M. J. Arcaro, P. F. Schade, J. L. Vincent, C. R. Ponce, and M. S. Livingstone, Seeing faces is necessary for face-domain formation, Nature Neuroscience, vol.8, issue.10, pp.1404-1412, 2017.
DOI : 10.1136/jamia.2001.0080443

M. Argyle, Bodily communication, 1975.

F. Badeig, Q. Pelorson, S. Arias, V. Drouard, I. Gebru et al., A Distributed Architecture for Interacting with NAO, Proceedings of the 2015 ACM on International Conference on Multimodal Interaction , ICMI '15, pp.385-386, 2015.
DOI : 10.1145/2818346.2823303

URL : https://hal.archives-ouvertes.fr/hal-01201716

Z. Cao, T. Simon, S. E. Wei, and Y. Sheikh, Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
DOI : 10.1109/CVPR.2017.143

F. Cruz, G. I. Parisi, J. Twiefel, and S. Wermter, Multi-modal integration of dynamic audiovisual patterns for an interactive reinforcement learning scenario, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.759-766, 2016.
DOI : 10.1109/IROS.2016.7759137

I. Gebru, S. Ba, X. Li, and R. Horaud, Audiovisual speaker diarization based on spatiotemporal bayesian fusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017.
DOI : 10.1109/tpami.2017.2648793

URL : https://hal.archives-ouvertes.fr/hal-01413403

A. Ghadirzadeh, J. Bütepage, A. Maki, D. Kragic, and M. Björkman, A sensorimotor reinforcement learning framework for physical Human-Robot Interaction, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.2682-2688, 2016.
DOI : 10.1109/IROS.2016.7759417

I. Goodfellow, Y. Bengio, and A. Courville, Deep learning, 2016.

M. A. Goodrich and A. C. Schultz, Human-robot Interaction: A Survey. Foundations and Trends in Human, Computer Interaction, vol.1, pp.203-275, 2007.
DOI : 10.1561/1100000005

URL : http://www.nowpublishers.com/article/DownloadSummary/HCI-005

S. Hochreiter and J. Schmidhuber, Long Short-Term Memory, Neural Computation, vol.4, issue.8, pp.1735-1780, 1997.
DOI : 10.1016/0893-6080(88)90007-X

L. P. Kaelbling, M. L. Littman, and A. W. Moore, Reinforcement learning: A survey, Journal of artificial intelligence research, vol.4, pp.237-285, 1996.

A. Kendon, Some functions of gaze-direction in social interaction, Acta Psychologica, vol.26, pp.22-63, 1967.
DOI : 10.1016/0001-6918(67)90005-4

D. P. Kingma and J. Ba, Adam: A method for stochastic optimization, International Conference on Learning Representations, 2014.

J. Kober, J. A. Bagnell, and J. Peters, Reinforcement learning in robotics: A survey, The International Journal of Robotics Research, vol.8, issue.2, pp.1238-1274, 2013.
DOI : 10.1007/s10514-009-9132-0

URL : http://www.ri.cmu.edu/pub_files/2013/7/Kober_IJRR_2013.pdf

X. Li, L. Girin, F. Badeig, and R. Horaud, Reverberant sound localization with a robot head based on direct-path relative transfer function, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.2819-2826, 2016.
DOI : 10.1109/IROS.2016.7759437

URL : https://hal.archives-ouvertes.fr/hal-01349771

X. Li, L. Girin, R. Horaud, and S. Gannot, Multiple-Speaker Localization Based on Direct-Path Features and Likelihood Maximization With Spatial Sparsity Regularization, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.25, issue.10, 1997.
DOI : 10.1109/TASLP.2017.2740001

URL : https://hal.archives-ouvertes.fr/hal-01413417

S. Ljungblad, J. Kotrbova, M. Jacobsson, H. Cramer, and K. Niechwiadowicz, Hospital robot at work, Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work, CSCW '12, pp.177-186, 2012.
DOI : 10.1145/2145204.2145233

B. Massé, S. Lathuilì-ere, P. Mesejo, and R. Horaud, A reinforcement learning approach to sensorimotor control in human-robot interaction, Submitted to IEEE International Conference on Robotics and Automation, 2017.

N. Mitsunaga, C. Smith, T. Kanda, H. Ishiguro, and N. Hagita, Robot Behavior Adaptation for Human-Robot Interaction based on Policy Gradient Reinforcement Learning, Journal of the Robotics Society of Japan, vol.24, issue.7, pp.820-829, 2006.
DOI : 10.7210/jrsj.24.820

URL : http://kth.diva-portal.org/smash/get/diva2:436245/FULLTEXT01

V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness et al., Human-level control through deep reinforcement learning, Nature, vol.101, issue.7540, pp.529-533, 2015.
DOI : 10.1016/S0004-3702(98)00023-X

S. Pourmehr, J. Thomas, J. Bruce, J. Wawerla, and R. Vaughan, Robust sensor fusion for finding HRI partners in a crowd, 2017 IEEE International Conference on Robotics and Automation (ICRA), pp.3272-3278, 2017.
DOI : 10.1109/ICRA.2017.7989373

A. H. Qureshi, Y. Nakamura, Y. Yoshikawa, and H. Ishiguro, Robot gains social intelligence through multimodal deep reinforcement learning, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), pp.745-751, 2016.
DOI : 10.1109/HUMANOIDS.2016.7803357

A. H. Qureshi, Y. Nakamura, Y. Yoshikawa, and H. Ishiguro, Show, attend and interact: Perceivable human-robot social interaction through neural attention Q-network, 2017 IEEE International Conference on Robotics and Automation (ICRA), pp.1639-1645, 2017.
DOI : 10.1109/ICRA.2017.7989193

M. Rothbucher, C. Denk, and K. Diepold, Robotic gaze control using reinforcement learning, 2012 IEEE International Workshop on Haptic Audio Visual Environments and Games (HAVE 2012) Proceedings, pp.83-88, 2012.
DOI : 10.1109/HAVE.2012.6374444

A. Sauppé and B. Mutlu, The Social Impact of a Robot Co-Worker in Industrial Settings, Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, CHI '15, pp.3613-3622, 2015.
DOI : 10.1145/1358628.1358709

G. Skantze, A. Hjalmarsson, and C. Oertel, Turn-taking, feedback and joint attention in situated human???robot interaction, Speech Communication, vol.65, pp.50-66, 2014.
DOI : 10.1016/j.specom.2014.05.005

R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction, IEEE Transactions on Neural Networks, vol.9, issue.5, 1998.
DOI : 10.1109/TNN.1998.712192

A. L. Thomaz, G. Hoffman, and C. Breazeal, Reinforcement Learning with Human Teachers: Understanding How People Want to Teach Robots, ROMAN 2006, The 15th IEEE International Symposium on Robot and Human Interactive Communication, pp.352-357, 2006.
DOI : 10.1109/ROMAN.2006.314459

M. Vázquez, A. Steinfeld, and S. E. Hudson, Maintaining awareness of the focus of attention of a conversation: A robot-centric reinforcement learning approach, 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp.36-43, 2016.
DOI : 10.1109/ROMAN.2016.7745088

R. J. Williams, Simple statistical gradientfollowing algorithms for connectionist reinforcement learning, Machine Learning, 1992.
DOI : 10.1007/bf00992696

A. Zaraki, D. Mazzei, M. Giuliani, and D. D. Rossi, Designing and Evaluating a Social Gaze-Control System for a Humanoid Robot, IEEE Transactions on Human-Machine Systems, vol.44, issue.2, pp.157-168, 2014.
DOI : 10.1109/THMS.2014.2303083