Research

Learning of intelligent swarm behavior

When is it ecologically beneficial to act as a collective, or to develop diversity within a swarm? When is it best to act alone?

Research Unit: 1

Project Number: 12

Example Behavior:
Collective Intelligence

Disciplines:
Behavioral Biology
Computational Neuroscience

 

Principal Investigators:
Pawel Romanczuk
Henning Sprekeler

Doctoral Researchers:
Robert Tjarko Lange

Postdoctoral Researchers:
Luis Alberto Gómez Nava

 

Expected Project Duration
2019 - 2023

← Projects Overview

Learning of intelligent swarm behavior

When is it ecologically beneficial to act as a collective, or to develop diversity within a swarm? When is it best to act alone?

©SCIoI

The proposed project will focus on the following four main objectives: In a first step, we will focus on developing analytical methods to identify heuristics of anticipation in live fish that interact with a biomimetic robotic fish (Robofish) and vary also in social responsiveness (objective a). In a second step, we will create situations in which live fish have to cooperate or compete with Robofish in order to achieve a goal effectively. This will allow us to estimate costs and benefits associated with anticipatory strategies (objective b). The aim of our experimental data is to identify cognitive heuristics that play a role in anticipation in interacting pairs that will then be used to develop a ubiquitous synthetic behavior of anticipation when social responsiveness in interaction partners varies (objective c). In order to evaluate this synthetic behavior, it will be implemented into Robofish as well as in humanoid robots and then tested in situations involving either robot-only pairs (robot-robot) or, in case of Robofish, also pairs with one live agent (fish-robot) (objective d).

Zhao, Y., Huepe, C., & Romanczuk, P. (2022). Contagion dynamics in self-organized systems of self-propelled particles. Scientific Reports. https://doi.org/10.1038/s41598-022-06083-0
Winklmayr, C., Kao, A. B., Bak-Coleman, J. B., & Romanczuk, P. (2020). The wisdom of stalemates: consensus and clustering as filtering mechanisms for improving collective accuracy. Proceedings of the Royal Society B: Biological Sciences, 287(1938), 20201802. https://doi.org/10.1098/rspb.2020.1802
Winklmayr, C., Kao, A. B., Bak-Coleman, J. B., & Romanczuk, P. (2023). Collective decision strategies in the presence of spatio-temporal correlations. Collective Intelligence. https://doi.org/10.1177/26339137221148675
Vischer, M., Lange, R., & Sprekeler, H. (2022). On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning. ICLR 2022. https://doi.org/10.48550/arXiv.2105.01648
Sarkanych, P., Krasnytska, M., Gomez-Nava, L., Romanczuk, P., & Holovatch, Y. (2023). Individual bias and fluctuations in collective decision making: from algorithms to Hamiltonians. Physical Biology. https://doi.org/10.1088/1478-3975/acd6ce
Rahmani, P., Peruani, F., & Romanczuk, P. (2020). Flocking in complex environments—Attention trade-offs in collective information processing. PLOS Computational Biology, 16(4), e1007697. https://doi.org/10.1371/journal.pcbi.1007697
Poel, W., Daniels, B. C., Sosna, M. M. G., Twomey, C. R., Blanc, S. L., Couzin, I., & Romanczuk, P. (2022). Subcritical escape waves in schooling fish. Science Advances. https://doi.org/10.1126/sciadv.abm6385
Poel, W., Winklmayr, C., & Romanczuk, P. (2021). Spatial Structure and Information Transfer in Visual Networks. Frontiers in Physics. https://doi.org/10.3389/fphy.2021.716576
Lukas, J., Auer, F., Goldhammer, T., Krause, J., Romanczuk, P., Klamser, P., Arias-Rodriguez, L., & Bierbach, D. (2021). Diurnal Changes in Hypoxia Shape Predator-Prey Interaction in a Bird-Fish System. Frontiers in Ecology and Evolution, 9. https://doi.org/10.3389/fevo.2021.619193
Lukas, J., Romanczuk, P., Klenz, H., Klamser, P., Arias Rodriguez, L., Krause, J., & Bierbach, D. (2021). Acoustic and visual stimuli combined promote stronger responses to aerial predation in fish. Behavioral Ecology, arab043. https://doi.org/10.1093/beheco/arab043
Lange, R., & Sprekeler, H. (2022). Learning not to learn: Nature versus Nurture in Silico. AAAI 2022. https://doi.org/10.48550/arXiv.2010.04466
Klamser, P. P., Gómez-Nava, L., Landgraf, T., Jolles, J. W., Bierbach, D., & Romanczuk, P. (2021). Impact of Variable Speed on Collective Movement of Animal Groups. arXiv:2106.00959 [physics, q-bio]. https://doi.org/10.3389/fphy.2021.715996
Klamser, P., & Romanczuk, P. (2021). Collective predator evasion: Putting the criticality hypothesis to the test. PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1008832
Gómez-Nava, L., Bon, R., & Peruani, F. (2022). Intermittent collective motion in sheep results from alternating the role of leader and follower. Nature Physics, 8. https://doi.org/10.1038/s41567-022-01769-8
Gómez-Nava, L., Lange, R. T., Klamser, P. P., Lukas, J., Arias-Rodriguez, L., Bierbach, D., Krause, J., Sprekeler, H., & Romanczuk, P. (2023). Fish shoals resemble a stochastic excitable system driven by environmental perturbations. Nature Physics. https://doi.org/10.1038/s41567-022-01916-1
Doran, C., Bierbach, D., Lukas, J., Klamser, P., Landgraf, T., Klenz, H., Habedank, M., Arias-Rodriguez, L., Krause, S., Romanczuk, P., & Krause, J. (2022). Fish waves as emergent collective antipredator behavior. Current Biology. https://doi.org/10.1016/j.cub.2021.11.068
Davidescu, M. R., Romanczuk, P., Gregor, T., & Couzin, I. D. (2023). Growth produces coordination trade-offs in Trichoplax adhaerens, an animal lacking a central nervous system. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2206163120
Daniels, B. C., & Romanczuk, P. (2021). Quantifying the impact of network structure on speed and accuracy in collective decision-making. Theory in Biosciences. https://doi.org/10.1007/s12064-020-00335-1

Research

An overview of our scientific work

See our Research Projects