Number of documents

26

Matthieu Geist


"Bilal Piot"   

Journal articles2 documents

  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Bridging the Gap Between Imitation Learning and Inverse Reinforcement Learning. IEEE Transactions on Neural Networks and Learning Systems, IEEE, 2017, 28 (8), pp.1814 - 1826. ⟨10.1109/TNNLS.2016.2543000⟩. ⟨hal-01629654⟩
  • Edouard Klein, Bilal Piot, Matthieu Geist, Olivier Pietquin. Classification structurée pour l'apprentissage par renforcement inverse. Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2013, 27 (2), pp.155-169. ⟨10.3166/ria.27.155-169⟩. ⟨hal-00869723⟩

Conference papers23 documents

  • Matthieu Geist, Bilal Piot, Olivier Pietquin. Faut-il minimiser le résidu de Bellman ou maximiser la valeur moyenne ?. Journées Francophones sur la Planification, la Décision et l'Apprentissage pour la conduite de systèmes (JFPDA 2017), Jul 2017, Caen, France. ⟨hal-01576347⟩
  • Matthieu Geist, Bilal Piot, Olivier Pietquin. Is the Bellman residual a bad proxy?. NIPS 2017 - Advances in Neural Information Processing Systems, Dec 2017, Long Beach, United States. pp.1-13. ⟨hal-01629739⟩
  • Julien Pérolat, Bilal Piot, Matthieu Geist, Bruno Scherrer, Olivier Pietquin. Softened approximate policy iteration for Markov games. ICML 2016 - 33rd International Conference on Machine Learning, Jun 2016, New York City, United States. ⟨hal-01393328⟩
  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Batch Policy Iteration Algorithms for Continuous Domains. European Workshop on Reinforcement Learning (EWRL), 2016, Barcelone, Spain. ⟨hal-01629651⟩
  • Layla El Asri, Bilal Piot, Matthieu Geist, Romain Laroche, Olivier Pietquin. Score-based Inverse Reinforcement Learning. International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016, Singapore, Singapore. ⟨hal-01406886⟩
  • Thibaut Munzer, Bilal Piot, Matthieu Geist, Olivier Pietquin, Manuel Lopes. Inverse Reinforcement Learning in Relational Domains. International Joint Conferences on Artificial Intelligence, Jul 2015, Buenos Aires, Argentina. ⟨hal-01154650⟩
  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Imitation Learning Applied to Embodied Conversational Agents. 4th Workshop on Machine Learning for Interactive Systems (MLIS 2015), Jul 2015, Lille, France. ⟨hal-01225816⟩
  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Méthode de minimisation du résidu de Bellman boostée qui tient compte des démonstrations expertes.. 9èmes Journées Francophones de Planification, Décision et Apprentissage (JFPDA'14), May 2014, Liège, Belgique. ⟨hal-01104789⟩
  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Boosted and Reward-regularized Classification for Apprenticeship Learning. AAMAS 2014 : 13th International Conference on Autonomous Agents and Multiagent Systems, May 2014, Paris, France. pp.1249-1256. ⟨hal-01107837⟩
  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Difference of Convex Functions Programming for Reinforcement Learning. Advances in Neural Information Processing Systems (NIPS 2014), Dec 2014, Montreal, Canada. ⟨hal-01104419⟩
  • Bilal Piot, Olivier Pietquin, Matthieu Geist. Predicting when to laugh with structured classification. InterSpeech 2014, Sep 2014, Singapore, Singapore. pp.1786-1790. ⟨hal-01104739⟩
  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Boosted Bellman Residual Minimization Handling Expert Demonstrations. European Conference, ECML PKDD 2014, Sep 2014, Nancy, France. pp.549-564, ⟨10.1007/978-3-662-44851-9_35⟩. ⟨hal-01060953⟩
  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Apprentissage par démonstrations : vaut-il la peine d'estimer une fonction de récompense?. Journées Francophones de Plannification, Décision et Apprentissage (JFPDA), Jul 2013, Lille, France. ⟨hal-00916941⟩
  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Learning from demonstrations: Is it worth estimating a reward function?. 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2013), Oct 2013, Princeton, New Jersey, United States. ⟨hal-00916938⟩
  • Edouard Klein, Bilal Piot, Matthieu Geist, Olivier Pietquin. A cascaded supervised learning approach to inverse reinforcement learning. Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2013), Sep 2013, Prague, Czech Republic. pp.1-16, ⟨10.1007/978-3-642-40988-2_1⟩. ⟨hal-00869804⟩
  • Radoslaw Niewiadomski, Jennifer Hofmann, Jérôme Urbain, Tracey Platt, Johannes Wagner, et al.. Laugh-aware virtual agent and its impact on user amusement. AAMAS '13, May 2013, Saint Paul, Minnesota, United States. pp.619-626. ⟨hal-00869751⟩
  • Edouard Klein, Bilal Piot, Matthieu Geist, Olivier Pietquin. Apprentissage par renforcement inverse en cascadant classification et régression. Journées Francophones de Plannification, Décision et Apprentissage (JFPDA), Jul 2013, Lille, France. ⟨hal-00916942⟩
  • Matthieu Geist, Edouard Klein, Bilal Piot, Yann Guermeur, Olivier Pietquin. Around Inverse Reinforcement Learning and Score-based Classification. 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2013), Oct 2013, Princeton, New Jersey, United States. ⟨hal-00916936⟩
  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Classification régularisée par la récompense pour l'Apprentissage par Imitation. Journées Francophones de Plannification, Décision et Apprentissage (JFPDA), Jul 2013, Lille, France. ⟨hal-00916940⟩
  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Learning from Demonstrations: Is It Worth Estimating a Reward Function?. Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2013), Sep 2013, Prague, Czech Republic. pp.17-32, ⟨10.1007/978-3-642-40988-2_2⟩. ⟨hal-00869801⟩
  • Edouard Klein, Bilal Piot, Matthieu Geist, Olivier Pietquin. Structured Classification for Inverse Reinforcement Learning. EWRL 2012, Jun 2012, Edinburgh, United Kingdom. pp.1-14. ⟨hal-00749524⟩
  • Edouard Klein, Matthieu Geist, Bilal Piot, Olivier Pietquin. Inverse Reinforcement Learning through Structured Classification. NIPS 2012, Dec 2012, Lake Tahoe, Nevada, United States. pp.1-9. ⟨hal-00778624⟩
  • Edouard Klein, Bilal Piot, Matthieu Geist, Olivier Pietquin. Classification structurée pour l'apprentissage par renforcement inverse. Conférence Francophone sur l'Apprentissage Automatique - CAp 2012, May 2012, Nancy, France. pp.1-16. ⟨hal-00701947⟩

Preprints, Working Papers, ...1 document

  • Bilal Piot, Matthieu Geist, Olivier Pietquin. Difference of Convex Functions Programming Applied to Control with Expert Data. 2017. ⟨hal-01629653⟩