Learning from Demonstrations: Is It Worth Estimating a Reward Function?

Bilal Piot 1 Matthieu Geist 1 Olivier Pietquin 1
1 IMS - Equipe Information, Multimodalité et Signal
UMI2958 - Georgia Tech - CNRS [Metz], SUPELEC-Campus Metz
Abstract : 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.
Type de document :
Communication dans un congrès
Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železný. Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2013), Sep 2013, Prague, Czech Republic. Springer, Lecture Notes in Computer Science, 8188, pp.17-32, 2013, Machine Learning and Knowledge Discovery in Databases. 〈10.1007/978-3-642-40988-2_2〉
Liste complète des métadonnées

Littérature citée [12 références]  Voir  Masquer  Télécharger

https://hal-supelec.archives-ouvertes.fr/hal-00869801
Contributeur : Sébastien Van Luchene <>
Soumis le : lundi 6 novembre 2017 - 17:42:19
Dernière modification le : jeudi 15 février 2018 - 08:48:15

Fichier

worth_estimating_reward.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Bilal Piot, Matthieu Geist, Olivier Pietquin. Learning from Demonstrations: Is It Worth Estimating a Reward Function?. Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železný. Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2013), Sep 2013, Prague, Czech Republic. Springer, Lecture Notes in Computer Science, 8188, pp.17-32, 2013, Machine Learning and Knowledge Discovery in Databases. 〈10.1007/978-3-642-40988-2_2〉. 〈hal-00869801〉

Partager

Métriques

Consultations de la notice

128

Téléchargements de fichiers

4