InforLorV4, PascalFrancis, Checkpoint, bibRecord, 000037

Classification structurée pour l'apprentissage par renforcement inverse

Identifieur interne : 000037 ( PascalFrancis/Checkpoint ); précédent : 000036; suivant : 000038

Classification structurée pour l'apprentissage par renforcement inverse

Auteurs : Edouard Klein [France] ; Bilal Piot [France] ; Matthieu Geist [France] ; Olivier Pietquin [France]

Source :

Revue d'intelligence artificielle [ 0992-499X ] ; 2013.

RBID : Pascal:13-0216741

Descripteurs français

Pascal (Inist)
- Classification, Structure donnée, Apprentissage renforcé, Paramétrisation, Simulateur, Récompense, Politique, Automobile, Conduite véhicule, Structure interne, Algorithme apprentissage, Problème inverse, Problème direct, Méthode heuristique.
Wicri :
- topic : Classification, Politique, Automobile.

English descriptors

KwdEn :
- Classification, Data structure, Direct problem, Heuristic method, Internal structure, Inverse problem, Learning algorithm, Motor car, Parameterization, Policy, Reinforcement learning, Reward, Simulator, Vehicle driving.

Abstract

This paper adresses the inverse reinforcement learning (IRL) problem, that is inferring a reward for which a demonstrated expert behavior is optimal. We introduce a new algorithm, SCIRL, whose principle is to use the so-called feature expectation of the expert as the parameterization of the score function of a multiclasse classifier. This approach produces a reward function for which the expert policy is provably near-optimal. Contrary to most of existing IRL algorithms, SCIRL does not require solving the direct RL problem. Moreover, with an appropriate heuristic, it can succeed with only trajectories sampled according to the expert behavior. This is illustrated on a car driving simulator.

Affiliations:

Links toward previous steps (curation, corpus...)

to stream PascalFrancis, to step Corpus: 000065
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Links to Exploration step

Pascal:13-0216741

Le document en format XML

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<s5>26</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Direct problem</s0>
<s5>26</s5>
</fC03>
<fC03 i1="13" i2="X" l="SPA"><s0>Problema directo</s0>
<s5>26</s5>
</fC03>
<fC03 i1="14" i2="X" l="FRE"><s0>Méthode heuristique</s0>
<s5>27</s5>
</fC03>
<fC03 i1="14" i2="X" l="ENG"><s0>Heuristic method</s0>
<s5>27</s5>
</fC03>
<fC03 i1="14" i2="X" l="SPA"><s0>Método heurístico</s0>
<s5>27</s5>
</fC03>
<fN21><s1>203</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
</standard>
</inist>
<affiliations><list><country><li>France</li>
</country>
<region><li>Grand Est</li>
<li>Lorraine (région)</li>
</region>
<settlement><li>Metz</li>
<li>Nancy</li>
</settlement>
</list>
<tree><country name="France"><region name="Grand Est"><name sortKey="Klein, Edouard" sort="Klein, Edouard" uniqKey="Klein E" first="Edouard" last="Klein">Edouard Klein</name>
</region>
<name sortKey="Geist, Matthieu" sort="Geist, Matthieu" uniqKey="Geist M" first="Matthieu" last="Geist">Matthieu Geist</name>
<name sortKey="Klein, Edouard" sort="Klein, Edouard" uniqKey="Klein E" first="Edouard" last="Klein">Edouard Klein</name>
<name sortKey="Pietquin, Olivier" sort="Pietquin, Olivier" uniqKey="Pietquin O" first="Olivier" last="Pietquin">Olivier Pietquin</name>
<name sortKey="Pietquin, Olivier" sort="Pietquin, Olivier" uniqKey="Pietquin O" first="Olivier" last="Pietquin">Olivier Pietquin</name>
<name sortKey="Piot, Bilal" sort="Piot, Bilal" uniqKey="Piot B" first="Bilal" last="Piot">Bilal Piot</name>
<name sortKey="Piot, Bilal" sort="Piot, Bilal" uniqKey="Piot B" first="Bilal" last="Piot">Bilal Piot</name>
</country>
</tree>
</affiliations>
</record>

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{{Explor lien
   |wiki=    Wicri/Lorraine
   |area=    InforLorV4
   |flux=    PascalFrancis
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   |type=    RBID
   |clé=     Pascal:13-0216741
   |texte=   Classification structurée pour l'apprentissage par renforcement inverse
}}

This area was generated with Dilib version V0.6.33.
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	Serveur d'exploration sur la recherche en informatique en Lorraine
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Serveur d'exploration sur la recherche en informatique en Lorraine

Classification structurée pour l'apprentissage par renforcement inverse

Classification structurée pour l'apprentissage par renforcement inverse

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Abstract

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