Scientific career
- 2004: BSc, Computer Science Engeneering, Politecnico di Milano, IT
- 2007: MSc, Computer Science, University of Illinois at Chicago, USA
- 2007: MSc, Computer Science Engeneering, Politecnico di Milano, IT
- 2013: PhD, Applied Sciences, Université Libre de Bruxelles, BE
- 2012-2014: Postdoctoral researcher, University of Leuven, BE
- 2014-: FWO Postdoctoral fellow, University of Leuven, BE
Research interests
My research focuses on the interplay between self-organization and evolution. The main big question I focus on is what evolutionary factors favour the evolution of particular forms of organizational pattern instead of others and, once these patterns evolve, I study what are the key mechanisms that lead to such collective-level organization.
I have an engineering background and, as such, I am interested in solving real-world societal problems. Beside their scientific relevance, I believe that answering the above fundamental question can have a big impact on the engineering community. On the one hand, discovering the fundamental laws of self-organization can either lead a) to new self-organizing artefacts, such as large robot swarms, that solve yet to encounter problems such as space exploration and b) to a better understanding of natural self-organizing system that lead to better infrastructural rules guiding the collective towards desirable social and economic benefits. On the other hand, studying the evolution of complex systems can be useful in order to have an “artificial spontaneous process” that leads automatically to the formation of useful artefacts.
My research is at the interface between different disciplines: computer science, statistical physics, robotics and biology. Computer science, as I mainly work with computer simulations. Statistical physics, as I strive to identify simple key mechanisms that lead to collective level phenomena, and as I use standard tools such as phase-transition analysis and analytical models to understand them. Robotics, as I mainly use robotics systems as a benchmark. Biology, as I look at the evolutionary factors that lead to the evolution of particular forms of self-organization.
Publications
Judhi Prasetyo, Giulia De Masi, Pallavi Ranjan, and Eliseo Ferrante. The best-of-n problem with dynamic site qualities: Achieving adaptability with stubborn individuals. In Marco Dorigo et al., editors, LNCS 11172. Swarm Intelligence. 11th International Conference, ANTS 2018. Springer, Berlin, Germany, 2018. [ bib | www: ]
Giuseppe Primiero, Elio Tuci, Jacopo Tagliabue, and Eliseo Ferrante. Swarm attack: A self-organized model to recover from malicious communication manipulation in a swarm of simple simulated agents. In Marco Dorigo et al., editors, LNCS 11172. Swarm Intelligence. 11th International Conference, ANTS 2018. Springer, Berlin, Germany, 2018. [ bib | www: ]
Nicolas Cambier, Vincent Fremont, Vito Trianni, and Eliseo Ferrante. Embodied evolution of self-organised aggregation by cultural propagation. In Marco Dorigo et al., editors, LNCS 11172. Swarm Intelligence. 11th International Conference, ANTS 2018. Springer, Berlin, Germany, 2018. [ bib | www: ]
Khaluf Y., Ferrante E. Pieter S., and Huepe C. Scale invariance in natural and artificial collective systems: a review.Journal of the Royal Society Interface, 14(136), 2017. Impact Factor: 3.82. [ bib | .pdf ]
Gabriele Valentini, Eliseo Ferrante, and Marco Dorigo. The best-of-n problem in robot swarms: Formalization, state of the art, and novel perspectives. Frontiers in Robotics and AI, 4:9, 2017. [ bib | .pdf ]
Heiko Hamann, Yara Khaluf, Jean Botev, Mohammad Divband Soorati, Eliseo Ferrante, Oliver Kosak, Jean-Marc Montanier, Sanaz Mostaghim, Richard Redpath, Jonathan Timmis, Frank Veenstra, Mostafa Wahby, and Aleš Zamuda. Hybrid societies: Challenges and perspectives in the design of collective behavior in self-organizing systems. Frontiers in Robotics and AI, 3(14), 2016. [ bib | .pdf ]
Rinde van Lon, Eliseo Ferrante, Ali Emre Turgut, Tom Wenseleers, Greet Vanden Berghe, and Tom Holvoet. Measures of dynamism and urgency in logistics. European Journal of Operational Research, 253(3):614–624, 2016.Impact Factor: 2.36. [ bib | .pdf ]
Gabriele Valentini, Eliseo Ferrante, Heiko Hamann, and Marco Dorigo. Collective decision with 100 kilobots: speed versus accuracy in binary discrimination problems. Autonomous Agents and Multi-Agent Systems, 30(3):553–580, 2016. Impact Factor: 1.25. [ bib | .pdf ]
A. Scheidler, A. Brutschy, E. Ferrante, and M. Dorigo. The k-unanimity rule for self-organized decision making in swarms of robots. IEEE Transactions on Cybernetics, PP(99):1175–1188, 2016. Impact Factor: 3.78. [ bib | .pdf ]
S. Van Essche, E. Ferrante, A. E. Turgut, R. Van Lon, T. Holvoet, and T. Wenseleers. Environmental factors promoting the evolution of recruitment strategies in swarms of foraging robots. In Proceedings of the First International Symposium on Swarm Behavior and Bio-Inspired Robotics, page to appear. MIT Press, Cambridge, MA, 2015. [ bib | .pdf ]
E. Ferrante, A.E. Turgut, E. Duéñez-Guzmán, M. Dorigo, and T. Wenseleers. Evolution of self-organized task specialization in robot swarms. PLOS Computational Biology, 11(8):e1004273, 2015. Impact Factor: 4.87. [ bib | .pdf ]
C. Huepe, E. Ferrante, T. Wenseleers, and A. E. Turgut. Scale-free correlations in flocking systems with position-based interactions. Journal of Statistical Physics, 158(3):549–562, 2014. Impact Factor: 1.28. [ bib | .pdf ]
Manuele Brambilla, Eliseo Ferrante, Adamo Prina, Mauro Birattari, and Marco Dorigo. Robotica di sciame: una rassegna bibliografica. Sistemi intelligenti, (3/2014):465–494, 2014. [ bib |http ]
E. Ferrante, A. E. Turgut, T. Wenseleers, and C. Huepe. Scale-free correlations in collective motion with position-based interactions. In Hod Lipson and Hiroki Sayama, editors, Artificial Life 14, volume 14, pages 300–301. MIT Press, Cambridge, MA, 2014. [ bib | .pdf ]
E. Ferrante, A. E. Turgut, A. Stranieri, C. Pinciroli, M. Birattari, and M. Dorigo. A self-adaptive communication strategy for flocking in stationary and non-stationary environments. Natural Computing, 13(2):225–245, 2014.Impact Factor: 0.54. [ bib | .pdf ]
E. Ferrante, E. Duéñez Guzmán, A. E. Turgut, and T. Wenseleers. Evolution of task partitioning in swarm robotics. In V. Trianni et al., editor, Proceedings of the Workshop on Collective Behaviors and Social Dynamics of the European Conference on Artificial Life (ECAL 2013), 2013. [ bib | .pdf ]
E. Ferrante, A. E. Turgut, M. Dorigo, and C. Huepe. Elasticity-based mechanism for the collective motion of self-propelled particles with spring-like interactions: A model system for natural and artificial swarms. Physical Review Letters, 111(268302):1–5, 2013. Impact Factor: 7.73. [ bib | .pdf ]
E. Ferrante. Information transfer in a flocking robot swarm, 2013. Ph.D thesis – Université Libre de Bruxelles. [ bib | .pdf ]
M. Dorigo, D. Floreano, L. M. Gambardella, F. Mondada, S. Nolfi, T. Baaboura, M. Birattari, M. Bonani, M. Brambilla, A. Brutschy, D. Burnier, A. Campo, A. L. Christensen, A. Decugnière, G. Di Caro, F. Ducatelle, E. Ferrante, A. Förster, J. Guzzi, V. Longchamp, S. Magnenat, J. Martinez Gonzales, N. Mathews, M. Montes de Oca, R. O’Grady, C. Pinciroli, G. Pini, P. Rétornaz, J. Roberts, V. Sperati, T. Stirling, A. Stranieri, T. Stützle, V. Trianni, E. Tuci, A. E. Turgut, and F. Vaussard. Swarmanoid: A novel concept for the study of heterogeneous robotic swarms. IEEE Robotics & Automation Magazine, 20(4):60–71, 2013. Impact Factor: 2.32. [ bib | .pdf ]
E. Ferrante, A. E. Turgut, M. Dorigo, and C. Huepe. Collective motion dynamics of active solids and active crystals. New Journal of Physics, 15(095011):1–20, 2013. Impact Factor: 3.67. [ bib | .pdf ]
E. Ferrante, E. Duéñez Guzmán, A. E. Turgut, and T. Wenseleers. Geswarm: Grammatical evolution for the automatic synthesis of collective behaviors in swarm robotics. In Proceedings of the fifteenth international conference on Genetic and evolutionary computation conference companion, pages 17–24. ACM, New York, NY, 2013. [ bib | .pdf ]
M. Brambilla, E. Ferrante, M. Birattari, and M. Dorigo. Swarm robotics: A review from the swarm engineering perspective. Swarm Intelligence, 7:1–41, 2013. Impact Factor: 1.83. [ bib | .pdf ]
E. Ferrante, S. Wenjie, A. E. Turgut, M. Birattari, M. Dorigo., and T. Wenseleers. Self-organized flocking with conflicting goal directions. In V. Blondel, T. Carletti, E. Carlon, A. D. Wit, P. Gaspard, A. Goldbeter, R. Lambiotte, and C. Vanderzande, editors, Proceedings of the 12th European Conference on Complex Systems (ECCS 2012), pages 607–613, Berlin, Germany, 2012. Springer. [ bib | .pdf ]
E. Ferrante, M. Brambilla, M. Birattari, and M. Dorigo. Socially-mediated negotiation for obstacle avoidance in collective transport. In A. Martinoli, F. Mondada, N. Correll, G. Mermoud, M. Egerstedt, M. A. Hsieh, L. E. Parker, and K. Stöy, editors, International Symposium on Distributed Autonomous Robotics Systems (DARS-2010), volume 83 of Springer Tracts in Advanced Robotics, pages 571–583. Springer, Berlin, Germany, 2013. [ bib | .pdf ]
E. Ferrante, A. E. Turgut, C. Huepe, M. Birattari, M. Dorigo., and T. Wenseleers. Explicit and implicit directional information transfer in collective motion. In C. Adami, D. M. Bryson, C. Ofria, and R. T. Pennock, editors, Artificial Life 13, volume 13, pages 551–552. MIT Press, Cambridge, MA, 2012. [ bib | .pdf ]
E. Ferrante, A. E. Turgut, C. Huepe, A. Stranieri, C. Pinciroli, and M. Dorigo. Self-organized flocking with a mobile robot swarm: a novel motion control method. Adaptive Behavior, 20(6):460–477, 2012. Impact Factor: 1.15. [ bib | .pdf ]
C. Pinciroli, V. Trianni, R. O’Grady, G.i Pini, A. Brutschy, M. Brambilla, N. Mathews, E. Ferrante, G. Di Caro, F. Ducatelle, M. Birattari, L. M. Gambardella, and M. Dorigo. ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems. Swarm Intelligence, 6(4):271–295, 2012. Impact Factor: 1.83. [ bib | .pdf ]
A. Brutschy, A. Scheidler, E. Ferrante, M. Dorigo, and M. Birattari. “Can ants inspire robots?” Self-organized decision making in robotic swarms. In Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, pages 4272–4273, Los Alamitos, CA, 2012. IEEE Computer Society Press. [ bib | .pdf ]
M. A. Montes de Oca, E. Ferrante, A. Scheidler, and L. F. Rossi. Binary consensus via exponential smoothing. In R. Colbaugh et al., editors, Proceedings of the Second International Conference on Complex Sciences: Theory and Applications (COMPLEX 2012), volume 126, pages 244–255. Springer, Berlin, Germany, 2012. [ bib | .pdf ]
M. Dorigo, M. Birattari, R. O’Grady, L.M. Gambardella, F. Mondada, D. Floreano, S. Nolfi, T. Baaboura, M. Bonani, M. Brambilla, A. Brutschy, D. Burnier, A. Campo, A.L. Christensen, A. Decugnière, G. Di Caro, F. Ducatelle, E. Ferrante, J. Martinez Gonzales, J. Guzzi V., Longchamp, S. Magnenat, N. Mathews, M. Montes de Oca, C. Pinciroli, G. Pini, P. Rétornaz, F. Rey, J. Roberts, F. Rochat, V. Sperati, T. Stirling, A. Stranieri, T. Stützle, V. Trianni, E. Tuci, A.E. Turgut, and F. Vaussard. Swarmanoid, the movie. In AAAI-11 Video Proceedings. AAAI Press, San Francisco, CA, 2011. Winner of the “AAAI-2011 Best AI Video Award”. [ bib | http ]
M. A. Montes de Oca, E. Ferrante, A. Scheidler, C. Pinciroli, M. Birattari, and M. Dorigo. Majority-rule opinion dynamics with differential latency: A mechanism for self-organized collective decision-making. Swarm Intelligence, 5(3–4):305–327, 2011. Impact Factor: 1.83. [ bib | .pdf ]
C. Pinciroli, V. Trianni, R. O’Grady, G. Pini, A. Brutschy, M. Brambilla, N. Mathews, E. Ferrante, G. A. Di Caro, F. Ducatelle, T. Stirling, A. Gutiérrez, L. M. Gambardella, and M. Dorigo. ARGoS: A modular, multi-engine simulator for heterogeneous swarm robotics. In Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’11), pages 5027–5034. IEEE Computer Society Press, Los Alamitos, CA, 2011. [ bib |.pdf ]
A. Stranieri, E. Ferrante, A. E. Turgut, V. Trianni, C. Pinciroli, M. Birattari, and M. Dorigo M. Self-Organized flocking with a heterogeneous mobile robot swarm. In T. Lenaerts, M. Giacobini, H. Bersini, P. Borgine, M. Dorigo, and R. Doursat, editors, Proceedings of ECAL 2011, pages 789–796, Cambridge, MA, 2011. MIT Press. [ bib | .pdf ]
M. A. Montes de Oca, E. Ferrante, N. Mathews, M. Birattari, and M. Dorigo. Opinion dynamics for decentralized decision-making in a robot swarm. In Marco Dorigo et al., editors, LNCS 6234. Swarm Intelligence. 7th International Conference, ANTS 2010, pages 251–262. Springer, Berlin, Germany, 2010. [ bib | .pdf ]
E. Ferrante, A. E. Turgut, N. Mathews, M. Birattari, and M. Dorigo. Flocking in stationary and non-stationary environments: A novel communication strategy for heading alignment. In R. Schaefer, C. Cotta, J. Kolodziej, and G. Rudolph, editors, Parallel Problem Solving from Nature — PPSN XI, volume 6239 of Lecture Notes in Computer Science, pages 331–340. Springer, Berlin, Germany, 2010. [ bib | .pdf ]
N. Mathews, A. L. Christensen, E. Ferrante, R. O’ Grady, and M. Dorigo. Establishing spatially targeted communication in a heterogeneous robot swarm. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 – Volume 1, AAMAS ’10, pages 939–946. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 2010. [ bib | .pdf ]
E. Ferrante, M. Brambilla, M. Birattari, and M. Dorigo. “Look out!”: Socially-Mediated Obstacle Avoidance in Collective Transport. In Swarm Intelligence: 7th International Conference, ANTS 2010, volume 6234 of Lecture Notes in Computer Science, pages 572–573. Springer, Berlin, Germany, 2010. [ bib | .pdf ]
M. A. Montes de Oca, E. Ferrante, N. Mathews, M. Birattari, and M. Dorigo. Optimal collective decision-making through social influence and different action execution times. In D. Curran and C. O’Riordan, editors, Proceedings of the Workshop on Organisation, Cooperation and Emergence in Social Learning Agents of the European Conference on Artificial Life (ECAL 2009), 2009. [ bib | .pdf ]
E. Ferrante, A. Lazaric, and M. Restelli. Transfer of task representation in reinforcement learning using policy-based proto-value functions. In Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems – Volume 3, AAMAS ’08, pages 1329–1332. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 2008. [ bib | .pdf ]
E. Ferrante. A control architecture for a heterogeneous swarm of robots: The design of a modular behavior-based architecture, 2009. MAS report – Université Libre de Bruxelles. [ bib | .pdf ]
E. Ferrante. Transfer of knowledge in reinforcement learning through policy-based proto-value functions, 2007. Master thesis – Politecnico di Milano. [ bib | .pdf ]
E. Ferrante, A. E. Turgut, N. Mathews, M. Birattari, and M. Dorigo. The role of explicit alignment in self-organized flocking. Technical report, Université Libre de Bruxelles, 2010. TR/IRIDIA/2010-014. [ bib | .pdf ]
Press and Media Coverage
Robots, evolución artificial y capacidad de autoorganización (in Spanish), Noticias de la Ciencia y la Tecnologia. 20 October 2015 [.pdf ].
Décidément, les fourmis savent travailler efficacement (in French), Sciences et Avenir. 19 August 2015 [.pdf ].
Robots Discover How Cooperative Behavior Evolved in Insects, IEEE Spectrum. 19 August 2015 [.pdf ].
Colonizzare pianeti con i robot (in Italian), Santeramo Live. 13 August 2015 [.pdf ].
Естественный отбор помогает групповой работе роботов (in Russian), KO. 11 August 2015 [.pdf ].
Antlike robots might help explain origins of cooperation, Science Magazine. 11 August 2015 [.pdf ].
Simple Robots Evolve to Become Cooperative, Real Clear Science. 11 August 2015 [.pdf ].
Bilim insanları robotların kendi kendine organize olmasını sağladı (in Turkish), Sol Haber. 8 August 2015 [.pdf ].
Scientists develop robots who can self-organize tasks, The News Reports. 8 August 2015 [.pdf ].
Des robots se partagent les tâches (in French), Science actualités. 7 August 2015 [.pdf ].
Darwinian thinking lets robot evolve – study, 3 News (New Zealand). 7 August 2015 [.pdf ].
Sciami di robot per colonizzare pianeti (in Italian), ANSA (Italian News Agency). 7 August 2015 [.pdf ].
Robots that divide tasks among themselves, Business Standard. 7 August 2015 [.pdf ].
Scientists produce robots that can artificially evolve and adapt to unfamiliar terrain with Darwinian thinking, City A.M.. 7 August 2015 [.pdf ].
Scientists develop robots who can divide tasks among themselves, DNA India. 7 August 2015 [.pdf ].
Robot intelligenti e autonomi per colonizzare i pianeti (in Italian), Eco Age. 7 August 2015 [.pdf ].
Artificially evolved robots that efficiently self-organize tasks, (e) Science News. 7 August 2015 [.pdf ].
I robot potranno “colonizzare” altri pianeti, Giornale della Sicilia. 7 August 2015 [.pdf ].
Artificially evolved robots that efficiently self-organize tasks, Health Medicine Network. 7 August 2015 [.pdf ].
Artificially evolved robots that efficiently self-organize tasks, Phys.Org. 7 August 2015 [.pdf ].
Pianeti, li colonizzeremo con sciami di robot (in Italian), La Repubblica. 7 August 2015 [.pdf ].
Robot Swarms Can Evolve to Self-Organize Their Tasks, Science World Report. 7 August 2015 [.pdf ].
Artificially Evolved Robots Efficiently Self-organize Complex Tasks, Scientific Computing. 7 August 2015 [.pdf ].
Artificial evolution is teaching robots to self-organise, Tech Radar. 7 August 2015 [.pdf ].
Robots that divide tasks among themselves, The Financial Express. 7 August 2015 [.pdf ].
Robots that divide tasks among themselves, Zee News India. 7 August 2015 [.pdf ].
Artificially evolved robots that efficiently self-organize tasks, Science Daily. 6 August 2015 [.pdf ].
Artificially evolved robots that efficiently self-organize tasks, Eureka Alert. 6 August 2015 [.pdf ].