Papers
4
Total Citations
98
H-Index
4
About
Marco Frison is a researcher whose work lies at the intersection of swarm robotics and collective behavior, with a particular focus on how groups of simple agents can autonomously organize complex tasks. His major contributions center on task partitioning—the process by which a large job is broken into smaller subtasks distributed among robots—and the trade-offs between specialization and flexibility. In his most-cited paper, "Task partitioning in swarms of robots: an adaptive method for strategy selection" (2011, 62 citations), Frison introduced a decentralized mechanism that allows robots to dynamically choose between performing a task directly or passing it to a teammate, optimizing efficiency in changing environments. His follow-up work, "Costs and benefits of behavioral specialization" (2012, 17 citations), systematically quantified the advantages and drawbacks of role differentiation, showing that while specialization can boost speed, it may reduce resilience. Through these studies, Frison has advanced our understanding of self-organized systems, demonstrating how minimal local rules can lead to robust global strategies. His research is essential reading for students and engineers designing scalable, fault-tolerant multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Costs and benefits of behavioral specialization17 citations · 2012
- 3Self-organized Task Partitioning in a Swarm of Robots13 citations · 2010
- 4Costs and Benefits of Behavioral Specialization6 citations · 2011