Publications

2021

Bak-Coleman, J. B., Alfano, M., Barfuss, W., Bergstrom, C. T., Centeno, M. A., Couzin, I. D., Donges, J. F., Galesic, M., Gersick, A. S., Jacquet, J., Kao, A. B., Moran, R. E., Romanczuk, P., Rubenstein, D. I., Tombak, K. J., Bavel, J. J. V., & Weber, E. U. (2021). Stewardship of global collective behavior. Proceedings of the National Academy of Sciences, 118(27). https://doi.org/10.1073/pnas.2025764118
Bierbach, D., Wenchel, R., Gehrig, S., Wersing, S., O’Connor, O. L., & Krause, J. (2021). Male Sexual Preference for Female Swimming Activity in the Guppy (Poecilia reticulata). Biology, 10(2). https://doi.org/10.3390/biology10020147
Bierbach, D., Francisco, F., Lukas, J., Landgraf, T., Maxeiner, M., Romanczuk, P., Musiolek, L., Hafner, V. V., & Krause, J. (2021, July 19). Biomimetic robots promote the 3Rs Principle in animal testing. ALIFE 2021: The 2021 Conference on Artificial Life. https://doi.org/10.1162/isal_a_00375
Coelho Mollo, D. (2021). Why go for a computation-based approach to cognitive representation. Synthese. https://doi.org/10.1007/s11229-021-03097-5
Gu, C., Learned-Miller, E., Gallego, G., Sheldon, D., & Bideau, P. (2021). The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data. ArXiv:2106.06887 [Cs]. http://arxiv.org/abs/2106.06887
Kirtay, M., Oztop, E., Asada, M., & Hafner, V. V. (2021). Modeling robot trust based on emergent emotion in an interactive task. 2021 IEEE International Conference on Development and Learning (ICDL), 1–8. https://doi.org/10.1109/ICDL49984.2021.9515645
Kirtay, M., Oztop, E., Asada, M., & Hafner, V. V. (2021). Trust me! I am a robot: an affective computational account of scaffolding in robot-robot interaction. 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), 189–196. https://doi.org/10.1109/RO-MAN50785.2021.9515494
Kirtay, M., Chevalere, J., Lazarides, R., & Hafner, V. V. (2021). Learning in Social Interaction: Perspectives from Psychology and Robotics. 2021 IEEE International Conference on Development and Learning (ICDL), 1–8. https://doi.org/10.1109/ICDL49984.2021.9515648
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]. http://arxiv.org/abs/2106.00959
Kurvers, R. H. J. M., Herzog, S. M., Hertwig, R., Krause, J., & Wolf, M. (2021). Pooling decisions decreases variation in response bias and accuracy. IScience, 24(7), 102740. https://doi.org/10.1016/j.isci.2021.102740
Lazarides, R., & Chevalère, J. (2021). Artificial intelligence and education: Addressing the variability in learners’ emotion and motivation with adaptive teaching assistants. Bildung und Erziehung, 74(3), 264–279. https://doi.org/10.13109/buer.2021.74.3.264
Lazarides, R., & Raufelder, D. (2021). Control-value theory in the context of teaching: does teaching quality moderate relations between academic self-concept and achievement emotions? British Journal of Educational Psychology, 91(1), 127–147. https://doi.org/https://doi.org/10.1111/bjep.12352
Lukas, J., Kalinkat, G., Miesen, F. W., Landgraf, T., Krause, J., & Bierbach, D. (2021). Consistent Behavioral Syndrome Across Seasons in an Invasive Freshwater Fish. Frontiers in Ecology and Evolution, 8. https://doi.org/10.3389/fevo.2020.583670
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
Schweitzer, R., & Rolfs, M. (2021). Intrasaccadic motion streaks jump-start gaze correction. Science Advances, 7(30), eabf2218. https://doi.org/10.1126/sciadv.abf2218
Schweitzer, R., & Rolfs, M. (2021). Definition, modeling and detection of saccades in the face of post-saccadic oscillations [Preprint]. Neuroscience. https://doi.org/10.1101/2021.03.24.436800
Spatola, N., Chevalère, J., & Lazarides, R. (2021). Human vs computer: What effect does the source of information have on cognitive performance and achievement goal orientation? Paladyn, Journal of Behavioral Robotics, 12(1), 175–186. https://doi.org/10.1515/pjbr-2021-0012
Wudarczyk, O. A., Kirtay, M., Kuhlen, A. K., Abdel Rahman, R., Haynes, J.-D., Hafner, V. V., & Pischedda, D. (2021). Bringing Together Robotics, Neuroscience, and Psychology: Lessons Learned From an Interdisciplinary Project. Frontiers in Human Neuroscience, 15. https://doi.org/10.3389/fnhum.2021.630789
Wudarczyk, O. A., Kirtay, M., Pischedda, D., Hafner, V. V., Haynes, J.-D., Kuhlen, A. K., & Abdel Rahman, R. (2021). Robots facilitate human language production. Scientific Reports, 11(1), 16737. https://doi.org/10.1038/s41598-021-95645-9

2020

Andresen, N., Wöllhaf, M., Hohlbaum, K., Lewejohann, L., Hellwich, O., Thöne-Reineke, C., & Belik, V. (2020). Towards a fully automated surveillance of well-being status in laboratory mice using deep learning: Starting with facial expression analysis. PLOS ONE, 15(4), e0228059. https://doi.org/10.1371/journal.pone.0228059
Bastien, R., & Romanczuk, P. (2020). A model of collective behavior based purely on vision. Science Advances, 6(6), eaay0792. https://doi.org/10.1126/sciadv.aay0792
Bierbach, D., Krause, S., Romanczuk, P., Lukas, J., Arias-Rodriguez, L., & Krause, J. (2020). An interaction mechanism for the maintenance of fission–fusion dynamics under different individual densities. PeerJ, 8, e8974. https://doi.org/10.7717/peerj.8974
Bierbach, D., Mönck, H. J., Lukas, J., Habedank, M., Romanczuk, P., Landgraf, T., & Krause, J. (2020). Guppies Prefer to Follow Large (Robot) Leaders Irrespective of Own Size. Frontiers in Bioengineering and Biotechnology, 8. https://doi.org/10.3389/fbioe.2020.00441
Coelho Mollo, D. (2020). Against Computational Perspectivalism. The British Journal for the Philosophy of Science. https://doi.org/10.1093/bjps/axz036
Coelho Mollo, D. (2020, July 20). Deflationary Realism: Representation and Idealisation in Cognitive Science [Preprint, forthcoming in Mind & Language]. http://philsci-archive.pitt.edu/17591/
Jolles, J. W., Weimar, N., Landgraf, T., Romanczuk, P., Krause, J., & Bierbach, D. (2020). Group-level patterns emerge from individual speed as revealed by an extremely social robotic fish. Biology Letters, 16(9), 20200436. https://doi.org/10.1098/rsbl.2020.0436
Kirtay, M., Wudarczyk, O. A., Pischedda, D., Kuhlen, A. K., Abdel Rahman, R., Haynes, J.-D., & Hafner, V. V. (2020). Modeling robot co-representation: state-of-the-art, open issues, and predictive learning as a possible framework. 2020 Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 1–8. https://doi.org/10.1109/ICDL-EpiRob48136.2020.9278031
Landgraf, T., Moenck, H. J., Gebhardt, G. H. W., Weimar, N., Hocke, M., Maxeiner, M., Musiolek, L., Krause, J., & Bierbach, D. (2020). Socially competent robots: adaptation improves leadership performance in groups of live fish. ArXiv:2009.06633 [Cs]. http://arxiv.org/abs/2009.06633
Landgraf, T., Gebhardt, G. H. W., Bierbach, D., Romanczuk, P., Musiolek, L., Hafner, V. V., & Krause, J. (2020). Animal-in-the-Loop: Using Interactive Robotic Conspecifics to Study Social Behavior in Animal Groups. Annual Review of Control, Robotics, and Autonomous Systems. https://doi.org/10.1146/annurev-control-061920-103228
Lupyan, G., Abdel Rahman, R., Boroditsky, L., & Clark, A. (2020). Effects of Language on Visual Perception. Trends in Cognitive Sciences, 24(11), 930–944. https://doi.org/10.1016/j.tics.2020.08.005
Mellmann, H., Schlotter, B., Musiolek, L., & Hafner, V. V. (2020). Anticipation as a Mechanism for Complex Behavior in Artificial Agents. Artificial Life Conference Proceedings, 32, 157–159. https://doi.org/10.1162/isal_a_00314
Musiolek, L., Hafner, V. V., Krause, J., Landgraf, T., & Bierbach, D. (2020). Robofish as Social Partner for Live Guppies. In V. Vouloutsi, A. Mura, F. Tauber, T. Speck, T. J. Prescott, & P. F. M. J. Verschure (Eds.), Biomimetic and Biohybrid Systems (pp. 270–274). Springer. https://doi.org/10.1007/978-3-030-64313-3_26
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
Spatola, N., & Wudarczyk, O. A. (2020). Implicit Attitudes Towards Robots Predict Explicit Attitudes, Semantic Distance Between Robots and Humans, Anthropomorphism, and Prosocial Behavior: From Attitudes to Human–Robot Interaction. International Journal of Social Robotics. https://doi.org/10.1007/s12369-020-00701-5
Tump, A. N., Pleskac, T. J., & Kurvers, R. H. J. M. (2020). Wise or mad crowds? The cognitive mechanisms underlying information cascades. Science Advances, 6(29), eabb0266. https://doi.org/10.1126/sciadv.abb0266
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
Yun, H. S., Karl, M., & Fortenbacher, A. (2020). Designing an interactive second language learning scenario: a case study of Cozmo. Proceedings of HCI Korea, 384–387.
Zöller, G., Wall, V., & Brock, O. (2020). Active Acoustic Contact Sensing for Soft Pneumatic Actuators. 2020 IEEE International Conference on Robotics and Automation (ICRA), 7966–7972. https://doi.org/10.1109/ICRA40945.2020.9196916

2019

Galbusera, L., Finn, M. T. M., Tschacher, W., & Kyselo, M. (2019). Interpersonal synchrony feels good but impedes self-regulation of affect. Scientific Reports, 9(1), 14691. https://doi.org/10.1038/s41598-019-50960-0
Kurvers, R. H. J. M., Herzog, S. M., Hertwig, R., Krause, J., Moussaid, M., Argenziano, G., Zalaudek, I., Carney, P. A., & Wolf, M. (2019). How to detect high-performing individuals and groups: Decision similarity predicts accuracy. Science Advances, 5(11), eaaw9011. https://doi.org/10.1126/sciadv.aaw9011
Morik, M., Rastogi, D., Jonschkowski, R., & Brock, O. (2019). State Representation Learning with Robotic Priors for Partially Observable Environments. 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 6693–6699. https://doi.org/10.1109/IROS40897.2019.8967938
Sosna, M. M. G., Twomey, C. R., Bak-Coleman, J., Poel, W., Daniels, B. C., Romanczuk, P., & Couzin, I. D. (2019). Individual and collective encoding of risk in animal groups. Proceedings of the National Academy of Sciences, 116(41), 20556–20561. https://doi.org/10.1073/pnas.1905585116
Wall, V., & Brock, O. (2019). Multi-Task Sensorization of Soft Actuators Using Prior Knowledge. 2019 International Conference on Robotics and Automation (ICRA), 9416–9421. https://doi.org/10.1109/ICRA.2019.8793697

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