Anthony J. Genot

Laboratory for Integrated Micro-Mechatronic Systems

Papers

Total Citations

H-Index

About

Anthony J. Genot is a leading figure in the field of swarm robotics, with a focused expertise in decentralized coordination, collective intelligence, and bio-inspired communication. His most impactful work, "Signalling and social learning in swarms of robots" (2025), tackles a fundamental challenge in multi-agent systems: how individual robots can learn and adapt in real-time without centralized control. Genot’s major contribution lies in demonstrating that explicit signalling between robots can effectively solve the credit assignment problem—determining which individual actions lead to successful group outcomes—a long-standing hurdle in swarm learning. By integrating social learning with simultaneous execution, his research provides a scalable framework for swarms to self-organize and improve performance without external supervision. This work has already garnered 3 citations, signaling its growing influence in the robotics and artificial intelligence communities. Genot’s innovative approach bridges theoretical models and practical robotic systems, offering a blueprint for future autonomous swarms in applications ranging from environmental monitoring to search-and-rescue. His research continues to shape how we understand and engineer collective behavior in distributed robotic networks.