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Publications

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2024

  1. Solopova, V., Herman, V., Benzmüller, C., & Landgraf, T. (2024). Check News in One Click: NLP-Empowered Pro-Kremlin Propaganda Detection. In N. Aletras & O. De Clercq (Eds.), Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations (pp. 44–51). Association for Computational Linguistics. https://aclanthology.org/2024.eacl-demo.6 Link>
  2. Granz, M., Heurich, M., & Landgraf, T. (2024). WeiPer: OOD Detection using Weight Perturbations of Class Projections. arXiv. https://doi.org/10.48550/arXiv.2405.17164 Link>
  3. Mellert, J., Kłos, W., Dormagen, D. M., Wild, B., Zachariae, A., Smith, M. L., Galizia, C. G., & Landgraf, T. (2024). Collective flow of circadian clock information in honeybee colonies. bioRxiv. https://doi.org/10.1101/2024.07.29.605620 Link>
  4. Solopova, V., Romeike, R., Gläser-Zikuda, M., Benzmüller, C., Landgraf, T., Hofmann, F., Schießl, J., Zhang, C., Plößl, L., & Witte, S. (2024). AI-powered automatic feedback on reflective writing. Annual Conference of the European Teacher Education Network (ETEN)“Teacher Education–Connecting Glocal.” http://fis.uni-bamberg.de/bitstreams/c052c8b0-c990-4780-99f0-8b387c693fc5/download Link>

2023

  1. Neubauer, L. C., Davidson, J. D., Wild, B., Dormagen, D. M., Landgraf, T., Couzin, I. D., & Smith, M. L. (2023). Honey bee drones are synchronously hyperactive inside the nest. bioRxiv. https://doi.org/10.1101/2023.01.19.524638 Link>
  2. Landgraf, T., Bierbach, D., Moenck, H. J., Musiolek, L., Hocke, M., & Maxeiner, M. (2023). Data for the publication "Socially competent robots". https://doi.org/10.17169/refubium-36430 Link>
  3. Solopova, V., Popescu, O.-I., Benzmüller, C., & Landgraf, T. (2023). Automated multilingual detection of Pro-Kremlin propaganda in newspapers and Telegram posts. arXiv. https://doi.org/10.48550/arXiv.2301.10604 Link>
  4. Solopova, V., Benzmüller, C., & Landgraf, T. (2023). The Evolution of Pro-Kremlin Propaganda From a Machine Learning and Linguistics Perspective. Proceedings of the Second Ukrainian Natural Language Processing Workshop (UNLP), 40–48. https://aclanthology.org/2023.unlp-1.5 Link>
  5. Maxeiner, M., Hocke, M., Moenck, H. J., Gebhardt, G. H. W., Weimar, N., Musiolek, L., Krause, J., Bierbach, D., & Landgraf, T. (2023). Social competence improves the performance of biomimetic robots leading live fish. Bioinspiration & Biomimetics, 18(4), 045001. https://doi.org/10.1088/1748-3190/acca59 Link>
  6. Van Havermaet, S., Simoens, P., Landgraf, T., & Khaluf, Y. (2023). Steering herds away from dangers in dynamic environments. Royal Society Open Science, 10(5), 230015. https://doi.org/10.1098/rsos.230015 Link>
  7. Solopova, V., Rostom, E., Cremer, F., Gruszczynski, A., Witte, S., Zhang, C., López, F. R., Plößl, L., Hofmann, F., Romeike, R., Gläser-Zikuda, M., Benzmüller, C., & Landgraf, T. (2023). PapagAI: Automated Feedback for Reflective Essays. In D. Seipel & A. Steen (Eds.), KI 2023: Advances in Artificial Intelligence (pp. 198–206). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-42608-7_16
  8. Neubauer, L. C., Davidson, J. D., Wild, B., Dormagen, D. M., Landgraf, T., Couzin, I. D., & Smith, M. L. (2023). Honey bee drones are synchronously hyperactive inside the nest. Animal Behaviour, 203, 207–223. https://doi.org/10.1016/j.anbehav.2023.05.018 Link>
  9. Dormagen, D. M., Wild, B., Wario, F., & Landgraf, T. (2023). Machine learning reveals the waggle drift’s role in the honey bee dance communication system. PNAS Nexus, 2(9), pgad275. https://doi.org/10.1093/pnasnexus/pgad275 Link>
  10. Jhawar, J., Davidson, J. D., Weidenmüller, A., Wild, B., Dormagen, D. M., Landgraf, T., Couzin, I. D., & Smith, M. L. (2023). How honeybees respond to heat stress from the individual to colony level. Journal of The Royal Society Interface, 20(207), 20230290. https://doi.org/10.1098/rsif.2023.0290 Link>

2022

  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, 32(3), 708–714.e4. https://doi.org/10.1016/j.cub.2021.11.068 Link>
  2. Smith, M. L., Davidson, J. D., Wild, B., Dormagen, D. M., Landgraf, T., & Couzin, I. D. (2022). Behavioral variation across the days and lives of honey bees. IScience, 25(9), 104842. https://doi.org/10.1016/j.isci.2022.104842 Link>
  3. Bierbach, D., Gómez-Nava, L., Francisco, F. A., Lukas, J., Musiolek, L., Hafner, V. V., Landgraf, T., Romanczuk, P., & Krause, J. (2022). Live fish learn to anticipate the movement of a fish-like robot. Bioinspiration & Biomimetics, 17(6), 065007. https://doi.org/10.1088/1748-3190/ac8e3e Link>
  4. Nader, Y., Sixt, L., & Landgraf, T. (2022). DNNR: Differential Nearest Neighbors Regression. Proceedings of the 39th International Conference on Machine Learning, 16296–16317. https://proceedings.mlr.press/v162/nader22a.html Link>
  5. Sixt, L., Schuessler, M., Popescu, O.-I., Weiß, P., & Landgraf, T. (2022, March). Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset. Proceedings of the International Conference on Learning Representations. https://openreview.net/forum?id=v6s3HVjPerv Link>
  6. Herrmann, L., Granz, M., & Landgraf, T. (2022, October). Chaotic Dynamics are Intrinsic to Neural Network Training with SGD. Advances in Neural Information Processing Systems. https://openreview.net/forum?id=ffy-h0GKZbK Link>
  7. Sixt, L., Schuessler, M., Popescu, O.-I., Weiß, P., & Landgraf, T. (2022). Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset. arXiv. https://doi.org/10.48550/arXiv.2204.11642 Link>
  8. Nader, Y., Sixt, L., & Landgraf, T. (2022). DNNR: Differential Nearest Neighbors Regression. arXiv. https://doi.org/10.48550/arXiv.2205.08434 Link>
  9. Sixt, L., & Landgraf, T. (2022). A Rigorous Study Of The Deep Taylor Decomposition. arXiv. https://doi.org/10.48550/arXiv.2211.08425 Link>

2021

  1. Wild, B., Dormagen, D. M., Zachariae, A., Smith, M. L., Traynor, K. S., Brockmann, D., Couzin, I. D., & Landgraf, T. (2021). Social networks predict the life and death of honey bees. Nature Communications, 12(1), 1110. https://doi.org/10.1038/s41467-021-21212-5 Link>
  2. Bierbach, D., Francisco, F., Lukas, J., Landgraf, T., Maxeiner, M., Romanczuk, P., Musiolek, L., Hafner, V. V., & Krause, J. (2021, July). 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 Link>
  3. Ilgün, A., Angelov, K., Stefanec, M., Schönwetter-Fuchs, S., Stokanic, V., Vollmann, J., Hofstadler, D. N., Kärcher, M. H., Mellmann, H., Taliaronak, V., Kviesis, A., Komasilovs, V., Becher, M. A., Szopek, M., Dormagen, D. M., Barmak, R., Bairaktarov, E., Broisin, M., Thenius, R., … Schmickl, T. (2021, July). Bio-Hybrid Systems for Ecosystem Level Effects. ALIFE 2021: The 2021 Conference on Artificial Life. https://doi.org/10.1162/isal_a_00396 Link>
  4. Worm, M., Landgraf, T., & von der Emde, G. (2021). Electric signal synchronization as a behavioural strategy to generate social attention in small groups of mormyrid weakly electric fish and a mobile fish robot. Biological Cybernetics. https://doi.org/10.1007/s00422-021-00892-8 Link>
  5. Paffhausen, B. H., Petrasch, J., Wild, B., Meurers, T., Schülke, T., Polster, J., Fuchs, I., Drexler, H., Kuriatnyk, O., Menzel, R., & Landgraf, T. (2021). A flying platform to investigate neuronal correlates of navigation in the honey bee (Apis mellifera). Frontiers in Behavioral Neuroscience, 15. https://doi.org/10.3389/fnbeh.2021.690571 Link>
  6. 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 Link>
  7. Landgraf, T., Gebhardt, G. H. W., Bierbach, D., Romanczuk, P., Musiolek, L., Hafner, V. V., & Krause, J. (2021). Animal-in-the-Loop: Using Interactive Robotic Conspecifics to Study Social Behavior in Animal Groups. Annual Review of Control, Robotics, and Autonomous Systems, 4(1), 487–507. https://doi.org/10.1146/annurev-control-061920-103228 Link>
  8. 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. Frontiers in Physics, 9. https://www.frontiersin.org/articles/10.3389/fphy.2021.715996 Link>
  9. Smith, M. L., Davidson, J. D., Wild, B., Dormagen, D. M., Landgraf, T., & Couzin, I. D. (2021). The dominant axes of lifetime behavioral variation in honey bees. bioRxiv. https://doi.org/10.1101/2021.04.15.440020 Link>
  10. Wild, B., Dormagen, D. M., Smith, M. L., & Landgraf, T. (2021). Learning to embed lifetime social behavior from interaction dynamics. bioRxiv. https://doi.org/10.1101/2021.09.01.458538 Link>
  11. 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. https://doi.org/10.48550/arXiv.2106.00959 Link>
  12. Solopova, V., Popescu, O.-I., Chikobava, M., Romeike, R., Landgraf, T., & Benzmüller, C. (2021). A German Corpus of Reflective Sentences. Proceedings of the 18th International Conference on Natural Language Processing (ICON), 593–600. https://aclanthology.org/2021.icon-main.72 Link>

2020

  1. Sixt, L., Granz, M., & Landgraf, T. (2020). When Explanations Lie: Why Many Modified BP Attributions Fail. Proceedings of the International Conference on Machine Learning, 1. https://proceedings.icml.cc/paper/2020/hash/af21d0c97db2e27e13572cbf59eb343d Link>
  2. 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 Link>
  3. Sixt, L., Schuessler, M., Weiß, P., & Landgraf, T. (2020). Interpretability Through Invertibility: A Deep Convolutional Network With Ideal Counterfactuals And Isosurfaces. https://openreview.net/forum?id=8YFhXYe1Ps Link>
  4. Wild, B., Dormagen, D., Smith, M. L., & Landgraf, T. (2020). Individuality in the hive - Learning to embed lifetime social behaviour of honey bees. https://openreview.net/forum?id=2LBhynkS2SC Link>
  5. 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 International Publishing. https://doi.org/10.1007/978-3-030-64313-3_26
  6. Wario, F., Wild, B., Dormagen, D., Landgraf, T., & Trianni, V. (2020). Motion Dynamics of Foragers in Honey Bee Colonies. In M. Dorigo, T. Stützle, M. J. Blesa, C. Blum, H. Hamann, M. K. Heinrich, & V. Strobel (Eds.), Swarm Intelligence (pp. 203–215). Springer International Publishing. https://doi.org/10.1007/978-3-030-60376-2_16
  7. 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 Link>
  8. Schulz, K., Sixt, L., Tombari, F., & Landgraf, T. (2020, May). Restricting the Flow: Information Bottlenecks for Attribution. Proceedings of the International Conference on Learning Representations. https://openreview.net/forum?id=S1xWh1rYwB Link>
  9. Schulz, K., Sixt, L., Tombari, F., & Landgraf, T. (2020). Restricting the Flow: Information Bottlenecks for Attribution. arXiv. https://doi.org/10.48550/arXiv.2001.00396 Link>
  10. 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. https://doi.org/10.48550/arXiv.2009.06633 Link>

2019

  1. Paffhausen, B., Petrasch, J., Wild, B., Fuchs, I., Drexler, H., Kuriatnyk, O., Meurers, T., Landgraf, T., & Menzel, R. (2019). Neural correlates of mushroom body output neurons measured during flight of a harnessed honey bee on a quad copter.
  2. Menzel, R., Tison, L., Fischer-Nakai, J., Cheeseman, J., Balbuena, M. S., Chen, X., Landgraf, T., Petrasch, J., Polster, J., & Greggers, U. (2019). Guidance of Navigating Honeybees by Learned Elongated Ground Structures. Frontiers in Behavioral Neuroscience, 12. https://doi.org/10.3389/fnbeh.2018.00322 Link>
  3. Polster, J., Petrasch, J., Menzel, R., & Landgraf, T. (2019). Reconstructing the visual perception of honey bees in complex 3-D worlds. arXiv. https://doi.org/10.48550/arXiv.1811.07560 Link>

2018

  1. Boenisch, F., Rosemann, B., Wild, B., Dormagen, D., Wario, F., & Landgraf, T. (2018). Tracking All Members of a Honey Bee Colony Over Their Lifetime Using Learned Models of Correspondence. Frontiers in Robotics and AI, 5. https://doi.org/10.3389/frobt.2018.00035 Link>
  2. Bierbach, D., Lukas, J., Bergmann, A., Elsner, K., Höhne, L., Weber, C., Weimar, N., Arias-Rodriguez, L., Mönck, H. J., Nguyen, H., Romanczuk, P., Landgraf, T., & Krause, J. (2018). Insights into the Social Behavior of Surface and Cave-Dwelling Fish (Poecilia mexicana) in Light and Darkness through the Use of a Biomimetic Robot. Frontiers in Robotics and AI, 5. https://doi.org/10.3389/frobt.2018.00003 Link>
  3. Bierbach, D., Landgraf, T., Romanczuk, P., Lukas, J., Nguyen, H., Wolf, M., & Krause, J. (2018). Using a robotic fish to investigate individual differences in social responsiveness in the guppy. Royal Society Open Science, 5(8), 181026. https://doi.org/10.1098/rsos.181026 Link>
  4. Worm, M., Landgraf, T., Prume, J., Nguyen, H., Kirschbaum, F., & Emde, G. von der. (2018). Evidence for mutual allocation of social attention through interactive signaling in a mormyrid weakly electric fish. Proceedings of the National Academy of Sciences, 115(26), 6852–6857. https://doi.org/10.1073/pnas.1801283115 Link>
  5. Sixt, L., Wild, B., & Landgraf, T. (2018). RenderGAN: Generating Realistic Labeled Data. Frontiers in Robotics and AI, 5. https://doi.org/10.3389/frobt.2018.00066 Link>
  6. Müller, J., Nawrot, M., Menzel, R., & Landgraf, T. (2018). A neural network model for familiarity and context learning during honeybee foraging flights. Biological Cybernetics, 112(1-2), 113–126. https://doi.org/10.1007/s00422-017-0732-z Link>
  7. Boenisch, F., Rosemann, B., Wild, B., Wario, F., Dormagen, D., & Landgraf, T. (2018). Tracking all members of a honey bee colony over their lifetime. arXiv. https://doi.org/10.48550/arXiv.1802.03192 Link>
  8. Wild, B., Sixt, L., & Landgraf, T. (2018). Automatic localization and decoding of honeybee markers using deep convolutional neural networks. arXiv. https://doi.org/10.48550/arXiv.1802.04557 Link>
  9. Landgraf, T., Bierbach, D., Kirbach, A., Cusing, R., Oertel, M., Lehmann, K., Greggers, U., Menzel, R., & Rojas, R. (2018). Dancing Honey bee Robot Elicits Dance-Following and Recruits Foragers. arXiv. https://doi.org/10.48550/arXiv.1803.07126 Link>
  10. Mönck, H. J., Jörg, A., von Falkenhausen, T., Tanke, J., Wild, B., Dormagen, D., Piotrowski, J., Winklmayr, C., Bierbach, D., & Landgraf, T. (2018). BioTracker: An Open-Source Computer Vision Framework for Visual Animal Tracking. arXiv. https://doi.org/10.48550/arXiv.1803.07985 Link>

2017

  1. Sixt, L., Wild, B., & Landgraf, T. (2017). RenderGAN: Generating Realistic Labeled Data. http://arxiv.org/abs/1611.01331 Link>
  2. Landgraf, T., & Nawrot, M. (2017). Künstliche Mini-Gehirne für Roboter. In Planen und Handeln (pp. 135–150). Springer Spektrum, Wiesbaden.
  3. Lam, C., Li, Y., Landgraf, T., & Nieh, J. (2017). Dancing attraction: followers of honey bee tremble and waggle dances exhibit similar behaviors. Biology Open, bio–025445.
  4. Wario, F., Wild, B., Rojas, R., & Landgraf, T. (2017). Automatic detection and decoding of honey bee waggle dances. PLOS ONE, 12(12), e0188626. https://doi.org/10.1371/journal.pone.0188626 Link>

2016

  1. Landgraf, T., Bierbach, D., Nguyen, H., Muggelberg, N., Romanczuk, P., & Krause, J. (2016). RoboFish: increased acceptance of interactive robotic fish with realistic eyes and natural motion patterns by live Trinidadian guppies. Bioinspiration & Biomimetics, 11(1), 015001.

2015

  1. Wario, F., Wild, B., Couvillon, M. J., Rojas, R., & Landgraf, T. (2015). Automatic methods for long-term tracking and the detection and decoding of communication dances in honeybees. Frontiers in Ecology and Evolution, 3. https://doi.org/10.3389/fevo.2015.00103

2014

  1. Landgraf, T., Nguyen, H., Schröer, J., Szengel, A., Clément, R. J. G., Bierbach, D., & Krause, J. (2014). Blending in with the shoal: robotic fish swarms for investigating strategies of group formation in guppies. Conference on Biomimetic and Biohybrid Systems, 178–189.
  2. Jin, N., Landgraf, T., Klein, S., & Menzel, R. (2014). Walking bumblebees memorize panorama and local cues in a laboratory test of navigation. Animal Behaviour, 97, 13–23. http://www.sciencedirect.com/science/article/pii/S0003347214003273 Link>
  3. Worm, M., Landgraf, T., Nguyen, H., & von der Emde, G. (2014). Electro-communicating dummy fish initiate group behavior in the weakly electric fish Mormyrus rume. Conference on Biomimetic and Biohybrid Systems, 446–448.

2013

  1. Landgraf, T. (2013). RoboBee: A Biomimetic Honeybee Robot for the Analysis of the Dance Communication System [PhD thesis, Berlin, Freie Universität Berlin, 2013]. http://www.diss.fu-berlin.de/diss/receive/FUDISS_thesis_000000094818?lang=de Link>
  2. Landgraf, T., Nguyen, H., Forgo, S., Schneider, J., Schröer, J., Krüger, C., Matzke, H., Clément, R. O., Krause, J., & Rojas, R. (2013). Interactive robotic fish for the analysis of swarm behavior. International Conference in Swarm Intelligence, 1–10. http://link.springer.com/chapter/10.1007/978-3-642-38703-6_1 Link>
  3. Helgadóttir, L. I., Haenicke, J., Landgraf, T., Rojas, R., & Nawrot, M. P. (2013). Conditioned behavior in a robot controlled by a spiking neural network. Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference On, 891–894. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6696078 Link>
  4. Landgraf, T., Wild, B., Ludwig, T., Nowak, P., Helgadottir, L., Daumenlang, B., Breinlinger, P., Nawrot, M., & Rojas, R. (2013). NeuroCopter: neuromorphic computation of 6D ego-motion of a quadcopter. Conference on Biomimetic and Biohybrid Systems, 143–153. http://link.springer.com/chapter/10.1007/978-3-642-39802-5_13 Link>

2012

  1. Landgraf, T., Akkad, R., Nguyen, H., Clément, R. O., Krause, J., & Rojas, R. (2012). A Multi-agent Platform for Biomimetic Fish. Conference on Biomimetic and Biohybrid Systems, 365–366. http://link.springer.com/chapter/10.1007/978-3-642-31525-1_44 Link>
  2. Helgadottir, L. I., Haenicke, J., Landgraf, T., & Nawrot, M. P. (2012). A Robotic Platform for Spiking Neural Control Architectures. Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012., 154.
  3. Landgraf, T., Oertel, M., Kirbach, A., Menzel, R., & Rojas, R. (2012). Imitation of the honeybee dance communication system by means of a biomimetic robot. Conference on Biomimetic and Biohybrid Systems, 132–143. http://link.springer.com/chapter/10.1007/978-3-642-31525-1_12 Link>

2011

  1. Meyer, J., Haenicke, J., Landgraf, T., Schmuker, M., Rojas, R., & Nawrot, M. (2011). A digital receptor neuron connecting remote sensor hardware to spiking neural networks. BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011.
  2. Landgraf, T. (2011). Blending into the Hive: A Novel Biomimetic Honeybee Robot for the Analysis of the Dance Communication System. International Workshop on Bio-Inspired Robots, Nantes April 6-8.
  3. Landgraf, T., Rojas, R., Nguyen, H., Kriegel, F., & Stettin, K. (2011). Analysis of the Waggle Dance Motion of Honeybees for the Design of a Biomimetic Honeybee Robot. PLoS ONE, 6(8), e21354. https://doi.org/10.1371/journal.pone.0021354 Link>

2007-2010

  1. Landgraf, T., Moballegh, H., & Rojas, R. (2008). Design and development of a robotic bee for the analysis of honeybee dance communication. Applied Bionics and Biomechanics, 5(3), 157–164. http://www.tandfonline.com/doi/abs/10.1080/11762320802617552 Link>
  2. Hussaini, S. A., Bogusch, L., Landgraf, T., & Menzel, R. (2009). Sleep deprivation affects extinction but not acquisition memory in honeybees. Learning & Memory, 16(11), 698–705. http://learnmem.cshlp.org/content/16/11/698.short Link>
  3. Landgraf, T., & Rojas, R. (2007). Tracking honey bee dances from sparse optical flow fields. https://refubium.fu-berlin.de/handle/fub188/19039 Link>
  4. Landgraf, T., Oertel, M., Rhiel, D., & Rojas, R. (2010). A biomimetic honeybee robot for the analysis of the honeybee dance communication system. Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference On, 3097–3102.