Suggestions
Pierre-Yves Oudeyer
Research Director at Inria, France
Pierre-Yves Oudeyer is a distinguished research director at Inria-France, leading the Flowers research team specializing in autonomous machine learning, cognitive sciences, and developmental robotics. He is a sought-after consultant for organizations focusing on AI, deep reinforcement learning, and educational technologies.
His research delves into the computational mechanisms enabling machines to emulate human child-like learning, emphasizing curiosity-driven learning and social interaction. He has significantly contributed to advancing curiosity-driven learning in AI, deep reinforcement learning, and robotics, including pioneering the concept and implementing it in artificial systems.
Pierre-Yves has been instrumental in developing innovative robotic technologies, such as emotional speech synthesis for Sony Qrio humanoid robot and machine learning techniques for adaptive interaction with the Sony AIBO social robot. He has received prestigious awards like the Inria-National Academy of Science young researcher prize in computer sciences and an ERC Starting Grant.
Apart from numerous academic publications and authored books, Pierre-Yves is credited with co-authoring 11 international patents. His team's noteworthy projects include creating the open-source 3D printed humanoid robot Poppy for reproducible science and education, widely adopted in schools and artistic ventures. He is also involved in a startup company.
Pierre-Yves Oudeyer holds a master's degree in Artificial Intelligence and pattern recognition, a Ph.D. in Artificial Intelligence and cognitive science, and has affiliations with institutions like Pierre and Marie Curie University, Ecole Normale Supérieure de Lyon. He maintains an active online presence through his website and Twitter account.
Highlights
Curiosity-driven exploration of Flow-Lenia universes
🔍First discoveries in our ongoing Alife project
🔬We use curiosity-driven autotelic algorithms as AI scientists 🤖 exploring the space of Flow-Lenia environments
🚀We aim to find environments that self-organize, from scratch, sensorimotor agents, memory, learning, cognition, and even evolution itself 🔄🧬🌱
🚀ADTool: New open-source python library release from the team @FlowersINRIA 🌸
🤖It's all about using curiosity-driven exploration AI algorithms to help scientists explore complex systems, i.e. map the diversity of behaviours in e.g. GRNs or other biological networks 🌐, Lenia-like CAs, Kuramoto models, etc
🔧The library is made to enable non-specialists use easily this exploration algorithms, including visual interface 🎨, and simple tools to store, reuse or share discoveries in a system 📂🔁
💬And a discord to discuss and ask questions to the team ! Thread below 👇
