Carlo Longhi

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About

Carlo Longhi is a researcher in evolutionary robotics, focusing on how robots can autonomously evolve both their physical forms (morphologies) and control systems (brains). His work explores the intersection of evolution and lifetime learning, particularly in dynamic environments where robots must adapt after "birth." In his highly cited 2023 study, "A Comparative Study of Brain Reproduction Methods for Morphologically Evolving Robots," Longhi systematically compared how different brain inheritance mechanisms affect the performance of evolving robot populations, revealing critical insights into the balance between evolution and learning. His 2025 paper, "Lamarckian Inheritance Improves Robot Evolution in Dynamic Environments," demonstrated that allowing robots to pass on learned behaviors to their offspring—a concept inspired by Lamarckian evolution—significantly enhances adaptation in changing conditions. Though early in his career, Longhi’s work is already shaping the future of autonomous robot design, offering practical pathways for creating robots that can evolve and learn in real-world, unpredictable settings.