Some recent publications

[J68] F. Pagnozzi and M. Birattari (2021).   Off-policy evaluation of the performance of a robot swarm: Importance sampling to assess potential modifications to the finite-state machine that controls the robots.   Frontiers in Robotics and AI, 8:625125

[J67] M. Kegeleirs, G. Grisetti, and M. Birattari (2021).   Swarm SLAM: challenges and perspectives.   Frontiers in Robotics and AI, 8:618268

[W21] D. Garzón Ramos, D. Bozhinoski, G. Francesca, L. Garattoni, K. Hasselmann, M. Kegeleirs, J. Kuckling, A. Ligot, F. J. Mendiburu, F. Pagnozzi, M. Salman, T. Stützle, and M. Birattari (2021).   The automatic off-line design of robot swarms: recent advances and perspectives. [PDF]   In G. De Masi, E. Ferrante, and P. Dario (Eds.) R2T2: Robotics Research for Tomorrow’s Technology. Technology Innovation Institute, Abu Dhabi, United Arab Emirates.

[P89] J. Kuckling, V. van Pelt, and M. Birattari (2021).   Automatic modular design of behavior trees for robot swarms with communication capabilities.   In P.A. Castillo and J.L. Jiménez-Laredo (Eds.) Applications of Evolutionary Computation: 24rd European Conference, EvoApplications 2021. LNCS 12694, pp. 130-145. Springer International Publishing, Cham, Switzerland. (Conference held in Seville, Spain. April 7-9, 2021)

[J66] M. Salman, D. Garzón Ramos, K. Hasselmann, and M. Birattari (2020).   Phormica: Photochromic pheromone release and detection system for stigmergic coordination in robot swarms.   Frontiers in Robotics and AI, 7:591402

[J65] J. Kuckling, T. Stützle, and M. Birattari (2020).   Iterative improvement in the automatic modular design of robot swarms.   PeerJ Computer Science, 6:e322

[J64] A. Ligot, J. Kuckling, D. Bozhinoski, and M. Birattari (2020).   Automatic modular design of robot swarms using behavior trees as a control architecture.   PeerJ Computer Science, 6:e314

[J63] K. Hasselmann and M. Birattari (2020).   Modular automatic design of collective behaviors for robots endowed with local communication capabilities.   PeerJ Computer Science, 6:e291

[J62] M. Birattari, A. Ligot, and K. Hasselmann (2020).   Disentangling automatic and semi-automatic approaches to the optimization-based design of control software for robot swarms.[PDF]   Nature Machine Intelligence, 2(9):494–499

[P88] A. Ligot, K. Hasselmann and M. Birattari (2020).   AutoMoDe-Arlequin: neural networks as behavioral modules for the automatic design of probabilistic finite state machines.   In M. Dorigo et al. (Eds.) Swarm Intelligence, 12th International Conference, ANTS 2020. LNCS. Springer International Publishing, Cham, Switzerland. (Confefence held in Barcelona, Spain. October 26-28, 2020)

[J61] D. Garzón Ramos and M. Birattari (2020).   Automatic design of collective behaviors for robots that can display and perceive colors.   Applied Sciences, 10(13):4654

[J60] A. Ligot and M. Birattari (2020).   Simulation-only experiments to mimic the effects of the reality gap in the automatic design of robot swarms.   Swarm Intelligence, 14(1):1-24

[C16] G. Spaey, M. Kegeleirs, D. Garzón Ramos, and M. Birattari (2020). Evaluation of alternative exploration schemes in the automatic modular design of robot swarms.   In B. Bogaerts, G. Bontempi, P. Geurts, N. Harley, B. Lebichot, T. Lenaerts, and G. Louppe (Eds.) Artificial Intelligence and Machine Learning, pp. 18-33. Springer, Cham, Switzerland.

[C15] J. Kuckling, K. Ubeda Arriaza, and M. Birattari (2020). AutoMoDe-IcePop: Automatic modular design of control software for robot swarms using simulated annealing.   In B. Bogaerts, G. Bontempi, P. Geurts, N. Harley, B. Lebichot, T. Lenaerts, and G. Louppe (Eds.) Artificial Intelligence and Machine Learning, pp. 3-17. Springer, Cham, Switzerland.

[J59] A. Roli, A. Ligot and M. Birattari (2019).   Complexity measures: questions and novel opportunities in the automatic design and analysis of robot swarms.   Frontiers in Robotics and AI, 6:130

[J58] M. Salman, A. Ligot, and M. Birattari (2019).   Concurrent design of control software and configuration of hardware for robot swarms under economic constraints.   PeerJ Computer Science, 5:e221

[J57] M. Birattari, A. Ligot, D. Bozhinoski, M. Brambilla, G. Francesca, L. Garattoni, D. Garzón Ramos, K. Hasselmann, M. Kegeleirs, J. Kuckling, F. Pagnozzi, A. Roli, M. Salman, and T. Stützle (2019).   Automatic off-line design of robot swarms: a manifesto.   Frontiers in Robotics and AI, 6:59

[P87] J. Kuckling, K. Ubeda Arriaza, and M. Birattari (2019).   Simulated annealing as an optimization algorithm in the automatic modular design of control software for robot swarms. [PDF]   In K. Beuls et al. (Eds.) BNAIC/BENELEARN 2019: Proceedings of the 31st Benelux Conference on Artificial Intelligence and the 28th Belgian Dutch Conference on Machine Learning. CEUR Workshop Proceedings, vol. 2491, abstract58, 2 pages. Aachen, Germany. Best Paper Award (Conference held in Brussels, Belgium. November 6-8, 2019)

[P86] G. Spaey, M. Kegeleirs, D. Garzón Ramos, M. Birattari (2019).   Comparison of different exploration schemes in the automatic modular design of robot swarms. [PDF]   In K. Beuls et al. (Eds.) BNAIC/BENELEARN 2019: Proceedings of the 31st Benelux Conference on Artificial Intelligence and the 28th Belgian Dutch Conference on Machine Learning. CEUR Workshop Proceedings, vol. 2491, abstract55, 2 pages. Aachen, Germany. (Conference held in Brussels, Belgium. November 6-8, 2019)

[P85] M. Kegeleirs, D. Garzón Ramos, and M. Birattari (2019).   Random walk exploration for swarm mapping. [PDF]   In K. Althoefer et al. (Eds.) Towards Autonomous Robotic Systems, TAROS 2019. LNAI 11650, pp. 211–222. Springer International Publishing, Cham, Switzerland. (Confefence held in London, UK. July 3-5, 2019)

[P84] A. Ligot and M. Birattari (2018).   On mimicking the effects of the reality gap with simulation-only experiments. [PDF]   In M. Dorigo et al. (Eds.) Swarm Intelligence, 11th International Conference, ANTS 2018. LNCS 11172, pp. 109-122. Springer International Publishing, Cham, Switzerland. (Confefence held in Rome, Italy. October 29-31, 2018)

[P83] J. Kuckling, A. Ligot, D. Bozhinoski, and M. Birattari (2018).   Behavior trees as a control architecture in the automatic modular design of robot swarms. [PDF]   In M. Dorigo et al. (Eds.) Swarm Intelligence, 11th International Conference, ANTS 2018. LNCS 11172, pp. 30-43. Springer International Publishing, Cham, Switzerland. (Confefence held in Rome, Italy. October 29-31, 2018)

[P82] K. Hasselmann, F. Robert, M. Birattari (2018).   Automatic design of communication-based behaviors for robot swarms. [PDF]   In M. Dorigo et al. (Eds.) Swarm Intelligence, 11th International Conference, ANTS 2018. LNCS 11172, pp. 16-29. Springer International Publishing, Cham, Switzerland. (Confefence held in Rome, Italy. October 29-31, 2018)

[P81] D. Bozhinoski and M. Birattari (2018).   Designing control software for robot swarms: Software engineering for the development of automatic design methods. [PDF]   In F. Ciccozzi et al. (Eds.) ACM/IEEE 1st International Workshop on Robotics Software Engineering, RoSE, pp. 33-35. ACM, New York. (Confefence held in Gothenburg, Sweden. May 28, 2018)

[C14] A. Roli, A. Ligot, and M. Birattari (2018).   Complexity measures in automatic design of robot swarms: an exploratory study. [PDF]   In M. Perillo, I. Poli, A. Roli, R. Serra, D. Slanzi, and M. Villani (Eds.) Artificial Life and Evolutionary Computation, CCIS 860, pp. 243-246. Springer, Cham, Switzerland.

[J56] L. Garattoni and M. Birattari (2018).   Autonomous task sequencing in a robot swarm.   Science Robotics, 3(20):eaat0430 [summary|abstract|toc|full text]

Last update: May 10, 2021