModified">2023-02-13 08:47:47</date>
              <date type="whenReleased">2017-11-06 17:48:44</date>
              <date type="whenProduced">2013-09-23</date>
              <date type="whenEndEmbargoed">2017-11-06</date>
              <ref type="file" target="https://centralesupelec.hal.science/hal-00869801v1/document">
                <date notBefore="2017-11-06"/>
              </ref>
              <ref type="file" subtype="author" n="1" target="https://centralesupelec.hal.science/hal-00869801v1/file/worth_estimating_reward.pdf" id="file-1629774-1675129">
                <date notBefore="2017-11-06"/>
              </ref>
              <ref type="externalLink" target="https://link.springer.com/content/pdf/10.1007%2F978-3-642-40988-2_2.pdf"/>
            </edition>
            <respStmt>
              <resp>contributor</resp>
              <name key="123540">
                <persName>
                  <forename>Sébastien</forename>
                  <surname>Van Luchene</surname>
                </persName>
                <email type="md5">983556412cb0e7fb6d6508a01ac9cf46</email>
                <email type="domain">supelec.fr</email>
              </name>
            </respStmt>
          </editionStmt>
          <publicationStmt>
            <distributor>CCSD</distributor>
            <idno type="halId">hal-00869801</idno>
            <idno type="halUri">https://centralesupelec.hal.science/hal-00869801</idno>
            <idno type="halBibtex">piot:hal-00869801</idno>
            <idno type="halRefHtml">&lt;i&gt;Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2013)&lt;/i&gt;, Sep 2013, Prague, Czech Republic. pp.17-32, &lt;a target="_blank" href="https://dx.doi.org/10.1007/978-3-642-40988-2_2"&gt;&amp;#x27E8;10.1007/978-3-642-40988-2_2&amp;#x27E9;&lt;/a&gt;</idno>
            <idno type="halRef">Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2013), Sep 2013, Prague, Czech Republic. pp.17-32, &amp;#x27E8;10.1007/978-3-642-40988-2_2&amp;#x27E9;</idno>
            <availability status="restricted">
              <licence target="https://about.hal.science/hal-authorisation-v1/">HAL Authorization<ref corresp="#file-1629774-1675129"/></licence>
            </availability>
          </publicationStmt>
          <seriesStmt>
            <idno type="stamp" n="SUPELEC">SUPELEC</idno>
            <idno type="stamp" n="UMI-COMPUTERSCIENCE">UMI 2958 - Axe de recherche : Computer Science</idno>
          </seriesStmt>
          <notesStmt>
            <note type="audience" n="2">International</note>
            <note type="invited" n="0">No</note>
            <note type="popular" n="0">No</note>
            <note type="peer" n="1">Yes</note>
            <note type="proceedings" n="1">Yes</note>
          </notesStmt>
          <sourceDesc>
            <biblStruct>
              <analytic>
                <title xml:lang="en">Learning from Demonstrations: Is It Worth Estimating a Reward Function?</title>
                <author role="aut">
                  <persName>
                    <forename type="first">Bilal</forename>
                    <surname>Piot</surname>
                  </persName>
                  <idno type="halauthorid">638076-0</idno>
                  <affiliation ref="#struct-160692"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Matthieu</forename>
                    <surname>Geist</surname>
                  </persName>
                  <email type="md5">c025140e3cc06ac39e7de0f0db2a4b70</email>
                  <email type="domain">univ-lorraine.fr</email>
                  <idno type="idhal" notation="string">matthieu-geist</idno>
                  <idno type="idhal" notation="numeric">6945</idno>
                  <idno type="halauthorid" notation="string">7492-6945</idno>
                  <affiliation ref="#struct-160692"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Olivier</forename>
                    <surname>Pietquin</surname>
                  </persName>
                  <email type="md5">d7ca8400327f875d5b916c43fee3b2c5</email>
                  <email type="domain">univ-lille1.fr</email>
                  <idno type="idhal" notation="string">olivier-pietquin</idno>
                  <idno type="idhal" notation="numeric">4024</idno>
                  <idno type="halauthorid" notation="string">23089-4024</idno>
                  <idno type="IDREF">https://www.idref.fr/142821861</idno>
                  <idno type="ORCID">https://orcid.org/0000-0002-5386-465X</idno>
                  <affiliation ref="#struct-160692"/>
                </author>
              </analytic>
              <monogr>
                <title level="m">Lecture Notes in Computer Science</title>
                <meeting>
                  <title>Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2013)</title>
                  <date type="start">2013-09-23</date>
                  <date type="end">2013-09-27</date>
                  <settlement>Prague</settlement>
                  <country key="CZ">Czech Republic</country>
                </meeting>
                <editor>Hendrik Blockeel</editor>
                <editor>Kristian Kersting</editor>
                <editor>Siegfried Nijssen</editor>
                <editor>Filip Železný</editor>
                <imprint>
                  <publisher>Springer</publisher>
                  <biblScope unit="serie">Machine Learning and Knowledge Discovery in Databases</biblScope>
                  <biblScope unit="volume">8188</biblScope>
                  <biblScope unit="pp">17-32</biblScope>
                  <date type="datePub">2013</date>
                </imprint>
              </monogr>
              <idno type="doi">10.1007/978-3-642-40988-2_2</idno>
            </biblStruct>
          </sourceDesc>
          <profileDesc>
            <langUsage>
              <language ident="en">English</language>
            </langUsage>
            <textClass>
              <classCode scheme="halDomain" n="stat.ml">Statistics [stat]/Machine Learning [stat.ML]</classCode>
              <classCode scheme="halTypology" n="COMM">Conference papers</classCode>
              <classCode scheme="halOldTypology" n="COMM">Conference papers</classCode>
              <classCode scheme="halTreeTypology" n="COMM">Conference papers</classCode>
            </textClass>
            <abstract xml:lang="en">
              <p>This paper provides a comparative study between Inverse Reinforcement Learning (IRL) and Apprenticeship Learning (AL). IRL and AL are two frameworks, using Markov Decision Processes (MDP), which are used for the imitation learning problem where an agent tries to learn from demonstrations of an expert. In the AL Framework, the agent tries to learn the expert policy whereas in the IRL Framework, the agent tries to learn a reward which can explain the behavior of the expert. This reward is then optimized to imitate the expert. One can wonder if it is worth estimating such a reward, or if estimating a Policy is sufficient. This quite natural question has not really been addressed in the literature right now. We provide partial answers, both from a theoretical and empirical point of view.</p>
            </abstract>
          </profileDesc>
        </biblFull>
      </listBibl>
    </body>
    <back>
      <listOrg type="structures">
        <org type="researchteam" xml:id="struct-160692" status="OLD">
          <orgName>IMS : Information, Multimodalité &amp; Signal</orgName>
          <desc>
            <address>
              <addrLine>2 rue Edouard Belin - - 57070 METZ</addrLine>
              <country key="FR"/>
            </address>
          </desc>
          <listRelation>
            <relation active="#struct-26305" type="direct"/>
            <relation active="#struct-303397" type="indirect"/>
          </listRelation>
        </org>
        <org type="laboratory" xml:id="struct-26305" status="OLD">
          <orgName>SUPELEC-Campus Metz</orgName>
          <date type="start">1985-01-01</date>
          <date type="end">2014-12-31</date>
          <desc>
            <address>
              <addrLine>2 rue Edouard Belin 57070 Metz</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.metz.supelec.fr/metz/</ref>
          </desc>
          <listRelation>
            <relation active="#struct-303397" type="direct"/>
          </listRelation>
        </org>
        <org type="institution" xml:id="struct-303397" status="VALID">
          <orgName>Ecole Supérieure d'Electricité - SUPELEC (FRANCE)</orgName>
          <desc>
            <address>
              <country key="FR"/>
            </address>
          </desc>
        </org>
      </listOrg>
    </back>
  </text>
</TEI>