Pierre-Yves Oudeyer
Artificial Intelligence, Machine Learning, Cognitive Science
I am research director (DR1) at Inria, heading the Flowers team at Inria Bordeaux Sud-Ouest and Univ. Bordeaux (see PhD students). I was also a research visitor at Microsoft Research Montreal (2021-22), and permanent researcher in Sony Computer Science Laboratory for 8 years (1999-2007).
Together with a great team, I study lifelong autonomous learning, and the self-organization of behavioural, cognitive and language structures, at the frontiers of artificial intelligence and cognitive sciences. I use machines as tools to understand better how children learn and develop, and I study how one can build machines that learn autonomously like children, as well as integrate within human cultures, within the new field of developmental artificial intelligence.
We work on applications in education, aiming to use AI techniques as tools in the service of humans, fostering learning, curiosity and creativity (e.g. our algorithms are used in Adaptiv’Maths). We also do outreach for democratizing access and understanding of AI, in diverse contexts ranging from schools to artistic projects. These projects led to several spin-off from the team, e.g. start-ups or NGOs.
For both fundamental and applied projects, we take an open science and open-source approach (e.g. see our team’s GitHub, and the Poppy open-source educational robotic kits with the associated community, used by >30k children in world in several countries).
We collaborate with many academic labs (e.g. Sorbonne-Université, MILA, Inserm) and industry (e.g. HuggingFace, Microsoft Research, evidenceB, Ubisoft, Poïetis, OnePoint).
Important note: If you wish to contact me for an application, please send an email including [application] in the object. For any other reason, please include [information] in the object. As I receive many emails, I may not be able to see your email if you do not include one of these tags.
In more details:
In AI, we study how machines can efficiently acquire world models and open-ended repertoires of skills over an extended time span. We develop autotelic deep reinforcement learning agents able to learn to represent and generate their own goals, leveraging language and culture as cognitive tools for creative exploration, planning and abstraction (see our recent perspective paper discussing new opportunities at the crossroads of Deep RL and large language models, where llms are seen as culture models). This research also involves automatic curriculum learning.
With colleagues, I develop computational theories of curiosity and intrinsically motivated learning (with AI, neuroscience and developmental psychology perspectives). We proposed the learning progress hypothesis to explain key aspects of human spontaneous exploration. We showed how curiosity-driven exploration can self-organize long term developmental trajectories, accouting for how infants progressively develop vocal skills, tool use and language.
I also work on theoretical models of the origins and evolution of speech and language, studying the role of self-organization in neural networks and agents dynamical coupling. In the new edition of my book “Self-organization in the evolution of speech” (to appear in 2020 at OUP, CC-BY), I present an integrated view of the roles of self-organization and intrinsic motivation in the origins of language.
Educational applications. We use curiosity-driven learning algorithms to personalize sequences of exercises for human learners, maximising learning efficiency and motivation: after an initial series of experiments with >1000 children in primary schools, we are now working with a consortium of edTech companies and the support of French ministry of Education to integrate this approach in an educational software for wide dissemination. We developed open-source educational robotics kits (some used by dozens of thousands of children in the world and adapted in largely disseminated educational books e.g. from Main à la Pâte), now disseminated by a non-governmental organization and a start-up.
AI for science: Recently, we started exploring the new area of automated discovery of self-organized patterns in complex systems, leveraging intrinsically motivated goal exploration and unsupervised representation learning.
Robotics applications. In robotics, our curiosity algorithms have been used within the Sony Aibo and Qrio humanoid entertainment robots. I also worked on emotional speech synthesis technologies used in some Playstation video games, and various forms of adaptive human-computer interfaces.
AI and the arts: We collaborate with artists through diverse projects aiming to explore the links between AI and society (e.g. here, here or here), in particular to facilitate understanding of AI and its societal dimensions in the general public.
Quick links:
- Science: Publications, Videos, Patents, Google Scholar
- Bio: Bio, CV, Awards, Collective Responsibilities
- Team: Flowers team, PhD students, Jobs
- Team activity report: 2019 yearly activity report, Quadriennal Flowers lab report (2013-2016)
- Join open science discussion on the Flowers open lab forum
Selected publications:
Selected publications by topic:
Machine Learning, Artificial Intelligence, Deep RL and Developmental AI,
- Language-grounded Intrinsically Motivated Deep RL:
- Colas, C., Karch, T., Lair, N., Dussoux, J. M., Moulin-Frier, C., Dominey, P., & Oudeyer, P. Y. (2020). Language as a Cognitive Tool to Imagine Goals in Curiosity Driven Exploration. Advances in Neural Information Processing Systems (Neurips 2020), 33.
- Akakzia, A., Colas, C., Oudeyer, P. Y., Chetouani, M., & Sigaud, O. (2021, May). Grounding Language to Autonomously-Acquired Skills via Goal Generation. In ICLR 2021.
- Goal-conditioned Intrinsically Motivated Deep Reinforcement Learning
- Colas, C., Fournier, P., & Chetouani, M., Sigaud, O., Oudeyer, P. Y., (2019). CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning. In International Conference on Machine Learning (ICML 2019). Code and videos.
- Colas, C., Sigaud, O., Oudeyer, P. Y. (2018). GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms. In Proceedings of International Conference on Machine Learning (ICML 2018), arXiv preprint arXiv:1802.05054. Other links: code and blog post.
- Curiosity-driven deep unsupervised learning, learning independently controllable features
- Laversanne-Finot, A., Péré, A., Oudeyer, P-Y. (2018) Curiosity Driven Exploration of Learned Disentangled Goal Spaces, In Proceedings of Conference on Robot Learning (CoRL 2018).
- Péré, A., Forestier, S., Sigaud, O., & Oudeyer, P. Y. (2018). Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration. In Proceedings of International Conference on Learning Representations (ICLR 2018), arXiv preprint arXiv:1803.00781. Other links: code.
- Automatic Curriculum Learning for training Deep RL agents that generalize
- Portelas, R., Colas, C., Weng, L., Hofmann, K., & Oudeyer, P. Y. (2021). Automatic Curriculum Learning For Deep RL: A Short Survey. In IJCAI 2020-International Joint Conference on Artificial Intelligence.
- Portelas, R., Colas, C., Hofmann, K., & Oudeyer, P. Y. (2019). Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments. Proceedings of Conference on Robot Learning (CoRL 2019). See pdf and code.
- Automated discovery in self-organized systems
- Etcheverry, M., Moulin-Frier, C., & Oudeyer, P. Y. (2020, December). Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems. In NeurIPS 2020-34th Conference on Neural Information Processing Systems.
- Reinke, C., Etcheverry, M., & Oudeyer, P. Y. (2020). Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems. In Proceedings of International Conferenc on Learning Representations (ICLR 2020, oral).
- Intrinsically Motivated Goal Exploration and Curriculum Learning
- Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning.
. (2017)
arXiv:1708.02190 - Baranes, A., Oudeyer, P-Y. (2013) Active Learning of Inverse Models with Intrinsically Motivated Goal Exploration in Robots, Robotics and Autonomous Systems, 61(1), pp. 49-73.
- Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning.
- Intrinsically Motivated Goal Exploration and Strategic Learning
- Nguyen, M., & Oudeyer, P.-Y. (2013). Active choice of teachers, learning strategies and goals for a socially guided intrinsic motivation learner. Paladyn: Journal of Behavioural Robotics, 3(3), 136–146.
- Lopes M., Oudeyer P-Y. (2012) The Strategic Student Approach for Life-Long Exploration and Learning, in Proceedings of IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-Epirob), San Diego, USA. https://flowers.inria.fr/mlopes/myrefs/12-ssp.pdf
- Developmental Constraints for Lifelong Robot Learning in High-Dimensions
- Oudeyer P-Y., Baranes A., Kaplan F. (2013) Intrinsically Motivated Learning of Real-World Sensorimotor Skills with Developmental Constraints, in Intrinsically Motivated Learning in Natural and Artificial Systems, eds. Baldassarre G. and Mirolli M., Springer.
- Knowledge-based Intrinsic Motivation and Artificial Curiosity in Developmental Robotics
- Oudeyer P-Y. and Kaplan F. (2007) Intrinsic Motivation Systems for Autonomous Mental Development Oudeyer P-Y, Kaplan , F. and Hafner, V. (2007) IEEE Transactions on Evolutionary Computation, 11(2), pp. 265–286.
- Oudeyer P-Y. and Kaplan F. (2007) What is intrinsic motivation? A typology of computational approaches , Frontiers in Neurorobotics, 1:6
- Kaplan, F., Oudeyer, P-Y (2003) Motivational principles for visual know-how development In Prince, C.G. et al., editors, Proceedings of the 3rd international workshop on Epigenetic Robotics : Modeling cognitive development in robotic systems, no. 101, pages 73-80, 2003. Lund University Cognitive Studies.
- SOFTWARE: A number of these models are available in the open-source Explauto Python library, available on GitHub (code written by C. Moulin-Frier and P. Rouanet): Explauto: an open-source Python library to study autonomous exploration in developmental robotics Clément Moulin-Frier; Pierre Rouanet; Pierre-Yves Oudeyer
ICDL-Epirob – International Conference on Development and Learning, Epirob, Oct 2014, Genoa, Italy.
- Intrinsically Motivated Exploration for Tool Use
- Forestier S, Oudeyer P-Y. 2016. Modular Active Curiosity-Driven Discovery of Tool Use. 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
- Multimodal Learning of Language in Robots
- Cederborg, T. and Oudeyer, P-Y. (2013) From Language to Motor Gavagai: Unified Imitation Learning of Multiple Linguistic and Non-linguistic Sensorimotor Skills, IEEE Transactions on Autonomous Mental Development. 5(3), pp. 222-239.
- Mangin O, Filliat D, ten Bosch L, Oudeyer P-Y (2015) MCA-NMF: Multimodal Concept Acquisition with Non-Negative Matrix Factorization, PLoS ONE 10(10): e0140732. doi:10.1371/journal.pone.0140732
- Human-Robot Interaction: Adaptive Interfaces
- Pierre Rouanet, Pierre-Yves Oudeyer, Fabien Danieau and David Filliat (2013) Teaching a robot how to recognize new visual objects: a study of the impact of interfaces IEEE Transactions on Robotics, vol.29, no.2, pp.525,541, Bibtex
- Grizou, J., Lopes, M. and Oudeyer, P-Y. (2013) Robot Learning Simultanously a Task and How to Interpret Human Instructions, Proceedings of IEEE International Conference on Development and Learning and Epigenetic Robotics, IEEE ICDL-Epirob, Osaka, Japan.
- Kaplan, F., Oudeyer, P-Y., Kubinyi, E. and Miklosi, A. (2002) Robotic clicker training, Robotics and Autonomous Systems, 38(3-4), pp. 197–206.
- Emotional Speech Synthesis and Recognition
- Oudeyer P-Y. (2003) The production and recognition of emotions in speech: features and algorithms International Journal in Human-Computer Studies, 59(1-2), pp. 157–183.
Cognitive Science: Models of Human Developmental Learning and Language Evolution
- Overview (Curiosity-driven Developmental Process and the Evolution of Language)
- Gottlieb, J. and Oudeyer, P-Y. (2018) Towards a Neuroscience of Active Sampling and Curiosity, Nature Reviews Neuroscience, 19(12), 758-770.
- Oudeyer, P-Y. and Smith. L. (2016) How Evolution may work through Curiosity-driven Developmental Process , Topics in Cognitive Science, 1-11.
- Oudeyer, P-Y. (2018) Computational Theories of Curiosity-driven Learning, in “The New Science of Curiosity”, ed. G. Gordon, NOVA.
- Models of Curiosity and its Role in Self-Organization of Developmental Structures
- Oudeyer P-Y, Kaplan , F. and Hafner, V. (2007) Intrinsic Motivation Systems for Autonomous Mental Development IEEE Transactions on Evolutionary Computation, 11(2), pp. 265–286.
- Gottlieb, J., Oudeyer, P-Y., Lopes, M., Baranes, A. (2013) Information Seeking, Curiosity and Attention: Computational and Neural Mechanisms, Trends in Cognitive Science, , 17(11), pp. 585-596. Bibtex Pdf preprint
- Kaplan F. and Oudeyer P-Y. (2007a) In search of the neural circuits of intrinsic motivation, Frontiers in Neuroscience, 1(1), pp.225–236.
- SOFTWARE: A number of these models are available in the open-source Explauto Python library, available on GitHub (code written by C. Moulin-Frier and P. Rouanet): Explauto: an open-source Python library to study autonomous exploration in developmental robotics Clément Moulin-Frier; Pierre Rouanet; Pierre-Yves Oudeyer ICDL-Epirob – International Conference on Development and Learning, Epirob, Oct 2014, Genoa, Italy.
- Curiosity in humans: behavioral experiments and data mining
- Adrien Baranes, Pierre-Yves Oudeyer, Jacqueline Gottlieb (2015) Eye Movements Reveal Epistemic Curiosity in Human Observers, Vision Research, 117, pp. 81-90. [pdf]
- Adrien Baranes, Pierre-Yves Oudeyer, Jacqueline Gottlieb (2014) The effects of task difficulty, novelty and the size of the search space on intrinsically motivated exploration, Frontiers in Neuroscience, 2014, 8 (317), pp.1-9. <10.3389/fnins.2014.00317> [pdf] [Bib]
- Curiosity in Language Acquisition and Speech Development
- . (2017) A Unified Model of Speech and Tool Use Early Development. Proceedings of the 39th Annual Meeting of the Cognitive Science Society.
- Oudeyer, P-Y. (2015) Open challenges in understanding development and evolution of speech forms: The roles of embodied self-organization, motivation and active exploration , Journal of Phonetics, in press, http://dx.doi.org/10.1016/j.wocn.2015.09.001.
- Moulin-Frier, C., Nguyen, S.M., Oudeyer, P-Y. (2014) Self-organization of early vocal development in infants and machines: the role of intrinsic motivation, Frontiers in Psychology (Cognitive Science), 4(1006), Bibtex
- Kaplan, F., Oudeyer, P-Y., Bergen B. (2008) Computational Models in the Debate over Language Learnability, Infant and Child Development, 17(1), pp. 55–80.
- Oudeyer P-Y., Kaplan F. (2006) Discovering Communication, Connection Science, 18(2), pp. 189–206.
- Language Acquisition, Sensorimotor Grounding and the Gavagai problem
- Mangin O, Filliat D, ten Bosch L, Oudeyer P-Y (2015) MCA-NMF: Multimodal Concept Acquisition with Non-Negative Matrix Factorization, PLoS ONE 10(10): e0140732. doi:10.1371/journal.pone.0140732
- Cederborg, T. and Oudeyer, P-Y. (2013) From Language to Motor Gavagai: Unified Imitation Learning of Multiple Linguistic and Non-linguistic Sensorimotor Skills, IEEE Transactions on Autonomous Mental Development. 5(3), pp. 222-239.
- Self-Organization in the Evolution of Speech
- Oudeyer, P-Y. (2006) Self-Organization in the Evolution of Speech, Oxford University Press.
- Oudeyer, P-Y. (2005) The Self-Organization of Speech Sounds, Journal of Theoretical Biology, 233(3), pp. 435–449.
- Darwinian Dynamics in Language Evolution
- Oudeyer P-Y., Kaplan F. (2007) Language Evolution as a Darwinian Process: Computational Studies, Cognitive Processing, , 8(1), pp. 21–35.
- Oudeyer, P-Y (2005) How phonological structures can be culturally selected for learnability, Adaptive Behavior, 13(4), pp. 269–280.
Adaptive Human-Machine Interfaces, BCI, Emotional Speech Processing
- Calibration-Free Brain-Computer Interfaces (BCI)
- I. Iturrate, J. Grizou, J. Omedes, P.-Y. Oudeyer, M. Lopes and L. Montesan (2015) Exploiting task constraints for self-calibrated brain-machine interface control using error-related potentials, PLOS One, 2015.
- Jonathan Grizou; Iñaki Iturrate; Luis Montesano; Pierre-Yves Oudeyer; Manuel Lopes (2014) Calibration-Free BCI Based Control , Proceedings of Twenty-Eighth AAAI Conference on Artificial Intelligence, Jul 2014, Quebec, Canada. Bibtex
- Adaptive Learning of how to Interpret Human Instruction/Social Signals
- Grizou, J., Lopes, M. and Oudeyer, P-Y. (2013) Robot Learning Simultanously a Task and How to Interpret Human Instructions, Proceedings of IEEE International Conference on Development and Learning and Epigenetic Robotics, IEEE ICDL-Epirob, Osaka, Japan. [videos of talk] Bibtex
- Thomas Cederborg; Pierre-Yves Oudeyer (2013) From Language to Motor Gavagai: Unified Imitation Learning of Multiple Linguistic and Non-linguistic Sensorimotor Skills, IEEE Transactions on Autonomous Mental Development (TAMD), IEEE, 2013 Bibtex
- Emotional Speech Synthesis and Recognition
- Oudeyer P-Y. (2003) The production and recognition of emotions in speech: features and algorithms, International Journal in Human-Computer Studies, 59(1-2), pp. 157–183. Bibtex
- Intuitive Interfaces for Human-Robot Interaction
- Pierre Rouanet; Pierre-Yves Oudeyer
; Fabien Danieau; David Filliat (2013) The Impact of Human-Robot Interfaces on the Learning of Visual Objects , IEEE Transactions on Robotics, IEEE Robotics and Automation Society, 2013, 29 (2), pp. 525-541 Bibtex - Robotic clicker training Kaplan, F., Oudeyer, P-Y., Kubinyi, E. and Miklosi, A. (2002) Robotics and Autonomous Systems, 38(3-4), pp. 197–206. Bibtex
- Pierre Rouanet; Pierre-Yves Oudeyer
Educational Technologies
- Theoretical perspective:
- Intrinsic motivation, curiosity and learning: theory and applications in educational technologies
P-Y. Oudeyer, J. Gottlieb and M. Lopes (2016)
Progress in Brain Research, 229, pp. 257-284.
- Intrinsic motivation, curiosity and learning: theory and applications in educational technologies
- Fostering human curiosity-driven learning
- Alaimi, M., Law, E., Pantasdo, K. D., Oudeyer, P. Y., & Sauzeon, H. (2020). Pedagogical Agents for Fostering Question-Asking Skills in Children. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI 2020).
- Ceha, J., Chhibber, N., Goh, J., McDonald, C., Oudeyer, P-Y., Kulic, D., Law, E. (2019) Expression of Curiosity in Social Robots: Design, Perception, and Effects on Behaviour, Proceedings of CHI 2019. Talk video.
- Adaptive personalization in intelligent tutoring systems, fostering efficient learning AND intrinsic motivation
- Benjamin Clement, Didier Roy, Pierre-Yves Oudeyer, Manuel Lopes (2015) Multi-Armed Bandits for Intelligent Tutoring Systems , Journal of Educational Data Mining (JEDM), Vol 7, No 2, 2015.
- Educational robotics
- Didier Roy, Gordana Gerber, Stéphane Magnenat, Fanny Riedo, Morgane Chevalier, Pierre-Yves Oudeyer, Francesco Mondada (2015) IniRobot: a pedagogical kit to initiate children to concepts of robotics and computer science , 6th International Conference on Robotics in Education, 2015.
Outreach Projects
Poppy: an Open-Source 3D Printed Robotic Platform
Link to information about the Poppy humanoid robot : Poppy Project web site. Poppy is an open-source 3D printed robot for science, education and art designed by the Flowers team. It was built to study the impact of the body on sensorimotor development and cognition: it makes it possible to really consider the body as an experimental variable. See article at Humanoids 2013 conference.
Poppy Overview from Poppy Project on Vimeo.
IniRobot: un kit pédagogique pour l'initiation à la robotique à l'école primaire
IniRobot: IniRobot est une série d’activités pédagogiques “clés en main” destinée à la découverte de la robotique et de la programmation à l’école primaire, en particulier lors des activités périscolaires. Ce kit est libre d’utilisation (Creative Commons CC-BY-SA) et utilise le robot Thymio développé à l’EPFL. Il est déployé en France dans les activités périscolaires des écoles de plusieurs villes, dont Lille, Talence et Lormont. Il a été développé par Didier Roy, Thomas Guitard et Pierre-Yves Oudeyer dans l’équipe Flowers, et est partagé sur le site participatif Dessine-moi un robot. Art and Science
I collaborate regularly with artist within project that explore the frontiers between art and science. This has been the opportunity to create original connections between the general public and our scientific projects, in particular by bringing people to ask themselves and to ourselves stimulating questions about the position of such scientific projects within society at large.
Examples of such projects include:
- Artistic residency “Etres et Numériques” (2014), a study of movement and emotions through the interaction between the humanoid robot Poppy and a dancer. This happened at Lycée Saintonge, in Bordeaux, and also included workshop with young students allowing them to discover various aspects of robotics and its role in society.#01- artistique | robotique | médiation – Recherche chien noir à tête d’ours, résidence Lycée Saintonge. Bordeaux 2014. from comacina, capsule créative on Vimeo.
- Ergo-Robots Experiment at “Mathematics: A Beautiful Elsewhere” (2012) Exhbition at Fondation Cartier pour l’Art Contemporain (Paris, France), with a collaboration with movie maker David Lynch.
- C2M1 (2010): “associate scientist” with artists for an art live theatrical performance about the impact of technology upon language (with C2M1 group in Boulogne-Billancourt, lead by Magali Desbazeille and Siegfried Canto). Video complète du spectacle C2M ici.
News
New blog post
Our now blog post is out! See Language as a Cognitive Tool: Dall-E, Humans and Vygotskian RL Agents
Inria/National Academy of Science Prize 2018
I have received in october 2018 the Inria Prize of the National Science Academy (computer science researcher under 40).
Industrial transfer in the large scale Adaptiv'Maths edTech project
The team is actively contributing to the large scale Adaptiv’Maths edTech project, coordinated by evidenceB and supported by the French ministry of education, transferring ZPDES machine learning technique we developed (see B. Clement’s PhD) to personalize sequences of maths exercises to be used large scale in French schools and beyond.
Recent papers on curiosity, autotelic deep RL and lifelong learning
Akakzia, A., Colas, C., Oudeyer, P. Y., Chetouani, M., & Sigaud, O. (2021, May). Grounding Language to Autonomously-Acquired Skills via Goal Generation. In ICLR 2021.
Colas, C., Karch, T., Lair, N., Dussoux, J. M., Moulin-Frier, C., Dominey, P., & Oudeyer, P. Y. (2020). Language as a Cognitive Tool to Imagine Goals in Curiosity Driven Exploration. Advances in Neural Information Processing Systems (Neurips 2020), 33.
Etcheverry, M., Moulin-Frier, C., & Oudeyer, P. Y. (2020, December). Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems. In NeurIPS 2020-34th Conference on Neural Information Processing Systems.
Portelas, R., Colas, C., Weng, L., Hofmann, K., & Oudeyer, P. Y. (2020). Automatic Curriculum Learning For Deep RL: A Short Survey. In Proceedings of IJCAI.
Recent talks
Invited talk at Life, Structure and Cognition seminar (IHES, 2022), on “Developmental AI: machines that learn like children and help children learn better”
Developing Minds opening seminar on Developmental AI (2021)
Invited talks at the ICLR 2021 workshops on “Self-supervision for reinforcement learning” and “Never-ending reinforcement learning“.
Invited talks at the ICRA 2021 workshops on “Learning to learn for robotics” and “Towards curious robots: modern approaches for intrinsically motivated intelligent behavior”
Invited talk at ELLIS workshop on Meta-Learning, on Instrinsically motivated learning and automatic curriculum learning as meta-learning.
Invited talk at the Neurips 2020 Deep RL Workshop, on Intrinsically Motivated Goal-conditioned Deep RL.
Invited seminar at the MIT embodied AI seminar, on developmental machine learning, Deep RL and artificial curiosity, April 2020, https://
Keynote talk at the Crossmodal Learning Center Autumn School, on Developmental Machine Learning, Curiosity and Deep RL, Dec. 2020. https://
Invited talk at the Brain and Cognition seminar at the University of Geneva, on Curiosity-driven learning in humans and mahcines, Oct. 2020. https://
Keynote talk at the EGC conference in Brussels, on developmental machine learning, Jan. 2020, https://
Jobs
See the Jobs page on the Flowers website.
Recent talk
Developmental AI: machines that learn like children and help children learn better
Follow @pyoudeyer
Tweets by pyoudeyer
Books
Les robots et l’intelligence artificielle (Nathan, 2020)
Mondes Mosaïques (CNRS Editions, 2016)
Aux sources de la parole (Odile Jacob, 2013)
Self-organization in the evolution of speech (Oxford University Press, 2006, updated version 2020)
In the press
The Economist, sept. 2018: A sense of curiosity is helpful for artificial intelligence; Scientific American, 2018: Intelligent Machines that Learn Like Children; Pour la Science, 2015: L’éveil des bébés robots La recherche, 2015 Le roboticien des sciences humaines Le Monde, nov. 2014 (portrait): Pierre-Yves Oudeyer, aussi curieux que ses robots Socialter, sept. 2014: Les robots seront-ils aussi “bêtes” que nous? Des machines et des hommes Les Echos, mars 2014 : Les robots auront un impact sur la société
Academic Talk on Models of the Evolution of Language
Contact Info
ERC Grant Explorers
My research is partially funded by an ERC Starting Grant (project EXPLORERS) from the European Research Council.