Alessia Loi

Centre National de la Recherche Scientifique

Papers

Total Citations

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About

Alessia Loi is a rising researcher in the field of swarm robotics, with a focused interest in decentralized coordination, communication, and social learning among autonomous agents. Her most-cited work, “Signalling and social learning in swarms of robots” (2025, 3 citations), makes a significant early contribution by investigating how communication can enhance coordination within robot swarms. In this paper, Loi addresses the critical credit assignment problem—the challenge of determining which individual actions lead to successful outcomes in a collective setting—by proposing a paradigm where learning and execution occur simultaneously in a decentralized manner. This work highlights the role of signalling as a mechanism for improving swarm efficiency and adaptability, offering a novel perspective on how robots can learn from each other in real time. Although early in her career, Loi’s research has already garnered attention for its potential to advance autonomous systems, particularly in scenarios requiring robust, scalable coordination without central control. Her contributions are paving the way for more intelligent and communicative robot collectives, making her a promising voice in the intersection of robotics, machine learning, and collective behavior.