Lancelot Da Costa

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About

Lancelot Da Costa is a rising star at the intersection of theoretical neuroscience, artificial intelligence, and robotics. His primary research focus is **active inference**—a mathematical framework that describes how biological agents minimize surprise to maintain their existence. Da Costa’s major contribution lies in translating this neuroscientific principle into practical, computational models for artificial systems. His highly cited 2022 paper, “How Active Inference Could Help Revolutionise Robotics” (40 citations), lays out a compelling roadmap for embedding sentient-like behavior into robots, moving beyond traditional reward-maximization paradigms. In his more recent 2024 work, “Active Inference as a Model of Agency” (2 citations), he tackles a foundational question: can agency be understood as something more than chasing rewards? Here, he demonstrates that any physically plausible biological agent naturally integrates exploration and exploitation—a key insight for building truly adaptive machines. Though early in his career, Da Costa’s work is already shaping how researchers think about embodied intelligence, offering a principled alternative to reinforcement learning. His research promises to bridge the gap between theoretical neuroscience and real-world robotics, making him a name to watch in the field.