Wever, M. D., van Rooijen, L., &; Hamann, H. (2020). Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets. Evolutionary Computation, 28(2), 165–193.https://doi.org/10.1162/evco_a_00266 
LibreCat: /record/15025
DOI: 10.1162/evco_a_00266

Hamann, H., Markarian, C., Meyer auf der Heide, F., &; Wahby, M. (2018). Pick, Pack, &; Survive: Charging Robots in a Modern Warehouse based on Online Connected Dominating Sets. In Ninth International Conference on Fun with Algorithms (FUN).https://doi.org/10.4230/LIPIcs.FUN.2018.22 
LibreCat: /record/2850
DOI: 10.4230/LIPIcs.FUN.2018.22

van Rooijen, L., Bäumer, F. S., Platenius, M. C., Geierhos, M., Hamann, H., &; Engels, G. (2017). From User Demand to Software Service: Using Machine Learning to Automate the Requirements Specification Process. In 2017 IEEE 25th International Requirements Engineering Conference Workshops (REW) (pp. 379–385). Piscataway, NJ, USA: IEEE.https://doi.org/10.1109/REW.2017.26 
LibreCat: /record/97
DOI: 10.1109/REW.2017.26

Wahby, M., Hofstadler, D. N., Heinrich, M. K., Zahadat, P., &; Hamann, H. (2016). An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap. In Proc. of the 10th International Conference on Self-Adaptive and Self-Organizing Systems.https://doi.org/10.1109/saso.2016.8 
LibreCat: /record/19961
DOI: 10.1109/saso.2016.8

Heinrich, M. K., Wahby, M., Divband Soorati, M., Hofstadler, D. N., Zahadat, P., Ayres, P.,https://doi.org/10.1109/fas-w.2016.43__Hamann, H. (2016). Self-Organized Construction with Continuous Building Material: Higher Flexibility Based on Braided Structures. In Proc. of the 1st International Workshop on Self-Organising Construction (SOCO).https://doi.org/10.1109/fas-w.2016.43 
LibreCat: /record/19968
DOI: 10.1109/fas-w.2016.43

Hamann, H., Khaluf, Y., Botev, J., Divband Soorati, M., Ferrante, E., Kosak, O.,https://doi.org/10.3389/frobt.2016.00014__Zamuda, A. (2016). Hybrid Societies: Challenges and Perspectives in the Design of Collective Behavior in Self-organizing Systems. Frontiers in Robotics and AI.https://doi.org/10.3389/frobt.2016.00014 
LibreCat: /record/19969
DOI: 10.3389/frobt.2016.00014

Hamann, H., &; Divband Soorati, M. (2016). Robot Self-Assembly as Adaptive Growth Process: Collective Selection of Seed Position and Self-Organizing Tree-Structures. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016).https://doi.org/10.1109/IROS.2016.7759845 
LibreCat: /record/19979
DOI: 10.1109/IROS.2016.7759845

Dorigo, M., Hamann, H., Valentini, G., &; Ferrante, E. (2016). Collective Decision with 100 Kilobots: Speed vs Accuracy in Binary Discrimination Problems. Journal of Autonomous Agents and Multi-Agent Systems, 30(3), 553–580.https://doi.org/10.1007/s10458-015-9323-3 
LibreCat: /record/19983
DOI: 10.1007/s10458-015-9323-3

Hamann, H., Valentini, G., &; Dorigo, M. (2016). Population Coding: A New Design Paradigm for Embodied Distributed Systems. In 10th Int. Conf. on Swarm Intelligence, ANTS 2016. Cham.https://doi.org/10.1007/978-3-319-44427-7_15 
LibreCat: /record/20000
DOI: 10.1007/978-3-319-44427-7_15

von Mammen, S., Hamann, H., &; Heider, M. (2016). Robot Gardens: An Augmented Reality Prototype for Plant-Robot Biohybrid Systems. In ACM Symposium on Virtual Reality Software and Technology (VRST).https://doi.org/10.1145/2993369.2993400 
LibreCat: /record/20001
DOI: 10.1145/2993369.2993400

Rybá, M., &; Hamann, H. (2016). Inspiration-Triggered Search: Towards Higher Complexities by Mimicking Creative Processes. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2016).https://doi.org/10.1145/2908812.2908815 
LibreCat: /record/20002
DOI: 10.1145/2908812.2908815

Khaluf, Y., &; Hamann, H. (2016). On the Definition of Self-organizing Systems: Relevance of Positive/Negative Feedback and Fluctuations. In ANTS 2016 (Vol. 9882, p. 298).
LibreCat: /record/20003

Valentini, G., Brambilla, D., Hamann, H., &; Dorigo, M. (2016). Collective Perception of Environmental Features in a Robot Swarm. In 10th Int. Conf. on Swarm Intelligence, ANTS 2016.https://doi.org/10.1007/978-3-319-44427-7_6 
LibreCat: /record/20004
DOI: 10.1007/978-3-319-44427-7_6

Kühne, T., Hamann, H., Arifulina, S., &; Engels, G. (2016). Patterns for Constructing Mutation Operators: Limiting the Search Space in a Software Engineering Application. In Proceedings of the 19th European Conference on Genetic Programming (EuroGP 2016) (pp. 278--293).https://doi.org/10.1007/978-3-319-30668-1_18 
LibreCat: /record/169
DOI: 10.1007/978-3-319-30668-1_18

Wahby, M., &; Hamann, H. (2015). On the Tradeoff between Hardware Protection and Optimization Success: A Case Study in Onboard Evolutionary Robotics for Autonomous Parallel Parking. In Applications of Evolutionary Computation (EvoApplications 2015).https://doi.org/10.1007/978-3-319-16549-3_61 
LibreCat: /record/19959
DOI: 10.1007/978-3-319-16549-3_61

Hamann, H., Wahby, M., Schmickl, T., Zahadat, P., Hofstadler, D., Stoy, K.,https://doi.org/10.1109/ssci.2015.158__Wojtaszek, P. (2015). Flora Robotica - Mixed Societies of Symbiotic Robot-Plant Bio-Hybrids. In Proceedings of the 2015 IEEE Symposium on Artificial Life (IEEE ALIFE’15).https://doi.org/10.1109/ssci.2015.158 
LibreCat: /record/19960
DOI: 10.1109/ssci.2015.158

Hamann, H. (2015). Lessons from Speciation Dynamics: How to Generate Selective Pressure Towards Diversity. Artificial Life, 464–480.https://doi.org/10.1162/artl_a_00186 
LibreCat: /record/19962
DOI: 10.1162/artl_a_00186

Wahby, M., Weinhold, A., &; Hamann, H. (2015). Revisiting BEECLUST: Aggregation of Swarm Robots with Adaptiveness to Different Light Settings. In Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS).https://doi.org/10.4108/eai.3-12-2015.2262877 
LibreCat: /record/19966
DOI: 10.4108/eai.3-12-2015.2262877

Wahby, M., Divband Soorati, M., von Mammen, S., &; Hamann, H. (2015). Evolution of Controllers for Robot-Plant Bio-Hybdrids: A Simple Case Study Using a Model of Plant Growth and Motion. In Proceedings. 25. Computational Intelligence Workshop.
LibreCat: /record/19967

Hamann, H., &; Divband Soorati, M. (2015). The Effect of Fitness Function Design on Performance in Evolutionary Robotics: The Influence of a Priori Knowledge. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2015) (pp. 153–160). ACM.https://doi.org/10.1145/2739480.2754676 
LibreCat: /record/19980
DOI: 10.1145/2739480.2754676