Pacher, K., Hernández-Román, N., Juarez-Lopez, A., Jiménez-Jiménez, J. E., Lukas, J., Sevinchan, Y., Krause, J., Arias-Rodríguez, L., & Bierbach, D. (2024). Thermal tolerance in an extremophile fish from Mexico is not affected by environmental hypoxia. Biology Open. https://doi.org/10.1242/bio.060223

Ajuwon, V., Cruz, B., Carriço, P., Champalimaud, Kacelnik, A., & Tiago Monteiro, T. (2023). GoFish: A low-cost, open-source platform for closed-loop behavioural experiments on fish. Behavior Research Methods. https://doi.org/10.3758/s13428-022-02049-2

Avanesi, V., Rockstroh, J., Mildner, T., Zargham, N., Reicherts, L., Friehs, M. A., Kontogiorgos, D., Wenig, N., & Malaka, R. (2023). From C-3PO to HAL: Opening The Discourse About The Dark Side of Multi-Modal Social Agents. Proceedings of the 5th International Conference on Conversational User Interfaces.

Aynetdinov, A., Alt, C., & Akbik, A. (2023). Parameter-Efficient Tuning Under Weak Supervision.

Battaje, A., Brock, O., & Rolfs, M. (2023). An Interactive Motion Perception Tool for Kindergarteners (and Vision Scientists). IPerception. https://doi.org/10.1177/20416695231159182

Baum, M., Froessl, A., Battaje, A., & Brock, O. (2023). Estimating the Motion of Drawers From Sound. ICRA 2023.

Bolenz, F., & Pachur, T. (2023). Older Adults Select Different But Not Simpler Strategies Than Younger Adults in Risky Choice. PsyArXiv. https://doi.org/10.31219/osf.io/9vhy8

Breen, A., & Deffner, D. (2023). Leading an urban invasion: risk-sensitive learning is a winning strategy. BioRxiv. https://doi.org/10.1101/2023.03.19.533319

Burema, D., Debowski-Weimann, N., Janowski, A. V., Grabowski, J., Maftei, M., Jacobs, M., Smagt, P. V. D., & Benbouzid, D. (2023). A sector-based approach to AI ethics: Understanding ethical issues of AI-related incidents within their sectoral context. AAAI/ACM Conference on AI, Ethics, and Society (AIES '23).

Burema, D., Jacobs, M., & Rozborski, F. (2023). Elusive technologies, elusive responsibilities: on the perceived responsibility of basic AI researchers. AI and Ethics. https://doi.org/10.1007/s43681-023-00358-6

Chevalère, J., Lazarides, R., Yun, H. S., Henke, A., Lazarides, C., Pinkwart, N., & Hafner, V. (2023). Do instructional strategies considering activity emotions reduce students’ boredom in a computerized open-ended learning environment? Computers & Education, 196. https://doi.org/10.1016/j.compedu.2023.104741

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

Deffner, D., Mezey, D., Kahl, B., Schakowski, A., Romanczuk, P., Wu, C. M., & Kurvers, R. (2023). Collective incentives reduce over-exploitation of social information in unconstrained human groups. PsyArXiv. https://doi.org/10.31234/osf.io/p3bj7

Dolokov, O., A; Andresen, N; Hohlbaum, K; Thöne-Reineke, C; Lewejohann, L; Hellwich. (2023). Upper Bound Tracker: A Multi-Animal Tracking Solution for Closed Laboratory Settings. 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) / VISAPP, 5, 945–952. https://doi.org/10.5220/0011609500003417

Ehlman, S., Scherer, U., Bierbach, D., Francisco, F., Laskowski, K., Krause, J., & Wolf, M. (2023). Leverging big data to uncover the eco-evolutionary factors shaping behavioural development. Proceedings of the Royal Society B.

Enge, A., Süß, F., & Abdel Rahman, R. (2023). Instant Effects of Semantic Information on Visual Perception. Journal of Neuroscience.

Eppinger, B., Ruel, A., & Bolenz, F. (2023). Diminished State Space Theory of Human Aging. Perspectives on Psychological Science. https://doi.org/10.1177/17456916231204811

Foerster, F., Romeo, M., Holthaus, P., Wood, L., Dondrup, C., Fischer, J. E., Liza, F. F., Kaszuba, S., Hough, J., Nesset, B., García, D. H., Kontogiorgos, D., Williams, J., Özkan, E. E., Barnard, P., Berumen, G., Price, D., Cobb, S., Wiltschko, M., … Huang, G. (2023). Working with Troubles and Failures in Conversation between Humans and Robots. Frontiers in Robotics and AI.

Godinez, A., Battaje, A., Brock, O., & Rolfs, M. (2023). Probing Perceptual Mechanism of Shape-Contingent Color after-Images via Interconnected Recursive Filters. Journal of Vision 23 / VSS 2023. https://doi.org/10.1167/jov.23.9.4885

Golde, J., Alt, C., & Akbik, A. (2023). TART: Zero- and Few-Shot Named Entity Recognition Across Languages and Domains.

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

Hamann, F., Ghosh, S., Martínez, I. J., Hart, T., Kacelnik, A., & Gallego, G. (2023). Low-power, Continuous Remote Behavioral Localization with Event Cameras. arXiv. https://doi.org/10.48550/arXiv.2312.03799

Kacelnik, A., Vasconcelos, M., & Monteiro, T. (2023). Testing cognitive models of decision-making: selected studies with starlings. Animal Cognition, 26, 117–127. https://doi.org/10.1007/s10071-022-01723-4

Kahnau, P., Mieske, P., Wilzopolski, J., Kalliokoski, O., Mandillo, S., Hölter, S. M., Voikar, V., Amfim, A., Badurek, S., Bartelik, A., Caruso, A., Čater, M., Ey, E., Golini, E., Jaap, A., Hrncic, D., Kiryk, A., Lang, B., Loncarevic-Vasiljkovic, N., … Hohlbaum, K. (2023). A systematic review of the development and application of home cage monitoring in laboratory mice and rats. BMC Biology, 256(21). https://doi.org/10.1186/s12915-023-01751-7

Kirtay, M., Hafner, V. V., Asada, M., & Oztop, E. (2023). Trust in robot-robot scaffolding. IEEE Transactions on Cognitive and Developmental Systems. https://doi.org/10.1109/TCDS.2023.3235974

Kontogiorgos, D. (2023). Utilising Explanations to Mitigate Robot Conversational Failures. ACM/IEEE International Conference on Human-Robot Interaction Workshops (HRI-W).

Kontogiorgos, D. (2023). Explanations as Communicative Acts in Human-Robot Miscommunication. IEEE International Conference on Robot and Human Interactive Communication - Workshops, IEEE RO-MAN-W 2023.

Kontogiorgos, D., & Schlangen, D. (2023). Explainable Embodied Intelligence for Collaborative Robots: An Interactive Approach. IPrA 2023 - International Pragmatics Conference 2023.

Kurvers, R. H., Nuzzolese, A. G., Russo, A., Barabucci, G., Herzog, S. M., & Trianni, V. (2023). Automating hybrid collective intelligence in open-ended medical diagnostics. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2221473120

Lang, B., Kahnau, P., Hohlbaum, K., Mieske, P., Andresen, N. P., Boon, M. N., Thöne-Reineke, C., Lewejohann, L., & Diederich, K. (2023). Challenges and advanced concepts for the assessment of learning and memory function in mice. Frontiers in Behavioral Neuroscience, 17. https://doi.org/10.3389/fnbeh.2023.1230082

Li, X., Baum, M., & Brock, O. (2023). Augmentation Enables One-Shot Generalization In Learning From Demonstration for Contact-Rich Manipulation. IROS 2023.

Lukas, J., Krause, J., Träger, A. S., Piotrowski, J. M., Romanczuk, P., Sprekeler, H., Arias-Rodriguez, L., Krause, S., Schutz, C., & Bierbach, D. (2023). Multispecies collective waving behaviour in fish. Philosophical Transactions of the Royal Society B. https://doi.org/10.1098/rstb.2022.0069

Mengers, V., Battaje, A., Baum, M., & Brock, O. (2023). Combining Motion and Appearance for Robust Probabilistic Object Segmentation in Real Time. ICRA 2023.

Mezey, D., Deffner, D., Kurvers, R. H., & Romanczuk, P. (2023). Visual social information use in collective foraging. BioRxiv. https://doi.org/

Milich, M., & Akbik, A. (2023). ZELDA: A Comprehensive Benchmark for Supervised Entity Disambiguation. EACL 2023.

Mottelson, A., & Kontogiorgos, D. (2023). Replicating replicability modeling of psychology papers. PNAS.

Patidar, S., Sieler, A., & Brock, O. (2023). In-Hand Cube Reconfiguration: Simplified. IROS 2023.

Poth, N. (2023). Probabilistic Learning and Psychological Similarity. Entropy. https://doi.org/10.3390/e25101407

Raoufi, M., Romanczuk, P., & Hamann, H. (2023). Individuality in Swarm Robots with the Case Study of Kilobots: Noise, Bug, or Feature? Artificial Life (ALife) 2023.

Raoufi, M., Romanczuk, P., & Hamann, H. (2023). Inter-individual Variations in Swarm Robotics with the Case Study of Kilobots. ICRA 2023/workshop "Heterogeneity in Multi-Robot Systems."

Raoufi, M., Romanczuk, P., & Hamann, H. (2023). Estimation of continuous environments by robot swarms: Correlated networks and decision-making. ICRA 2023.

Roth, N., Rolfs, M., Hellwich, O., & Obermayer, K. (2023). Diminished state space theory of human aging. PsyArXiv. https://doi.org/10.31219/osf.io/x7wpj

Roth, N., Rolfs, M., Hellwich, O., & Obermayer, K. (2023). Objects guide human gaze behavior in dynamic real-world scenes. bioRxiv. https://doi.org/10.1101/2023.03.14.532608

Scherer, U., Laskowki, K., Kressler, M., Ehlman, S. M., Wolf, M., & Bierbach, D. (2023). Perceived predation risk affects the development of among-individual behavioral variation in a naturally clonal freshwater fish. BioRxiv. https://doi.org/10.1101/2023.11.25.568653

Scherer, U., Ehlman, S. M., Bierbach, D., Krause, J., & Wolf, M. (2023). Reproductive individuality of clonal fish raised in near-identical environments and its link to early-life behavioral individuality. Nature Communications. https://doi.org/10.1038/s41467-023-43069-6

Schweitzer, R., Doering, M., Seel, T., Raisch, J., & Rolfs, M. (2023). Saccadic omission revisited: What saccade-induced smear looks like. bioRxiv.

Shiba, S., Hamann, F., Aoki, Y., & Gallego, G. (2023). Event-based Background-Oriented Schlieren. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1–16. https://doi.org/10.1109/TPAMI.2023.3328188

Sieler, A., & Brock, O. (2023). Dexterous Soft Hands Linearize Feedback-Control for In-Hand Manipulation. IROS 2023.

Snell-Rood, E., & Ehlman, S. (2023). Developing the genotype-to-phenotype relationship in evolutionary theory: a primer of developmental features. Evolution and Development, 1–17. https://doi.org/10.1111/ede.12434

Stahl, K., Graziadei, A., Dau, T., Brock, O., & Rappsilber, J. (2023). Protein structure prediction with in-cell phot-crosslinking mass spectrometry and deep learning. Nature Biotechnology. https://doi.org/10.1038/s41587-023-01704-z

Tavernier, N., Wisniewski, D., & Brass, M. (2023). Manipulating free will beliefs using online video games. Psychological Research. https://doi.org/10.1007/s00426-023-01815-x

Ajuwon, V., Ojeda, A., Murphy, R., Monteiro, T., & Kacelnik, A. (2022). Paradoxical choice and the reinforcing value of information. Animal Cognition, 26. https://doi.org/10.1007/s10071-022-01698-2

Battaje, A., & Brock, O. (2022). One Object at a Time: Accurate and Robust Structure From Motion for Robots. IROS 2022. https://doi.org/10.1109/IROS47612.2022.9981953

Baum, M., & Brock, O. (2022). "The World Is Its Own Best Model": Robust Real-World Manipulation Through Online Behavior Selection. ICRA 2022. https://doi.org/10.1109/ICRA46639.2022.9811845

Baum, M., Schattenhofer, L., Rössler, T., Osuna-Mascaró, A., Auersperg, A., Kacelnik, A., & Brock, O. (2022). Yoking-Based Identification of Learning Behavior in Artificial and Biological Agents. SAB 2022. https://doi.org/10.1007/978-3-031-16770-6_6

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.

Bolenz, F., & Eppinger, B. (2022). Valence bias in metacontrol of decision making in adolescents and young adults. Child Development. https://doi.org/10.1111/cdev.13693

Bolenz, F., & Pachur, T. (2022). Exploring the structure of predecisional information search in risky choice. Proceedings of the 44th Annual Conference of the Cognitive Science Society, 2297–2302.

Bolenz, F., Profitt, M., Stechbarth, F., Eppinger, B., & Strobel, A. (2022). Need for cognition does not account for individual differences in metacontrol of decision making. Scientific Reports. https://doi.org/10.1038/s41598-022-12341-y

Chen, Y., Mikkelsen, J., Binder, A., Alt, C., & Hennig, L. (2022). A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition. Proceedings of the 7th Workshop on Representation Learning for NLP. https://doi.org/10.18653/v1/2022.repl4nlp-1.6

Chevalère, J., Kirtay, M., Hafner, V., & Lazarides, R. (2022). Who to Observe and Imitate in Humans and Robots: The Importance of Motivational Factors. International Journal of Social Robotics. https://doi.org/10.1007/s12369-022-00923-9

Coelho Mollo, D. (2022). Intelligent Behaviour. Erkenntnis. https://doi.org/10.1007/s10670-022-00552-8

Deffner, D., & McElreath, R. (2022). When does selection favor learning from the old? Social learning in age-structured populations. Plos One. https://doi.org/10.1371/journal.pone.0267204

Deffner, D., Rohrer, J., & McElreath, R. (2022). A Causal Framework for Cross-Cultural Generalizability. Advances in Methods and Practices in Psychological Science. https://doi.org/10.1177/2515245922110636

Deffner, D., Kandler, A., & Fogarty, L. (2022). Effective population size for culturally evolving traits. Plos Computational Biology. https://doi.org/10.1371/journal.pcbi.1009430

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

Driess, D., Schubert, I., Florence, P., Li, Y., & Toussaint, M. (2022). Reinforcement Learning with Neural Radiance Fields. NeurIPS 2022. https://doi.org/10.48550/arXiv.2206.01634

Driess, D., Huang, Z., Li, Y., Tedrake, R., & Toussaint, M. (2022). Learning Multi-Object Dynamics with Compositional Neural Radiance Fields. CoRL 2022. https://doi.org/10.48550/arXiv.2202.11855

Ehlman, S., Scherer, U., & Wolf, M. (2022). Developmental feedbacks and the emergence of individuality. Royal Society Open Science.

Ghosh, S., & Gallego, G. (2022). Event-based Stereo Depth Estimation from Ego-motion using Ray Density Fusion. ECCVW Ego4D 2022.

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

Goris, J., Braem, S., Herck, S. V., Simoens, J., Deschrijver, E., Wiersema, J. R., Paton, B., Brass, M., & Todd, J. (2022). Reduced primacy bias in autism during early sensory processing. Journal of Neuroscience, 19(42). https://doi.org/10.1523/JNEUROSCI.3088-20.2022

Ha, J.-S., Driess, D., & Toussaint, M. (2022). Deep Visual Constraints: Neural Implicit Models for Manipulation Planning from Visual Input. IEEE Robotics and Automation Letters. https://doi.org/10.1109/LRA.2022.3194955

Halawa, M., Hellwich, O., & Bideau, P. (2022). Action based Contrastive Learning for Trajectory Prediction. European Conference on Computer Vision (ECCV), 143–159. https://doi.org/10.1007/978-3-031-19842-7_9

Hamann, F., & Gallego, G. (2022). Stereo Co-capture System for Recording and Tracking Fish with Frame- and Event Cameras. International Conference on Pattern Recognition (ICPR), Workshop on Visual observation and analysis of Vertebrate And Insect Behavior.

Hansen, M., Krause, S., Dhellemmes, F., Pacher, K., Kurves, R., Domenici, P., & Krause, J. (2022). Mechanisms of prey division in striped marlin, a marine group hunting predator. Communications Biology.

Harbecke, D., Chen, Y., Hennig, L., & Alt, C. (2022). Why only Micro-F1? Class Weighting of Measures for Relation Classification. Proceedings of the 1st Workshop on Efficient Benchmarking in NLP. https://doi.org/10.18653/v1/2022.nlppower-1.4

Harris, J., Driess, D., & Toussaint, M. (2022). FC3: Feasibility-Based Control Chain Coordination. IROS 2022. https://doi.org/10.1109/IROS47612.2022.9981758

Henke, L., Guseva, M., Wagemans, K., Pischedda, D., Haynes, J.-D., Jahn, G., & Anders, S. (2022). Surgical face masks do not impair the decoding of facial expressions of negative affect more severely in older than in younger adults. Cognitive Research: Principles and Implications, 7, 63. https://doi.org/10.1186/s41235-022-00403-8

Kamat, J., Ortiz-Haro, J., Toussaint, M., Pokorny, F. T., & Orthey, A. (2022). BITKOMO: Combining Sampling and Optimization for Fast Convergence in Optimal Motion Planning. IROS 2022. https://doi.org/10.1109/IROS47612.2022.9981732

Kirtay, M., Oztop, E., Kuhlen, A. K., Asada, M., & Hafner, V. V. (2022). Trustworthiness assessment in multimodal human-robot interaction based on cognitive load. 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 469–476. https://doi.org/10.1109/RO-MAN53752.2022.9900730

Kirtay, M., Oztop, E., Kuhlen, A. K., Asada, M., & Hafner, V. V. (2022). Forming robot trust in heterogeneous agents during a multimodal interactive game. 2022 IEEE International Conference on Development and Learning (ICDL), 307–313. https://doi.org/10.1109/ICDL53763.2022.9962212

Lange, R., & Sprekeler, H. (2022). Learning not to learn: Nature versus Nurture in Silico. AAAI 2022. https://doi.org/10.48550/arXiv.2010.04466

Laskowski, K., Bierbach, D., Jolles, J., Doran, C., & Wolf, M. (2022). The emergence and development of behavioral individuality in clonal fish. Nature Communications. https://doi.org/10.1038/s41467-022-34113-y

Li, X., & Brock, O. (2022). Learning from Demonstration Based On Environmental Constraints. IEEE Robotics and Automation Letters with IROS Option. https://doi.org/10.1109/LRA.2022.3196096

Maier, M., Leonhardt, Alexander, & Abdel Rahman, R. (2022). Bad robots? Humans rapidly attribute mental states during the perception of robot faces. KogWis 2022.

Maier, M., Frömer, R., Rost, J., Sommer, W., & Abdel Rahman, R. (2022). Linguistic and semantic influences on early vision: evidence from object perception and mental imagery. Cognitive Neuroscience of Language Embodiment and Relativity.

Maier, M., Blume, F., Bideau, P., Hellwich, O., & Abdel Rahman, R. (2022). Knowledge-Augmented Face Perception: Prospects for the Bayesian Brain-Framework to Align AI and Human Vision. Consciousness and Cognition, 101.

Makowicz, A. M., Bierbach, D., Richardson, C., & Hughes, K. A. (2022). Cascading indirect genetic effects in a clonal vertebrate. Proceedings of the Royal Society B.

Makowicz, A. M., Bierbach, D., Richardson, C., & Hughes, K. A. (2022). Cascading indirect genetic effects in a clonal vertebrate. Proceedings of the Royal Society B: Biological Sciences, 289(1978). https://doi.org/10.1098/rspb.2022.0731

McNamara, J., & Wolf, M. (2022). Social interaction can select for reduced ability. Proceedings of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rspb.2022.1788

Molinari, F., Agrawal, N., Stańczak, S., & Raisch, J. (2022). Over-The-Air Max-Consensus in Clustered Networks Adopting Half-Duplex Communication Technology. IEEE Transactions on Control of Network Systems, Early access. https://doi.org/10.1109/TCNS.2022.3212870

Muscinelli, F., Roth, N., Shurygina, O., Obermayer, K., & Rolfs, M. (2022). Object-based Spread of Attention Affects Fixation Duration During Free Viewing. Perception/ ECVP2022.

Ortiz-Haro, J., Karpas, E., Katz, M., & Toussaint, M. (2022). A Conflict-driven Interface between Symbolic Planning and Nonlinear Constraint Solving. IEEE Robotics and Automation Letters. https://doi.org/10.1109/LRA.2022.3191948

Ortiz-Haro, J., Ha, J.-S., Driess, D., & Toussaint, M. (2022). Structured deep generative models for sampling on constraint manifolds in sequential manipulation. CoRL 2021.

Pachur, T. (2022). Strategy selection in decisions from givens: Deciding at a glance? Cognitive Psychology. https://doi.org/10.1016/j.cogpsych.2022.101483

Pannen, T. J., Puhlmann, S., & Brock, O. (2022). A Low-Cost, Easy-to-Manufacture, Flexible, Multi-Taxel Tactile Sensor and its Application to In-Hand Object Recognition. IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.48550/arXiv.2111.09687

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.

Puhlmann, S., Harris, J., & Brock, O. (2022). RBO Hand 3 – A Platform for Soft Dexterous Manipulation. IEEE Transactions on Robotics. https://doi.org/10.48550/arXiv.2201.10883

Reverberi, C., Pischedda, D., Mantovani, M., Haynes, J.-D., & Rustichini, A. (2022). Strategic complexity and cognitive skills affect brain response in interactive decision-making. Scientific Reports, 12, 15896. https://doi.org/10.1038/s41598-022-17951-0

Romanczuk, P., & Daniels, B. C. (2022). Phase Transitions and Criticality in the Collective Behavior of Animals — Self-Organization and Biological Function. Order, Disorder and Criticality.

Amjadi, A. S., Raoufi, M., & Turgut, A. E. (2021). A self-adaptive landmark-based aggregation method for robot swarms. Adaptive Behavior, 30(3), 223–236. https://doi.org/10.1177/1059712320985543

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

Battaje, A., & Brock, O. (2021). Interconnected Recursive Filters in Artificial and Biological Vision. DGR Days 2021, 32–32.

Baum, M., & Brock, O. (2021). Achieving Robustness in a Drawer Manipulation Task by using High-level Feedback instead of Planning. DGR Days, 29–29.

Baum, M., & Brock, O. (2021). Achieving Robustness in a Drawer Manipulation Task by using High-level Feedback instead of Planning. DGR Days.

Bhatt, A., Sieler, A., Puhlmann, S., & Brock, O. (2021). Surprisingly Robust In-Hand Manipulation: An Empirical Study. Proceedings of Robotics: Science and Systems. https://doi.org/10.15607/RSS.2021.XVII.089

Bierbach, D., Francisco, F., Lukas, J., Landgraf, T., Maxeiner, M., Romanczuk, P., Musiolek, L., Hafner, V. V., & Krause, J. (2021). 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

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

Chouzouris, T., Roth, N., Cakan, C., & Obermayer, K. (2021). Applications of optimal nonlinear control to a whole-brain network of FitzHugh-Nagumo oscillators. Physical Review E, 104(2), 24213. https://doi.org/10.1103/PhysRevE.104.024213

Coelho Mollo, D. (2021). Why go for a computation-based approach to cognitive representation. Synthese, 199(3), 6875–6895.

Coelho Mollo, D. (2021). Deflationary realism: Representation and idealisation in cognitive science. Mind & Language, 1–19. https://doi.org/10.1111/mila.12364

Coelho Mollo, D., Millière, R., Rathkopf, C., & Stinson, C. (2021). Conceptual Combinations – Benchmark task for Beyond the Imitation Game Benchmark. Github.

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

Demandt, N., Bierbach, D., Kurvers, R. H. J. M., Krause, J., Kurtz, J., & Scharsack, J. P. (2021). Parasite infection impairs the shoaling behaviour of uninfected shoal members under predator attack. Behavioral Ecology and Sociobiology. https://doi.org/10.1007/s00265-021-03080-7

Driess, D., Ha, J.-S., Toussaint, M., & Tedrake, R. (2021). Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning. CoRL 2021. https://doi.org/10.48550/arXiv.2110.00792

Driess, D., Ha, J.-S., & Toussaint, M. (2021). Learning to solve sequential physical reasoning problems from a scene image. The International Journal of Robotics Research, 40(12–14), 1435–1466. https://doi.org/10.1177/02783649211056967

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. International Conference on Computer Vision (ICCV), 13495–13504. https://doi.org/10.1109/ICCV48922.2021.01324

Kahnau, P., Guenther, A., Boon, M. N., Terzenbach, J. D., Hanitzsch, E., Lewejohann, L., & Brust, V. (2021). Lifetime Observation of Cognition and Physiological Parameters in Male Mice. Frontiers in Behavioral Neuroscience, 15, 709775. https://doi.org/10.3389/fnbeh.2021.709775

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., 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., Chevalère, 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., & Romanczuk, P. (2021). Collective predator evasion: Putting the criticality hypothesis to the test. PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1008832

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

Krause, J., Romanczuk, P., Cracco, E., Arlidge, W., Nassauer, A., & Brass, M. (2021). Collective rule-breaking. Trends in Cognitive Sciences.

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

Laskowski, K. L., Seebacher, F., Habedank, M., Meka, J., & Bierbach, D. (2021). Two Locomotor Traits Show Different Patterns of Developmental Plasticity Between Closely Related Clonal and Sexual Fish. Frontiers in Physiology, 12, 740604. https://doi.org/10.3389/fphys.2021.740604

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/10.1111/bjep.12352

Leonhardt, A., Maier, M., & Abdel Rahman, R. (2021). The impact of affective knowledge on the perception and evaluation of robot faces. 5th Virtual Social Interactions (VSI) Conference.

Lois-Milevicich, J., Cerrutti, M., Kacelnik, A., & Reboreda, J. (2021). Sex differences in learning flexibility in an avian brood parasite, the shiny cowbird. , 189. https://doi.org/10.1016/j.beproc.2021.104438

Lu, Y., Bierbach, D., Ormanns, J., Warren, W. C., Walter, R. B., & Schartl, M. (2021). Fixation of allelic gene expression landscapes and expression bias pattern shape the transcriptome of the clonal Amazon molly. Genome Research. https://doi.org/10.1101/gr.268870.120

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.

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

Mieske, P., Diederich, K., & Lewejohann, L. (2021). Roaming in a Land of Milk and Honey: Life Trajectories and Metabolic Rate of Female Inbred Mice Living in a Semi Naturalistic Environment. Animals, 11(10), 3002. https://doi.org/10.3390/ani11103002

Monteiro, T., Hart, T., & Kacelnik, A. (2021). Imprinting on time-structured acoustic stimuli in ducklings. , 17. https://doi.org/10.1098/rsbl.2021.0381

Mühlhoff, R. (2021). Predictive Privacy: Towards an Applied Ethics of Data Analytics. Ethics and Information Technology. https://doi.org/10.1007/s10676-021-09606-x

Páll, E., & Brock, O. (2021). Analysis of Open-Loop Grasping From Piles. IEEE International Conference on Robotics and Automation (ICRA), 2591–2597. https://doi.org/10.1109/ICRA48506.2021.9561065

Pischedda, D., Lange, A., Kirtay, M., Wudarczyk, O. A., Abdel Rahman, R., Hafner, V. V., Kuhlen, A. K., & Haynes, J.-D. (2021). Who is my interlocutor? Partner-specific neural representations during communicative interactions with human or artificial task partners. 5th Virtual Social Interactions (VSI) Conference.

Pischedda, D., Lange, A., Kirtay, M., Wudarczyk, O. A., Abdel Rahman, R., Hafner, V. V., Kuhlen, A. K., & Haynes, J.-D. (2021). Am I speaking to a human, a robot, or a computer? Neural representations of task partners in communicative interactions with humans or artificial agents. Neuroscience 2021.

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

Pütz, O. (2021). Managing exactness and vagueness in computer science work: Programming and self-repair in meetings. Social Studies of Science, 51(6), 938–961. https://doi.org/10.1177%2F03063127211010972

Raoufi, M., Hamann, H., & Romanczuk, P. (2021). Speed-vs-Accuracy Tradeoff in Collective Estimation: An Adaptive Exploration-Exploitation Case. IEEE 2021 International Symposium on Multi-Robot and Multi-Agent Systems (MRS).

Rolfs, M., & Schweitzer, R. (2021). Coupling perception to action through incidental sensory consequences of motor behaviour. Nature Reviews Psychology, 1, 112–123. https://doi.org/10.1038/s44159-021-00015-x

Roth, N., Bideau, P., Hellwich, O., Rolfs, M., & Obermayer, K. (2021). A modular framework for object-based saccadic decisions in dynamic scenes. CVPR EPIC Workshop / arXiv:2106.06073. https://doi.org/10.48550/arXiv.2106.06073

Roth, N., Bideau, P., Hellwich, O., Rolfs, M., & Obermayer, K. (2021). Modeling the influence of objects on saccadic decisions in dynamic real-world scenes. PERCEPTION / 43rd European Conference on Visual Perception (ECVP) 2021.

Schmittwilken, L., Matic, M., Maertens, M., & Vincent, J. (2021). BRENCH: An open-source framework for b(r)enchmarking brightness models. Journal of Vision. https://doi.org/10.1167/jov.22.3.36

Schubert, I., Driess, D., Oguz, O. S., & Toussaint, M. (2021). Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics. NeurIPS 2021. https://doi.org/10.48550/arXiv.2111.07908

Schweitzer, R., & Rolfs, M. (2021). Intrasaccadic motion streaks jump-start gaze correction. Science Advances, 7(30), eabf2218. https://doi.org/10.1126/sciadv.abf2218

Shurygina, O., & Rolfs, M. (2021). Visual sensitivity and reaction time measures show no evidence for purely exogenous object-based attention. Journal of Vision / VSS 2021, 2571–2571. https://doi.org/10.1167/jov.21.9.2571

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., 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

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

Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, A., others, Pischedda, D., others, & Schonberg, T. (2020). Variability in the analysis of a single neuroimaging dataset by many teams. Nature, 582, 84–88. https://doi.org/10.1038/s41586-020-2314-9

Coelho Mollo, D. (2020). Against Computational Perspectivalism. The British Journal for the Philosophy of Science. https://doi.org/10.1093/bjps/axz036

Halawa, M., Wollhaf, M., Vellasques, E., Sanchez Sanz, U., Urko Sanz, & Hellwich, O. (2020). Learning Disentangled Expression Representations from Facial Images. arxiv and WiCV at ECCV2020. https://doi.org/10.48550/arXiv.2008.07001

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]. https://doi.org/10.48550/arXiv.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

Meindl, M., Molinari, F., Raisch, J., & Seel, T. (2020). Overcoming Output Constraints in Iterative Learning Control Systems by Reference Adaptation. 21st IFAC World Congress, 53, 1480–1486. https://doi.org/10.1016/j.ifacol.2020.12.1938

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

Mühlhoff, R. (2020). Prädiktive Privatheit: Warum wir alle "etwas zu verbergen haben". VerantwortungKI – Künstliche Intelligenz und gesellschaftliche Folgen, herausgegeben von Christoph Markschies und Isabella Hermann. Bd. 3/2020. Berlin-Brandenburgische Akademie der Wissenschaften.

Mühlhoff, R. (2020). Automatisierte Ungleichheit: Ethik der Künstlichen Intelligenz in der biopolitische Wende des Digitalen Kapitalismus. Deutsche Zeitschrift Für Philosophie, 6(68). https://doi.org/10.1515/dzph-2020-0059

Musiolek, L., Hafner, V. V., Krause, J., Landgraf, T., & Bierbach, D. (2020). Robofish as Social Partner for Live Guppies. Biomimetic and Biohybrid Systems, 270–274. https://doi.org/10.1007/978-3-030-64313-3_26

Pischedda, D., Palminteri, S., & Coricelli, G. (2020). The effect of counterfactual information on outcome value coding in medial prefrontal and cingulate cortex: From an absolute to a relative neural code. The Journal of Neuroscience, 40(16), 3268–3277. https://doi.org/10.1523/JNEUROSCI.1712-19.2020

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.

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., Fortenbacher, A., Geißler, S., & Heumos, T. (2020). Towards External Regulation of Emotions Using Sensors: Tow Case Studies. INTED2020, 9313–9320. https://doi.org/10.21125/inted.2020.2576

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

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

Yun, H. S., & Fortenbacher, A. (2019). Listen to your body: making learners aware of their cognitive and affective state. ICER2019.