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About

Olivier L. Georgeon is a pioneering researcher at the intersection of developmental artificial intelligence, enactive cognition, and constructivist robotics. His work fundamentally challenges conventional AI paradigms by designing autonomous agents that learn through interaction rather than pre-programmed knowledge. Georgeon's most influential contribution is his "Enactive approach to autonomous agent and robot learning" (2013, 7 citations), which introduced a framework where agents construct their own understanding of the world through sensorimotor engagement. His 2014 paper on "Autonomous object modeling based on affordances" (5 citations) further advanced this vision, demonstrating how self-motivated agents can organize behavior by discovering interaction possibilities with unknown objects. Georgeon also created "Little AI: Playing a constructivist robot" (2017, 4 citations), an award-winning pedagogical game that makes developmental AI concepts accessible to students and the public. His recent "Artificial enactive inference in three-dimensional world" (2024, 6 citations) extends his framework into complex 3D environments. Through his "Artificial Interactionism" paradigm (2022, 2 citations), Georgeon critiques the isolation of perception from cognition in AI, advocating for embodied, interactive learning systems that build knowledge from experience—a vision that continues to shape the future of autonomous robotics and cognitive science.