@article{15025, abstract = {{In software engineering, the imprecise requirements of a user are transformed to a formal requirements specification during the requirements elicitation process. This process is usually guided by requirements engineers interviewing the user. We want to partially automate this first step of the software engineering process in order to enable users to specify a desired software system on their own. With our approach, users are only asked to provide exemplary behavioral descriptions. The problem of synthesizing a requirements specification from examples can partially be reduced to the problem of grammatical inference, to which we apply an active coevolutionary learning approach. However, this approach would usually require many feedback queries to be sent to the user. In this work, we extend and generalize our active learning approach to receive knowledge from multiple oracles, also known as proactive learning. The ‘user oracle’ represents input received from the user and the ‘knowledge oracle’ represents available, formalized domain knowledge. We call our two-oracle approach the ‘first apply knowledge then query’ (FAKT/Q) algorithm. We compare FAKT/Q to the active learning approach and provide an extensive benchmark evaluation. As result we find that the number of required user queries is reduced and the inference process is sped up significantly. Finally, with so-called On-The-Fly Markets, we present a motivation and an application of our approach where such knowledge is available.}}, author = {{Wever, Marcel Dominik and van Rooijen, Lorijn and Hamann, Heiko}}, journal = {{Evolutionary Computation}}, number = {{2}}, pages = {{165–193}}, publisher = {{MIT Press Journals}}, title = {{{Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets}}}, doi = {{10.1162/evco_a_00266}}, volume = {{28}}, year = {{2020}}, } @inproceedings{2850, author = {{Hamann, Heiko and Markarian, Christine and Meyer auf der Heide, Friedhelm and Wahby, Mostafa}}, booktitle = {{Ninth International Conference on Fun with Algorithms (FUN)}}, title = {{{Pick, Pack, & Survive: Charging Robots in a Modern Warehouse based on Online Connected Dominating Sets}}}, doi = {{10.4230/LIPIcs.FUN.2018.22}}, year = {{2018}}, } @inproceedings{97, abstract = {{Bridging the gap between informal, imprecise, and vague user requirements descriptions and precise formalized specifications is the main task of requirements engineering. Techniques such as interviews or story telling are used when requirements engineers try to identify a user's needs. The requirements specification process is typically done in a dialogue between users, domain experts, and requirements engineers. In our research, we aim at automating the specification of requirements. The idea is to distinguish between untrained users and trained users, and to exploit domain knowledge learned from previous runs of our system. We let untrained users provide unstructured natural language descriptions, while we allow trained users to provide examples of behavioral descriptions. In both cases, our goal is to synthesize formal requirements models similar to statecharts. From requirements specification processes with trained users, behavioral ontologies are learned which are later used to support the requirements specification process for untrained users. Our research method is original in combining natural language processing and search-based techniques for the synthesis of requirements specifications. Our work is embedded in a larger project that aims at automating the whole software development and deployment process in envisioned future software service markets.}}, author = {{van Rooijen, Lorijn and Bäumer, Frederik Simon and Platenius, Marie Christin and Geierhos, Michaela and Hamann, Heiko and Engels, Gregor}}, booktitle = {{2017 IEEE 25th International Requirements Engineering Conference Workshops (REW)}}, isbn = {{978-1-5386-3489-9}}, keywords = {{Software, Unified modeling language, Requirements engineering, Ontologies, Search problems, Natural languages}}, location = {{Lisbon, Portugal}}, pages = {{379--385}}, publisher = {{IEEE}}, title = {{{From User Demand to Software Service: Using Machine Learning to Automate the Requirements Specification Process}}}, doi = {{10.1109/REW.2017.26}}, year = {{2017}}, } @inproceedings{19961, abstract = {{The self-organizing bio-hybrid collaboration ofrobots and natural plants allows for a variety of interestingapplications. As an example we investigate how robots can beused to control the growth and motion of a natural plant, using LEDs to provide stimuli. We follow an evolutionaryrobotics approach where task performance is determined bymonitoring the plant's reaction. First, we do initial plantexperiments with simple, predetermined controllers. Then weuse image sampling data as a model of the dynamics ofthe plant tip xy position. Second, we use this approach toevolve robot controllers in simulation. The task is to makethe plant approach three predetermined, distinct points in anxy-plane. Finally, we test the evolved controllers in real plantexperiments and find that we cross the reality gap successfully. We shortly describe how we have extended from plant tipto many points on the plant, for a model of the plant stemdynamics. Future work will extend to two-axes image samplingfor a 3-d approach.}}, author = {{Wahby, Mostafa and Hofstadler, Daniel Nicolas and Heinrich, Mary Katherine and Zahadat, Payam and Hamann, Heiko}}, booktitle = {{Proc. of the 10th International Conference on Self-Adaptive and Self-Organizing Systems}}, isbn = {{9781509035342}}, title = {{{An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap}}}, doi = {{10.1109/saso.2016.8}}, year = {{2016}}, } @inproceedings{19968, author = {{Heinrich, Mary Katherine and Wahby, Mostafa and Divband Soorati, Mohammad and Hofstadler, Daniel Nicolas and Zahadat, Payam and Ayres, Phil and Stoy, Kasper and Hamann, Heiko}}, booktitle = {{Proc. of the 1st International Workshop on Self-Organising Construction (SOCO)}}, isbn = {{9781509036516}}, title = {{{Self-Organized Construction with Continuous Building Material: Higher Flexibility Based on Braided Structures}}}, doi = {{10.1109/fas-w.2016.43}}, year = {{2016}}, } @article{19969, author = {{Hamann, Heiko and Khaluf, Yara and Botev, Jean and Divband Soorati, Mohammad and Ferrante, Eliseo and Kosak, Oliver and Montanier, Jean-Marc and Mostaghim, Sanaz and Redpath, Richard and Timmis, Jon and Veenstra, Frank and Wahby, Mostafa and Zamuda, Aleš}}, issn = {{2296-9144}}, journal = {{Frontiers in Robotics and AI}}, title = {{{Hybrid Societies: Challenges and Perspectives in the Design of Collective Behavior in Self-organizing Systems}}}, doi = {{10.3389/frobt.2016.00014}}, year = {{2016}}, } @inproceedings{19979, author = {{Hamann, Heiko and Divband Soorati, Mohammad}}, booktitle = {{IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016)}}, title = {{{Robot Self-Assembly as Adaptive Growth Process: Collective Selection of Seed Position and Self-Organizing Tree-Structures}}}, doi = {{10.1109/IROS.2016.7759845}}, year = {{2016}}, } @article{19983, author = {{Dorigo, Marco and Hamann, Heiko and Valentini, Gabriele and Ferrante, Eliseo}}, journal = {{Journal of Autonomous Agents and Multi-Agent Systems}}, number = {{3}}, pages = {{553--580}}, title = {{{Collective Decision with 100 Kilobots: Speed vs Accuracy in Binary Discrimination Problems}}}, doi = {{10.1007/s10458-015-9323-3}}, volume = {{30}}, year = {{2016}}, } @inproceedings{20000, author = {{Hamann, Heiko and Valentini, Gabriele and Dorigo, Marco}}, booktitle = {{10th Int. Conf. on Swarm Intelligence, ANTS 2016}}, isbn = {{9783319444260}}, issn = {{0302-9743}}, title = {{{Population Coding: A New Design Paradigm for Embodied Distributed Systems}}}, doi = {{10.1007/978-3-319-44427-7_15}}, year = {{2016}}, } @inproceedings{20001, author = {{von Mammen, Sebastian and Hamann, Heiko and Heider, Michael}}, booktitle = {{ACM Symposium on Virtual Reality Software and Technology (VRST)}}, isbn = {{9781450344913}}, title = {{{Robot Gardens: An Augmented Reality Prototype for Plant-Robot Biohybrid Systems}}}, doi = {{10.1145/2993369.2993400}}, year = {{2016}}, } @inproceedings{20002, author = {{Rybář, Milan and Hamann, Heiko}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2016)}}, isbn = {{9781450342063}}, title = {{{Inspiration-Triggered Search: Towards Higher Complexities by Mimicking Creative Processes}}}, doi = {{10.1145/2908812.2908815}}, year = {{2016}}, } @inproceedings{20003, author = {{Khaluf, Yara and Hamann, Heiko}}, booktitle = {{ANTS 2016}}, pages = {{298}}, title = {{{On the Definition of Self-organizing Systems: Relevance of Positive/Negative Feedback and Fluctuations}}}, volume = {{9882}}, year = {{2016}}, } @inproceedings{20004, author = {{Valentini, Gabriele and Brambilla, Davide and Hamann, Heiko and Dorigo, Marco}}, booktitle = {{10th Int. Conf. on Swarm Intelligence, ANTS 2016}}, isbn = {{9783319444260}}, issn = {{0302-9743}}, title = {{{Collective Perception of Environmental Features in a Robot Swarm}}}, doi = {{10.1007/978-3-319-44427-7_6}}, year = {{2016}}, } @inproceedings{169, abstract = {{We apply methods of genetic programming to a general problem from software engineering, namely example-based generation of specifications. In particular, we focus on model transformation by example. The definition and implementation of model transformations is a task frequently carried out by domain experts, hence, a (semi-)automatic approach is desirable. This application is challenging because the underlying search space has rich semantics, is high-dimensional, and unstructured. Hence, a computationally brute-force approach would be unscalable and potentially infeasible. To address that problem, we develop a sophisticated approach of designing complex mutation operators. We define ‘patterns’ for constructing mutation operators and report a successful case study. Furthermore, the code of the evolved model transformation is required to have high maintainability and extensibility, that is, the code should be easily readable by domain experts. We report an evaluation of this approach in a software engineering case study.}}, author = {{Kühne, Thomas and Hamann, Heiko and Arifulina, Svetlana and Engels, Gregor}}, booktitle = {{Proceedings of the 19th European Conference on Genetic Programming (EuroGP 2016)}}, pages = {{278----293}}, title = {{{Patterns for Constructing Mutation Operators: Limiting the Search Space in a Software Engineering Application}}}, doi = {{10.1007/978-3-319-30668-1_18}}, year = {{2016}}, } @inproceedings{19959, author = {{Wahby, Mostafa and Hamann, Heiko}}, booktitle = {{Applications of Evolutionary Computation (EvoApplications 2015)}}, title = {{{On the Tradeoff between Hardware Protection and Optimization Success: A Case Study in Onboard Evolutionary Robotics for Autonomous Parallel Parking}}}, doi = {{10.1007/978-3-319-16549-3_61}}, year = {{2015}}, } @inproceedings{19960, abstract = {{Besides the life-as-it-could-be driver of artificial life research there is also the concept of extending natural life by creating hybrids or mixed societies that are built from natural and artificial components. In this paper we motivate and present the research program of the project flora robotica. Our objective is to develop and to investigate closely linked symbiotic relationships between robots and natural plants and to explore the potentials of a plant-robot society able to produce architectural artifacts and living spaces. These robot-plant bio-hybrids create synergies that allow for new functions of plants and robots. They also create novel design opportunities for an architecture that fuses the design and construction phase. The bio-hybrid is an example of mixed societies between 'hard' artificial and 'wet' natural life, which enables an interaction between natural and artificial ecologies. They form an embodied, self-organizing, and distributed cognitive system which is supposed to grow and develop over long periods of time resulting in the creation of meaningful architectural structures. A key idea is to assign equal roles to robots and plants in order to create a highly integrated, symbiotic system. Besides the gain of knowledge, this project has the objective to create a bio-hybrid system with a defined function and application -- growing architectural artifacts.}}, author = {{Hamann, Heiko and Wahby, Mostafa and Schmickl, Thomas and Zahadat, Payam and Hofstadler, Daniel and Stoy, Kasper and Risi, Sebastian and Faina, Andres and Veenstra, Frank and Kernbach, Serge and Kuksin, Igor and Kernbach, Olga and Ayres, Phil and Wojtaszek, Przemyslaw}}, booktitle = {{Proceedings of the 2015 IEEE Symposium on Artificial Life (IEEE ALIFE'15)}}, isbn = {{9781479975600}}, title = {{{Flora Robotica - Mixed Societies of Symbiotic Robot-Plant Bio-Hybrids}}}, doi = {{10.1109/ssci.2015.158}}, year = {{2015}}, } @article{19962, abstract = {{Recent approaches in evolutionary robotics (ER) propose to generate behavioral diversity in order to evolve desired behaviors more easily. These approaches require the definition of a behavioral distance, which often includes task-specific features and hence a priori knowledge. Alternative methods, which do not explicitly force selective pressure towards diversity (SPTD) but still generate it, are known from the field of artificial life, such as in artificial ecologies (AEs). In this study, we investigate how SPTD is generated without task-specific behavioral features or other forms of a priori knowledge and detect how methods of generating SPTD can be transferred from the domain of AE to ER. A promising finding is that in both types of systems, in systems from ER that generate behavioral diversity and also in the investigated speciation model, selective pressure is generated towards unpopulated regions of search space. In a simple case study we investigate the practical implications of these findings and point to options for transferring the idea of self-organizing SPTD in AEs to the domain of ER.}}, author = {{Hamann, Heiko}}, issn = {{1064-5462}}, journal = {{Artificial Life}}, pages = {{464--480}}, title = {{{Lessons from Speciation Dynamics: How to Generate Selective Pressure Towards Diversity}}}, doi = {{10.1162/artl_a_00186}}, year = {{2015}}, } @inproceedings{19966, abstract = {{Aggregation is a crucial task in swarm robotics to ensure cooperation. We investigate the task of aggregation on an area specified indirectly by certain environmental features, here it is a light distribution. We extend the original BEECLUST algorithm, that implements an aggregation behavior, to an adaptive variant that automatically adapts to any light conditions. We compare these two control algorithms in a number of swarm robot experiments with different light conditions. The improved, adaptive variant is found to be significantly better in the tested setup.}}, author = {{Wahby, Mostafa and Weinhold, Alexander and Hamann, Heiko}}, booktitle = {{Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)}}, isbn = {{9781631901003}}, title = {{{Revisiting BEECLUST: Aggregation of Swarm Robots with Adaptiveness to Different Light Settings}}}, doi = {{10.4108/eai.3-12-2015.2262877}}, year = {{2015}}, } @inproceedings{19967, author = {{Wahby, Mostafa and Divband Soorati, Mohammad and von Mammen, Sebastian and Hamann, Heiko}}, booktitle = {{Proceedings. 25. Computational Intelligence Workshop}}, title = {{{Evolution of Controllers for Robot-Plant Bio-Hybdrids: A Simple Case Study Using a Model of Plant Growth and Motion}}}, year = {{2015}}, } @inproceedings{19980, abstract = {{Fitness function design is known to be a critical feature of the evolutionary-robotics approach. Potentially, the complexity of evolving a successful controller for a given task can be reduced by integrating a priori knowledge into the fitness function which complicates the comparability of studies in evolutionary robotics. Still, there are only few publications that study the actual effects of different fitness functions on the robot's performance. In this paper, we follow the fitness function classification of Nelson et al. (2009) and investigate a selection of four classes of fitness functions that require different degrees of a priori knowledge. The robot controllers are evolved in simulation using NEAT and we investigate different tasks including obstacle avoidance and (periodic) goal homing. The best evolved controllers were then post-evaluated by examining their potential for adaptation, determining their convergence rates, and using cross-comparisons based on the different fitness function classes. The results confirm that the integration of more a priori knowledge can simplify a task and show that more attention should be paid to fitness function classes when comparing different studies.}}, author = {{Hamann, Heiko and Divband Soorati, Mohammad}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2015)}}, pages = {{153--160}}, publisher = {{ACM}}, title = {{{The Effect of Fitness Function Design on Performance in Evolutionary Robotics: The Influence of a Priori Knowledge}}}, doi = {{10.1145/2739480.2754676}}, year = {{2015}}, }