Members
Overall Objectives
Research Program
Application Domains
Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
XML PDF e-pub
PDF e-Pub


Bibliography

Major publications by the team in recent years
[1]
A. Angeli, D. Filliat, S. Doncieux, J. Meyer.
Fast and incremental method for loop-closure detection using bags of visual words, in: Robotics, IEEE Transactions on, 2008, vol. 24, no 5, pp. 1027–1037.
[2]
A. Baranes, P.-Y. Oudeyer.
RIAC: Robust Intrinsically Motivated Exploration and Active Learning, in: IEEE Trans. on Auto. Ment. Dev., 2009, vol. 1, no 3, pp. 155-169.
http://www.pyoudeyer.com/TAMDBaranesOudeyer09.pdf
[3]
A. Baranes, P.-Y. Oudeyer.
Active learning of inverse models with intrinsically motivated goal exploration in robots, in: Robotics and Autonomous Systems, 2013, vol. 61, no 1, pp. 49 - 73. [ DOI : 10.1016/j.robot.2012.05.008 ]
http://www.pyoudeyer.com/RAS-SAGG-RIAC-2012.pdf
[4]
J. Buchli, F. Stulp, E. Theodorou, S. Schaal.
Learning Variable Impedance Control, in: International Journal of Robotics Research, 2011, vol. 30, no 7, pp. 820-833.
http://ijr.sagepub.com/content/early/2011/03/31/0278364911402527
[5]
T. Degris, O. Sigaud, P. Wuillemin.
Learning the Structure of Factored Markov Decision Processes in Reinforcement Learning Problems, in: Proceedings of the 23rd International Conference on Machine learning (ICML), 2006, pp. 257–264.
[6]
T. Degris, M. White, R. Sutton.
Off-Policy Actor-Critic, in: International Conference on Machine Learning, 2012.
http://hal.inria.fr/hal-00764021
[7]
D. Filliat.
A visual bag of words method for interactive qualitative localization and mapping, in: Robotics and Automation, 2007 IEEE International Conference on, IEEE, 2007, pp. 3921–3926.
[8]
A. Gepperth.
Efficient online bootstrapping of sensory representations, in: Neural Networks, December 2012. [ DOI : 10.1016/j.neunet.2012.11.002 ]
http://hal.inria.fr/hal-00763660
[9]
A. Gepperth, S. Rebhan, S. Hasler, J. Fritsch.
Biased competition in visual processing hierarchies: a learning approach using multiple cues, in: Cognitive Computation, March 2011, vol. 3, no 1.
http://hal.archives-ouvertes.fr/hal-00647809/en/
[10]
J. Gottlieb, P.-Y. Oudeyer, M. Lopes, A. Baranes.
Information-seeking, curiosity, and attention: computational and neural mechanisms., in: Trends in Cognitive Sciences, November 2013, vol. 17, no 11, pp. 585-93. [ DOI : 10.1016/j.tics.2013.09.001 ]
http://hal.inria.fr/hal-00913646
[11]
M. Lopes, T. Lang, M. Toussaint, P.-Y. Oudeyer.
Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress, in: Neural Information Processing Systems (NIPS), Lake Tahoe, United States, December 2012.
http://hal.inria.fr/hal-00755248
[12]
M. Lopes, F. Melo, L. Montesano.
Active learning for reward estimation in inverse reinforcement learning, in: Machine Learning and Knowledge Discovery in Databases, 2009, pp. 31–46.
[13]
L. Montesano, M. Lopes, A. Bernardino, J. Santos-Victor.
Learning Object Affordances: From Sensory–Motor Coordination to Imitation, in: Robotics, IEEE Transactions on, 2008, vol. 24, no 1, pp. 15–26.
[14]
S. M. Nguyen, A. Baranes, P.-Y. Oudeyer.
Bootstrapping Intrinsically Motivated Learning with Human Demonstrations, in: proceedings of the IEEE International Conference on Development and Learning, Frankfurt, Allemagne, 2011, ERC Grant EXPLORERS 240007.
http://hal.archives-ouvertes.fr/hal-00645986
[15]
P.-Y. Oudeyer, F. Kaplan, V. Hafner.
Intrinsic Motivation Systems for Autonomous Mental Development, in: IEEE Transactions on Evolutionary Computation, 2007, vol. 11, no 1, pp. 265–286.
http://www.pyoudeyer.com/ims.pdf
[16]
P.-Y. Oudeyer.
Self-Organization in the Evolution of Speech, Studies in the Evolution of Language, Oxford University Press, 2006.
[17]
P.-Y. Oudeyer.
On the impact of robotics in behavioral and cognitive sciences: from insect navigation to human cognitive development, in: IEEE Transactions on Autonomous Mental Development, 2010, vol. 2, no 1, pp. 2–16.
http://hal.inria.fr/inria-00541783/en/
[18]
P. Rouanet, P.-Y. Oudeyer, F. Danieau, D. Filliat.
The Impact of Human-Robot Interfaces on the Learning of Visual Objects, in: IEEE Transactions on Robotics, January 2013.
http://hal.inria.fr/hal-00758241
[19]
F. Stulp, B. Buchli, A. Ellmer, M. Mistry, E. Theodorou, S. Schaal.
Model-free Reinforcement Learning of Impedance Control in Stochastic Force Fields, in: IEEE Transactions on Autonomous Mental Development, 2012.
[20]
F. Stulp, A. Fedrizzi, L. Mösenlechner, M. Beetz.
Learning and Reasoning with Action-Related Places for Robust Mobile Manipulation, in: Journal of Artificial Intelligence Research (JAIR), 2012, vol. 43, pp. 1–42.
[21]
F. Stulp, E. Theodorou, S. Schaal.
Reinforcement Learning with Sequences of Motion Primitives for Robust Manipulation, in: IEEE Transactions on Robotics, 2012, vol. 28, no 6, pp. 1360-1370.
Publications of the year

Doctoral Dissertations and Habilitation Theses

[22]
T. Cederborg.
A Formal Approach to Social Learning: Exploring Language Acquisition Through Imitation, Université Sciences et Technologies - Bordeaux I, December 2013.
http://hal.inria.fr/tel-00937615
[23]
N. Lyubova.
Approche développementale de la perception pour un robot humanoïde, Ecole Nationale Supérieure de Techniques Avancées - ENSTA, October 2013.
http://hal.inria.fr/tel-00925067
[24]
S. M. Nguyen.
A Curious Robot Learner for Interactive Goal-Babbling : Strategically Choosing What, How, When and from Whom to Learn, Université Sciences et Technologies - Bordeaux I, November 2013.
http://hal.inria.fr/tel-00936992

Articles in International Peer-Reviewed Journals

[25]
A. Baranes, P.-Y. Oudeyer.
Active Learning of Inverse Models with Intrinsically Motivated Goal Exploration in Robots, in: Robotics and Autonomous Systems, January 2013, vol. 61, no 1, pp. 69-73. [ DOI : 10.1016/j.robot.2012.05.008 ]
http://hal.inria.fr/hal-00788440
[26]
T. Cederborg, P.-Y. Oudeyer.
From Language to Motor Gavagai: Unified Imitation Learning of Multiple Linguistic and Non-linguistic Sensorimotor Skills, in: IEEE Transactions on Autonomous Mental Development (TAMD), 2013.
http://hal.inria.fr/hal-00910982
[27]
J. Gottlieb, P.-Y. Oudeyer, M. Lopes, A. Baranes.
Information-seeking, curiosity, and attention: computational and neural mechanisms, in: Trends in Cognitive Sciences, November 2013, vol. 17, no 11, pp. 585-93. [ DOI : 10.1016/j.tics.2013.09.001 ]
http://hal.inria.fr/hal-00913646
[28]
S. Ivaldi, S. M. Nguyen, N. Lyubova, A. Droniou, V. Padois, D. Filliat, P.-Y. Oudeyer, O. Sigaud.
Object learning through active exploration, in: IEEE Transactions on Autonomous Mental Development, 2013, pp. 1-18.
http://hal.inria.fr/hal-00919694
[29]
C. Moulin-Frier, M. A. Arbib.
Recognizing Speech in a Novel Accent: The Motor Theory of Speech Perception Reframed, in: Biological Cybernetics, August 2013, vol. 107, no 4, pp. 421-447. [ DOI : 10.1007/s00422-013-0557-3 ]
http://hal.inria.fr/hal-00864213
[30]
C. Moulin-Frier, S. M. Nguyen, P.-Y. Oudeyer.
Self-Organization of Early Vocal Development in Infants and Machines: The Role of Intrinsic Motivation, in: Frontiers in Psychology, 2013, vol. 4, no 1006. [ DOI : 10.3389/fpsyg.2013.01006 ]
http://hal.inria.fr/hal-00927940
[31]
S. N'Guyen, C. Moulin-Frier, J. Droulez.
Decision Making under Uncertainty: A Quasimetric Approach, in: PLoS ONE, December 2013, vol. 8, no 12. [ DOI : 10.1371/journal.pone.0083411 ]
http://hal.inria.fr/hal-00922767
[32]
S. M. Nguyen, P.-Y. Oudeyer.
Socially Guided Intrinsic Motivation for Robot Learning of Motor Skills, in: Autonomous Robots, July 2013, 1 p. [ DOI : 10.1007/s10514-013-9339-y ]
http://hal.inria.fr/hal-00936938
[33]
P. Peter, K. Mrinal, M. Franziska, F. Stulp, B. Jonas, E. Theodorou, S. Stefan.
From Dynamic Movement Primitives to Associative Skill Memories, in: Robotics and Autonomous Systems, 2013, vol. 61, no 4, pp. 351-361.
http://hal.inria.fr/hal-00789397
[34]
P. Rouanet, P.-Y. Oudeyer, F. Danieau, D. Filliat.
The Impact of Human-Robot Interfaces on the Learning of Visual Objects, in: IEEE Transactions on Robotics, April 2013, vol. 29, no 2, pp. 525-541. [ DOI : 10.1109/TRO.2012.2228134 ]
http://hal.inria.fr/hal-00758241
[35]
O. Sigaud, F. Stulp.
Adaptation de la matrice de covariance pour l'apprentissage par renforcement direct, in: Revue d'Intelligence Artificielle, 2013, vol. 27, no 2, pp. 243-263.
http://hal.inria.fr/hal-00922127
[36]
F. Stulp, P.-Y. Oudeyer.
Exploration through Covariance Matrix Adaptation Enables Developmental Motor Learning, in: Paladyn. Journal of Behavioral Robotics,, 2013, pp. 128-135.
http://hal.inria.fr/hal-00922125
[37]
F. Stulp, O. Sigaud.
Robot Skill Learning: From Reinforcement Learning to Evolution Strategies, in: Paladyn, Journal of Behavioral Robotics, 2013, vol. 4, no 1, pp. 49-61.
http://hal.inria.fr/hal-00922132

International Conferences with Proceedings

[38]
J. Almingol, L. Montesano, M. Lopes.
Learning Multiple Behaviors from Unlabeled Demonstrations in a Latent Controller Space, in: International Conference on Machine Learning (ICML-13), Atlanta, United States, 2013, pp. 136-144.
http://hal.inria.fr/hal-00871852
[39]
A. Armand, D. Filliat, J. Ibanez-Guzman.
Modelling Stop Intersection Approaches using Gaussian Processes, in: IEEE International Conference on Intelligent Transportation Systems - ITSC, Netherlands, 2013, xx p.
http://hal.inria.fr/hal-00919680
[40]
F. Benureau, P.-Y. Oudeyer.
Autonomous Reuse of Motor Exploration Trajectories, in: International Conference on Development and Learning and on Epigenetic Robotics, Osaka, Japan, August 2013.
http://hal.inria.fr/hal-00850759
[41]
A. Chapoulie, P. Rives, D. Filliat.
Appearance-based segmentation of indoors/outdoors sequences of spherical views, in: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'2013, Tokyo, Japan, November 2013, pp. 1946-1951.
http://hal.inria.fr/hal-00845450
[42]
M. Dubois, P. K. Rozo, A. Gepperth, F. A. Gonzalez, D. Filliat.
A Comparison of Geometric and Energy-Based Point Cloud Semantic Segmentation Methods, in: European Conference on Mobile Robotics (ECMR), Spain, 2013.
http://hal.inria.fr/hal-00919627
[43]
J. Grizou, I. Iturrate, L. Montesano, M. Lopes, P.-Y. Oudeyer.
Interactive Task Estimation From Unlabelled Teaching Signals, in: International Workshop on Human-Machine Systems, Cyborgs and Enhancing Devices, Manchester, United Kingdom, October 2013.
http://hal.inria.fr/hal-00858210
[44]
J. Grizou, I. Iturrate, L. Montesano, M. Lopes, P.-Y. Oudeyer.
Zero-calibration BMIs for sequential tasks using error-related potentials, in: IROS 2013 Workshop on Neuroscience and Robotics, Tokyo, Japan, November 2013.
http://hal.inria.fr/hal-00872484
[45]
J. Grizou, M. Lopes, P.-Y. Oudeyer.
Robot Learning Simultaneously a Task and How to Interpret Human Instructions, in: Joint IEEE International Conference on Development and Learning an on Epigenetic Robotics (ICDL-EpiRob), Osaka, Japan, 2013.
http://hal.inria.fr/hal-00850703
[46]
T. Hester, P. Stone, M. Lopes.
Learning Exploration Strategies in Model-Based Reinforcement Learning, in: International Conference on Autonomous Agents and Multiagent Systems, AAMAS'13, St. Paul, MN, United States, 2013.
http://hal.inria.fr/hal-00871861
[47]
J. Kulick, T. Lang, M. Toussaint, M. Lopes.
Active Learning for Teaching a Robot Grounded Relational Symbols, in: International Joint Conference on Artificial Intelligence, Beijing, China, 2013.
http://hal.inria.fr/hal-00871858
[48]
M. Lapeyre, P. Rouanet, P.-Y. Oudeyer.
Poppy Humanoid Platform: Experimental Evaluation of the Role of a Bio-inspired Thigh Shape, in: Humanoids 2013, Atlanta, United States, October 2013.
http://hal.inria.fr/hal-00861110
[49]
M. Lapeyre, P. Rouanet, P.-Y. Oudeyer.
Poppy: a New Bio-Inspired Humanoid Robot Platform for Biped Locomotion and Physical Human-Robot Interaction, in: Proceedings of the 6th International Symposium on Adaptive Motion in Animals and Machines (AMAM), Darmstadt, Germany, March 2013.
http://hal.inria.fr/hal-00788433
[50]
M. Lapeyre, P. Rouanet, P.-Y. Oudeyer.
The Poppy Humanoid Robot: Leg Design for Biped Locomotion, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan, November 2013.
http://hal.inria.fr/hal-00852858
[51]
N. Lyubova, D. Filliat, S. Ivaldi.
Improving object learning through manipulation and robot self-identification, in: IEEE International Conference on Robotics and Biomimetics, China, 2013.
http://hal.inria.fr/hal-00919649
[52]
N. Lyubova, S. Ivaldi, D. Filliat.
Developmental object learning through manipulation and human demonstration, in: ICRA Mobile Manipulation Workshop on Interactive Perception, Germany, 2013.
http://hal.inria.fr/hal-00839519
[53]
O. Mangin, P.-Y. Oudeyer.
Learning Semantic Components from Subsymbolic Multimodal Perception, in: Joint IEEE International Conference on Development and Learning an on Epigenetic Robotics (ICDL-EpiRob), Osaka, Japan, IEEE, 2013.
http://hal.inria.fr/hal-00842453
[54]
C. Moulin-Frier, P.-Y. Oudeyer.
Exploration strategies in developmental robotics: a unified probabilistic framework, in: ICDL-Epirob - International Conference on Development and Learning, Epirob, Osaka, Japan, 2013.
http://hal.inria.fr/hal-00860641
[55]
C. Moulin-Frier, P.-Y. Oudeyer.
Learning how to reach various goals by autonomous interaction with the environment: unification and comparison of exploration strategies, in: 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM2013), Princeton University, New Jersey, Princeton, United States, 2013.
http://hal.inria.fr/hal-00922537
[56]
C. Moulin-Frier, P.-Y. Oudeyer.
The role of intrinsic motivations in learning sensorimotor vocal mappings: a developmental robotics study, in: Interspeech, Lyon, France, ISCA, 2013.
http://hal.inria.fr/hal-00860655
[57]
S. M. Nguyen, S. Ivaldi, N. Lyubova, A. Droniou, D. Gerardeaux-Viret, D. Filliat, V. Padois, O. Sigaud, P.-Y. Oudeyer.
Learning to recognize objects through curiosity-driven manipulation with the iCub humanoid robot, in: IEEE International Conference on Development and Learning and on Epigenetic Robotics - ICDL-EPIROB, Japan, 2013, pp. 1–8.
http://hal.inria.fr/hal-00919674
[58]
D. Silver, G. Lever, N. Heess, T. Degris, D. Wierstra, M. Riedmiller.
Deterministic Policy Gradient Algorithms, in: ICML, Beijing, China, June 2014.
http://hal.inria.fr/hal-00938992

National Conferences with Proceedings

[59]
D. Filliat.
Software architecture of the PACOM project, in: Proceedings of the 8th National Conference on Control Architectures of Robots, France, 2013.
http://hal.inria.fr/hal-00839518

Conferences without Proceedings

[60]
O. Mangin, P.-Y. Oudeyer.
Inverse Reinforcement Learning of a Dictionary of Primitive Tasks, in: Workshop on Hierarchical and Structured Learning for Robotics, Berlin, Germany, Gerhard Neumann and George Konidaris and Freek Stulp and Jan Peters, June 2013.
http://hal.inria.fr/hal-00931398
[61]
F. Stulp, G. Raiola, A. Hoarau, S. Ivaldi, O. Sigaud.
Learning Compact Parameterized Skills with a Single Regression, in: IEEE-RAS International Conference on Humanoid Robots, United States, 2013.
http://hal.inria.fr/hal-00922135
[62]
F. Stulp, O. Sigaud.
Policy Improvement: Between Black-Box Optimization and Episodic Reinforcement Learning, in: Journées Francophones Planification, Décision, et Apprentissage pour la conduite de systèmes, France, 2013.
http://hal.inria.fr/hal-00922133

Scientific Books (or Scientific Book chapters)

[63]
P.-Y. Oudeyer, A. Baranes, F. Kaplan.
Intrinsically Motivated Learning of Real World Sensorimotor Skills with Developmental Constraints, in: Intrinsically Motivated Learning in Natural and Artificial Systems, G. Baldassarre, M. Mirolli (editors), Springer, February 2013.
http://hal.inria.fr/hal-00788611
[64]
P. Oudeyer.
Self-Organization: Complex Dynamical Systems in the Evolution of Speech, in: The Language Phenomenon, P. Binder, K. Smith (editors), Springer, 2013.
http://hal.inria.fr/hal-00788509

Other Publications

[65]
M. Lopes, B. Clement, D. Roy, P.-Y. Oudeyer.
Multi-Armed Bandits for Intelligent Tutoring Systems, 2013.
http://hal.inria.fr/hal-00913669
References in notes
[66]
L. Steels, R. Brooks (editors)
The Artificial Life Route to Artificial Intelligence: Building Embodied, Situated Agents, L. Erlbaum Associates Inc., Hillsdale, NJ, USA, 1995.
[67]
B. Argall, S. Chernova, M. Veloso.
A Survey of Robot Learning from Demonstration, in: Robotics and Autonomous Systems, 2009, vol. 57, no 5, pp. 469–483.
[68]
M. Asada, S. Noda, S. Tawaratsumida, K. Hosoda.
Purposive Behavior Acquisition On A Real Robot By Vision-Based Reinforcement Learning, in: Machine Learning, 1996, vol. 23, pp. 279-303.
[69]
A. Barto, S. Singh, N. Chentanez.
Intrinsically Motivated Learning of Hierarchical Collections of Skills, in: Proceedings of the 3rd International Conference on Development and Learning (ICDL 2004), Salk Institute, San Diego, 2004.
[70]
D. Berlyne.
Conflict, Arousal and Curiosity, McGraw-Hill, 1960.
[71]
C. Breazeal.
Designing sociable robots, The MIT Press, 2004.
[72]
R. Brooks, C. Breazeal, R. Irie, C. C. Kemp, B. Scassellati, M. Williamson.
Alternative essences of intelligence, in: Proceedings of 15th National Conference on Artificial Intelligence (AAAI-98, AAAI Press, 1998, pp. 961–968.
[73]
A. Clark.
Mindware: An Introduction to the Philosophy of Cognitive Science, Oxford University Press, 2001.
[74]
D. Cohn, Z. Ghahramani, M. Jordan.
Active learning with statistical models, in: Journal of artificial intelligence research, 1996, vol. 4, pp. 129–145.
[75]
W. Croft, D. Cruse.
Cognitive Linguistics, Cambridge Textbooks in Linguistics, Cambridge University Press, 2004.
[76]
M. Csikszenthmihalyi.
Flow-the psychology of optimal experience, Harper Perennial, 1991.
[77]
B. Damas, J. Santos-Victor.
Online Learning of Single- and Multivalued Functions with an Infinite Mixture of Linear Experts, in: Neural Computation, 2013, vol. 25, no 11, pp. 3044–3091.
[78]
P. Dayan, W. Belleine.
Reward, motivation and reinforcement learning, in: Neuron, 2002, vol. 36, pp. 285–298.
[79]
E. Deci, R. Ryan.
Intrinsic Motivation and Self-Determination in Human Behavior, Plenum Press, 1985.
[80]
J. Elman.
Learning and development in neural networks: The importance of starting small, in: Cognition, 1993, vol. 48, pp. 71–99.
[81]
D. Filliat, E. Battesti, S. Bazeille, G. Duceux, A. Gepperth, L. Harrath, I. Jebari, R. Pereira, A. Tapus, C. Meyer, S.-H. Ieng, R. Benosman, E. Cizeron, J.-C. Mamanna, B. Pothier.
RGBD object recognition and visual texture classification for indoor semantic mapping, in: Technologies for Practical Robot Applications (TePRA), 2012 IEEE International Conference on, United States, 2012, pp. 127 - 132.
http://hal.inria.fr/hal-00755295
[82]
C. Fleischer, A. Wege, K. Kondak, G. Hommel.
Application of EMG signals for controlling exoskeleton robots, in: Biomedizinische Technik, 2006, vol. 51, no 5/6, pp. 314–319.
[83]
A. Gepperth, L.-C. Caron.
Simultaneous concept formation driven by predictability, in: International conference on development and learning, San Diego, États-Unis, October 2012.
[84]
A. Gepperth, B. Dittes, M. Garcia Ortiz.
The contribution of context information: a case study of object recognition in an intelligent car, in: Neurocomputing, February 2012, vol. 94. [ DOI : 10.1016/j.neucom.2012.03.008 ]
http://hal.inria.fr/hal-00763650
[85]
A. Gepperth.
Co-training of context models for real-time object detection, in: IEEE Symposium on Intelligent Vehicles, Madrid, Espagne, June 2012.
http://hal.inria.fr/hal-00763676
[86]
A. Gepperth.
Efficient online bootstrapping of sensory representations, in: Neural Networks, December 2012. [ DOI : 10.1016/j.neunet.2012.11.002 ]
http://hal.inria.fr/hal-00763660
[87]
D. Gouaillier, V. Hugel, P. Blazevic, C. Kilner, J. Monceaux, P. Lafourcade, B. Marnier, J. Serre, B. Maisonnier.
The nao humanoid: a combination of performance and affordability, in: CoRR, vol. abs/0807.3223, 2008.
[88]
I. Ha, Y. Tamura, H. Asama, J. Han, D. Hong.
Development of open humanoid platform DARwIn-OP, in: SICE Annual Conference (SICE), 2011 Proceedings of, IEEE, 2011, pp. 2178–2181.
[89]
S. Harnad.
The symbol grounding problem, in: Physica D, 1990, vol. 40, pp. 335–346.
[90]
M. Hasenjager, H. Ritter.
Active learning in neural networks, Physica-Verlag GmbH, Heidelberg, Germany, Germany, 2002, pp. 137–169.
[91]
J. Haugeland.
Artificial Intelligence: the very idea, The MIT Press, Cambridge, MA, USA, 1985.
[92]
J.-C. Horvitz.
Mesolimbocortical and nigrostriatal dopamine responses to salient non-reward events, in: Neuroscience, 2000, vol. 96, no 4, pp. 651-656.
[93]
X. Huang, J. Weng.
Novelty and reinforcement learning in the value system of developmental robots, in: Proceedings of the 2nd international workshop on Epigenetic Robotics : Modeling cognitive development in robotic systems, C. Prince, Y. Demiris, Y. Marom, H. Kozima, C. Balkenius (editors), Lund University Cognitive Studies 94, 2002, pp. 47–55.
[94]
S. Ivaldi, N. Lyubova, D. Gérardeaux-Viret, A. Droniou, S. Anzalone, M. Chetouani, D. Filliat, O. Sigaud.
Perception and human interaction for developmental learning of objects and affordances, in: Proc. of the 12th IEEE-RAS International Conference on Humanoid Robots - HUMANOIDS, Japan, 2012, to appear.
http://hal.inria.fr/hal-00755297
[95]
M. Johnson.
Developmental Cognitive Neuroscience, 2nd, Blackwell publishing, 2005.
[96]
W. B. Knox, P. Stone.
Combining manual feedback with subsequent MDP reward signals for reinforcement learning, in: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'10), 2010, pp. 5–12.
[97]
R. Laurent, C. Moulin-Frier, P. Bessière, J.-L. Schwartz, J. Diard.
Integrate, yes, but what and how? A computational approach of perceptuo-motor fusion in speech perception., 2012, Accepted commentary in Behavioral and Brain Sciences, in Press..
http://hal.inria.fr/hal-00765973
[98]
M. Lopes, T. Cederborg, P.-Y. Oudeyer.
Simultaneous Acquisition of Task and Feedback Models, in: Development and Learning (ICDL), 2011 IEEE International Conference on, Germany, 2011, pp. 1 - 7. [ DOI : 10.1109/DEVLRN.2011.6037359 ]
http://hal.inria.fr/hal-00636166/en
[99]
M. Lopes, P.-Y. Oudeyer.
The Strategic Student Approach for Life-Long Exploration and Learning, in: IEEE Conference on Development and Learning / EpiRob 2012, San Diego, United States, November 2012.
http://hal.inria.fr/hal-00755216
[100]
M. Lungarella, G. Metta, R. Pfeifer, G. Sandini.
Developmental Robotics: A Survey, in: Connection Science, 2003, vol. 15, no 4, pp. 151-190.
[101]
O. Ly, M. Lapeyre, P. Oudeyer.
Bio-inspired vertebral column, compliance and semi-passive dynamics in a lightweight humanoid robot, in: Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, IEEE, 2011, pp. 1465–1472.
[102]
N. Lyubova, D. Filliat.
Developmental Approach for Interactive Object Discovery, in: Neural Networks (IJCNN), The 2012 International Joint Conference on, Australia, 2012, pp. 1-7.
http://hal.inria.fr/hal-00755298
[103]
O. Mangin, P.-Y. Oudeyer.
Learning the Combinatorial Structure of Demonstrated Behaviors with Inverse Feedback Control, in: Human Behavior Understanding, Lecture notes in computer science, Springer, October 2012, vol. 7559.
http://hal.inria.fr/hal-00764448
[104]
O. Mangin, P.-Y. Oudeyer.
Learning to recognize parallel combinations of human motion primitives with linguistic descriptions using non-negative matrix factorization, in: Proceedings of 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, October 2012.
http://hal.inria.fr/hal-00764353
[105]
J. Marshall, D. Blank, L. Meeden.
An Emergent Framework for Self-Motivation in Developmental Robotics, in: Proceedings of the 3rd International Conference on Development and Learning (ICDL 2004), Salk Institute, San Diego, 2004.
[106]
M. Mason, M. Lopes.
Robot Self-Initiative and Personalization by Learning through Repeated Interactions, in: 6th ACM/IEEE International Conference on Human-Robot, Switzerland, 2011. [ DOI : 10.1145/1957656.1957814 ]
http://hal.inria.fr/hal-00636164/en
[107]
P. Miller.
Theories of developmental psychology, 4th, New York: Worth, 2001.
[108]
C. Moulin-Frier, R. Laurent, P. Bessière, J.-L. Schwartz, J. Diard.
Adverse conditions improve distinguishability of auditory, motor and percep-tuo-motor theories of speech perception: an exploratory Bayesian modeling study, in: Language and Cognitive Processes, 2012, vol. 27, no 7-8 Special Issue: Speech Recognition in Adverse Conditions, pp. 1240-1263. [ DOI : 10.1080/01690965.2011.645313 ]
http://hal.archives-ouvertes.fr/hal-00642311
[109]
S. M. Nguyen, A. Baranes, P.-Y. Oudeyer.
Bootstrapping Intrinsically Motivated Learning with Human Demonstrations, in: IEEE International Conference on Development and Learning, Frankfurt, Germany, 2011.
http://hal.inria.fr/hal-00645986/en
[110]
S. M. Nguyen, A. Baranes, P.-Y. Oudeyer.
Constraining the Size Growth of the Task Space with Socially Guided Intrinsic Motivation using Demonstrations., in: IJCAI Workshop on Agents Learning Interactively from Human Teachers (ALIHT), Barcelona, Spain, 2011.
http://hal.inria.fr/hal-00645995/en
[111]
S. M. Nguyen, P.-Y. Oudeyer.
Active Choice of Teachers, Learning Strategies and Goals for a Socially Guided Intrinsic Motivation Learner, in: Paladyn Journal of Bejavioral Robotics, September 2012, vol. 3, no 3, pp. 136-146. [ DOI : 10.2478/s13230-013-0110-z ]
http://hal.inria.fr/hal-00936932
[112]
S. M. Nguyen, P.-Y. Oudeyer.
Interactive Learning Gives the Tempo to an Intrinsically Motivated Robot Learner, in: IEEE-RAS International Conference on Humanoid Robots, Osaka, Japan, December 2012.
http://hal.inria.fr/hal-00762753
[113]
S. M. Nguyen, P.-Y. Oudeyer.
Properties for Efficient Demonstrations to a Socially Guided Intrinsically Motivated Learner, in: 21st IEEE International Symposium on Robot and Human Interactive Communication, Paris, France, September 2012.
http://hal.inria.fr/hal-00762758
[114]
S. M. Nguyen, P.-Y. Oudeyer.
Socially Guided Intrinsically Motivated Learner, in: IEEE International Conference on Development and Learning, San Diego, United States, 2012. [ DOI : 10.1109/DevLrn.2012.6400809 ]
http://hal.inria.fr/hal-00936960
[115]
S. M. Nguyen, P.-Y. Oudeyer.
Whom Will an Intrinsically Motivated Robot Learner Choose to Imitate from?, in: Post-Graduate Conference on Robotics and Development of Cognition: RobotDoC-PhD 2012, Lausanne, Switzerland, September 2012.
http://hal.inria.fr/hal-00762762
[116]
R. Nowak.
The Geometry of Generalized Binary Search, in: Information Theory, Transactions on, 2011, vol. 57, no 12, pp. 7893–7906.
[117]
P.-Y. Oudeyer, F. Kaplan.
Intelligent adaptive curiosity: a source of self-development, in: Proceedings of the 4th International Workshop on Epigenetic Robotics, L. Berthouze, H. Kozima, C. Prince, G. Sandini, G. Stojanov, G. Metta, C. Balkenius (editors), Lund University Cognitive Studies, 2004, vol. 117, pp. 127–130.
[118]
P.-Y. Oudeyer, F. Kaplan.
What is intrinsic motivation? A typology of computational approaches, in: Frontiers in Neurorobotics, 2007, vol. 1, no 1.
[119]
P.-Y. Oudeyer.
Sur les interactions entre la robotique et les sciences de l'esprit et du comportement, in: Informatique et Sciences Cognitives : influences ou confluences ?, C. Garbay, D. Kaiser (editors), Presses Universitaires de France, 2009.
http://hal.inria.fr/inria-00420309/en/
[120]
P.-Y. Oudeyer.
L'auto-organisation dans l'évolution de la parole, in: Parole et Musique: Aux origines du dialogue humain, Colloque annuel du Collège de France, S. Dehaene, C. Petit (editors), Odile Jacob, 2009, pp. 83-112.
http://hal.inria.fr/inria-00446908/en/
[121]
A. Revel, J. Nadel.
How to build an imitator?, in: Imitation and Social Learning in Robots, Humans and Animals: Behavioural, Social and Communicative Dimensions, K. Dautenhahn, C. Nehaniv (editors), Cambridge University Press, 2004.
[122]
T. Schatz, P.-Y. Oudeyer.
Learning motor dependent Crutchfield's information distance to anticipate changes in the topology of sensory body maps, in: IEEE International Conference on Learning and Development, Chine Shangai, 2009.
http://hal.inria.fr/inria-00420186/en/
[123]
M. Schembri, M. Mirolli, G. Baldassarre.
Evolving internal reinforcers for an intrinsically motivated reinforcement-learning robot, in: IEEE 6th International Conference on Development and Learning, 2007. ICDL 2007., July 2007, pp. 282-287.
http://dx.doi.org/10.1109/DEVLRN.2007.4354052
[124]
J. Schmidhuber.
Curious Model-Building Control Systems, in: Proceedings of the International Joint Conference on Neural Networks, Singapore, IEEE press, 1991, vol. 2, pp. 1458–1463.
[125]
W. Schultz, P. Dayan, P. Montague.
A neural substrate of prediction and reward, in: Science, 1997, vol. 275, pp. 1593-1599.
[126]
M. Schwarz, M. Schreiber, S. Schueller, M. Missura, S. Behnke.
NimbRo-OP Humanoid TeenSize Open Platform.
[127]
F. Stulp, P.-Y. Oudeyer.
Emergent Proximo-Distal Maturation through Adaptive Exploration, in: International Conference on Development and Learning (ICDL), 2012.
[128]
F. Stulp, O. Sigaud.
Path Integral Policy Improvement with Covariance Matrix Adaptation, in: Proceedings of the 29th International Conference on Machine Learning (ICML), 2012.
[129]
F. Stulp, O. Sigaud.
Policy Improvement Methods: Between Black-Box Optimization and Episodic Reinforcement Learning, 2012, 34 p.
http://hal.inria.fr/hal-00738463
[130]
F. Stulp.
Adaptive Exploration for Continual Reinforcement Learning, in: International Conference on Intelligent Robots and Systems (IROS), 2012.
[131]
E. Thelen, L. B. Smith.
A dynamic systems approach to the development of cognition and action, MIT Press, Cambridge, MA, 1994.
[132]
A. L. Thomaz, C. Breazeal.
Teachable robots: Understanding human teaching behavior to build more effective robot learners, in: Artificial Intelligence Journal, 2008, vol. 172, pp. 716-737.
[133]
A. Turing.
Computing machinery and intelligence, in: Mind, 1950, vol. 59, pp. 433-460.
[134]
F. Varela, E. Thompson, E. Rosch.
The embodied mind : Cognitive science and human experience, MIT Press, Cambridge, MA, 1991.
[135]
J. Weng, J. McClelland, A. Pentland, O. Sporns, I. Stockman, M. Sur, E. Thelen.
Autonomous mental development by robots and animals, in: Science, 2001, vol. 291, pp. 599-600.