@inproceedings{16358, author = {{Li, Shouwei and Meyer auf der Heide, Friedhelm and Podlipyan, Pavel}}, booktitle = {{Algorithms for Sensor Systems, Proceedings of the 12th International Symposium on Algorithms and Experiments for Wireless Sensor Networks (ALGOSENSORS)}}, publisher = {{Springer}}, title = {{{The impact of the Gabriel subgraph of the visibility graph on the gathering of mobile autonomous robots}}}, doi = {{10.1007/978-3-319-53058-1_5 }}, year = {{2016}}, } @inproceedings{16359, abstract = {{In this paper, we solve the local gathering problem of a swarm of n indistinguishable, point-shaped robots on a two dimensional grid in asymptotically optimal time O(n) in the fully synchronous FSYNC time model. Given an arbitrarily distributed (yet connected) swarm of robots, the gathering problem on the grid is to locate all robots within a 2x2- sized area that is not known beforehand. Two robots are connected if they are vertical or horizontal neighbors on the grid. The locality constraint means that no global control, no compass, no global communication and only local vision is available; hence, a robot can only see its grid neighbors up to a constant L1-distance, which also limits its movements. A robot can move to one of its eight neighboring grid cells and if two or more robots move to the same location they are merged to be only one robot. The locality constraint is the significant challenging issue here, since robot move- ments must not harm the (only globally checkable) swarm connectivity. For solving the gathering problem, we provide a synchronous algorithm { executed by every robot { which ensures that robots merge without breaking the swarm con- nectivity. In our model, robots can obtain a special state, which marks such a robot to be performing specific connec- tivity preserving movements in order to allow later merge operations of the swarm. Compared to the grid, for gath- ering in the Euclidean plane for the same robot and time model the best known upper bound is O(n^2).}}, author = {{Cord-Landwehr, Andreas and Fischer, Matthias and Jung, Daniel and Meyer auf der Heide, Friedhelm}}, booktitle = {{Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA)}}, pages = {{301--312}}, publisher = {{ACM}}, title = {{{Asymptotically Optimal Gathering on a Grid}}}, doi = {{10.1145/2935764.2935789}}, year = {{2016}}, } @inproceedings{16360, abstract = {{We consider the following variant of the two dimensional gathering problem for swarms of robots: Given a swarm of n indistinguishable, point shaped robots on a two dimensional grid. Initially, the robots form a closed chain on the grid and must keep this connectivity during the whole process of their gathering. Connectivity means, that neighboring robots of the chain need to be positioned at the same or neighboring points of the grid. In our model, gathering means to keep shortening the chain until the robots are located inside a 2*2 subgrid. Our model is completely local (no global control, no global coordinates, no compass, no global communication or vision, ...). Each robot can only see its next constant number of left and right neighbors on the chain. This fixed constant is called the viewing path length. All its operations and detections are restricted to this constant number of robots. Other robots, even if located at neighboring or the same grid point cannot be detected. Only based on the relative positions of its detectable chain neighbors, a robot can decide to obtain a certain state. Based on this state and their local knowledge, the robots do local modifications to the chain by moving to neighboring grid points without breaking the chain. These modifications are performed without the knowledge whether they lead to a global progress or not. We assume the fully synchronous FSYNC model. For this problem, we present a gathering algorithm which needs linear time. This result generalizes a result, where an open chain with specified distinguishable (and fixed) endpoints is considered. }}, author = {{Abshoff, Sebastian and Cord-Landwehr, Andreas and Fischer, Matthias and Jung, Daniel and Meyer auf der Heide, Friedhelm}}, booktitle = {{Proceedings of the 30th International Parallel and Distributed Processing Symposium (IPDPS)}}, pages = {{689--699}}, publisher = {{IEEE}}, title = {{{Gathering a Closed Chain of Robots on a Grid}}}, doi = {{10.1109/IPDPS.2016.51}}, year = {{2016}}, } @inproceedings{16364, author = {{Macker, Alexander and Malatyali, Manuel and Meyer auf der Heide, Friedhelm}}, booktitle = {{2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS)}}, isbn = {{9781509021406}}, title = {{{On Competitive Algorithms for Approximations of Top-k-Position Monitoring of Distributed Streams}}}, doi = {{10.1109/ipdps.2016.91}}, year = {{2016}}, } @unpublished{16396, abstract = {{We consider a scheduling problem where machines need to be rented from the cloud in order to process jobs. There are two types of machines available which can be rented for machine-type dependent prices and for arbitrary durations. However, a machine-type dependent setup time is required before a machine is available for processing. Jobs arrive online over time, have machine-type dependent sizes and have individual deadlines. The objective is to rent machines and schedule jobs so as to meet all deadlines while minimizing the rental cost. Since we observe the slack of jobs to have a fundamental influence on the competitiveness, we study the model when instances are parameterized by their (minimum) slack. An instance is called to have a slack of $\beta$ if, for all jobs, the difference between the job's release time and the latest point in time at which it needs to be started is at least $\beta$. While for $\beta < s$ no finite competitiveness is possible, our main result is an $O(\frac{c}{\varepsilon} + \frac{1}{\varepsilon^3})$-competitive online algorithm for $\beta = (1+\varepsilon)s$ with $\frac{1}{s} \leq \varepsilon \leq 1$, where $s$ and $c$ denotes the largest setup time and the cost ratio of the machine-types, respectively. It is complemented by a lower bound of $\Omega(\frac{c}{\varepsilon})$.}}, author = {{Mäcker, Alexander and Malatyali, Manuel and Meyer auf der Heide, Friedhelm and Riechers, Sören}}, booktitle = {{arXiv:1609.01184}}, title = {{{Cost-efficient Scheduling on Machines from the Cloud}}}, year = {{2016}}, } @article{139, abstract = {{We consider online optimization problems in which certain goods have to be acquired in order to provide a service or infrastructure. Classically, decisions for such problems are considered as final: one buys the goods. However, in many real world applications, there is a shift away from the idea of buying goods. Instead, leasing is often a more flexible and lucrative business model. Research has realized this shift and recently initiated the theoretical study of leasing models (Anthony and Gupta in Proceedings of the integer programming and combinatorial optimization: 12th International IPCO Conference, Ithaca, NY, USA, June 25–27, 2007; Meyerson in Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2005), 23–25 Oct 2005, Pittsburgh, PA, USA, 2005; Nagarajan and Williamson in Discret Optim 10(4):361–370, 2013) We extend this line of work and suggest a more systematic study of leasing aspects for a class of online optimization problems. We provide two major technical results. We introduce the leasing variant of online set multicover and give an O(log(mK)logn)-competitive algorithm (with n, m, and K being the number of elements, sets, and leases, respectively). Our results also imply improvements for the non-leasing variant of online set cover. Moreover, we extend results for the leasing variant of online facility location. Nagarajan and Williamson (Discret Optim 10(4):361–370, 2013) gave an O(Klogn)-competitive algorithm for this problem (with n and K being the number of clients and leases, respectively). We remove the dependency on n (and, thereby, on time). In general, this leads to a bound of O(lmaxloglmax) (with the maximal lease length lmax). For many natural problem instances, the bound improves to O(K2).}}, author = {{Abshoff, Sebastian and Kling, Peter and Markarian, Christine and Meyer auf der Heide, Friedhelm and Pietrzyk, Peter }}, journal = {{Journal of Combinatorial Optimization}}, number = {{4}}, pages = {{ 1197----1216}}, publisher = {{Springer}}, title = {{{Towards the price of leasing online}}}, doi = {{10.1007/s10878-015-9915-5}}, year = {{2016}}, } @inproceedings{143, abstract = {{We present an efficient parallel algorithm for the general Monotone Circuit Value Problem (MCVP) with n gates and an underlying graph of bounded genus k. Our algorithm generalizes a recent result by Limaye et al. who showed that MCVP with toroidal embedding (genus 1) is in NC when the input contains a toroidal embedding of the circuit. In addition to extending this result from genus 1 to any bounded genus k, and unlike the work reported by Limaye et al., we do not require a precomputed embedding to be given. Most importantly, our results imply that given a P-complete problem, it is possible to find an algorithm that makes the problem fall into NC by fixing one or more parameters. Hence, we deduce the interesting analogy: Fixed Parameter Parallelizable (FPP) is with respect to P-complete what Fixed Parameter Tractable (FPT) is with respect to NP-complete. Similar work that uses treewidth as parameter was also presented by Elberfeld et al. in [6].}}, author = {{Abu-Khzam, Faisal N. and Li, Shouwei and Markarian, Christine and Meyer auf der Heide, Friedhelm and Podlipyan, Pavel}}, booktitle = {{Proceedings of the 22nd International Conference on Computing and Combinatorics (COCOON)}}, pages = {{92--102}}, title = {{{The Monotone Circuit Value Problem with Bounded Genus Is in NC}}}, doi = {{10.1007/978-3-319-42634-1_8}}, year = {{2016}}, } @article{145, abstract = {{Comparative evaluations of peer-to-peer protocols through simulations are a viable approach to judge the performance and costs of the individual protocols in large-scale networks. In order to support this work, we present the peer-to-peer system simulator PeerfactSim.KOM, which we extended over the last years. PeerfactSim.KOM comes with an extensive layer model to support various facets and protocols of peer-to-peer networking. In this article, we describe PeerfactSim.KOM and show how it can be used for detailed measurements of large-scale peer-to-peer networks. We enhanced PeerfactSim.KOM with a fine-grained analyzer concept, with exhaustive automated measurements and gnuplot generators as well as a coordination control to evaluate sets of experiment setups in parallel. Thus, by configuring all experiments and protocols only once and starting the simulator, all desired measurements are performed, analyzed, evaluated, and combined, resulting in a holistic environment for the comparative evaluation of peer-to-peer systems. An immediate comparison of different configurations and overlays under different aspects is possible directly after the execution without any manual post-processing. }}, author = {{Feldotto, Matthias and Graffi, Kalman}}, journal = {{Concurrency and Computation: Practice and Experience}}, number = {{5}}, pages = {{1655--1677}}, publisher = {{Wiley Online Library}}, title = {{{Systematic evaluation of peer-to-peer systems using PeerfactSim.KOM}}}, doi = {{10.1002/cpe.3716}}, volume = {{28}}, year = {{2016}}, } @misc{251, author = {{Pfannschmidt, Karlson}}, publisher = {{Universität Paderborn}}, title = {{{Solving the aggregated bandits problem}}}, year = {{2015}}, } @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}}, } @inproceedings{19988, author = {{Hamann, Heiko and Schmickl, Thomas and Zahadat, Payam}}, booktitle = {{13th European Conference on Artificial Life (ECAL 2015)}}, pages = {{174}}, publisher = {{MIT Press}}, title = {{{Evolving Collective Behaviors With Diverse But Predictable Sensor States}}}, doi = {{10.7551/978-0-262-33027-5-ch036}}, year = {{2015}}, } @inbook{19989, author = {{Hamann, Heiko and Correll, Nikolaus and Kacprzyk, Janusz and Pedrycz, Witold}}, booktitle = {{Springer Handbook of Computational Intelligence}}, pages = {{1423--1431}}, publisher = {{Springer}}, title = {{{Probabilistic Modeling of Swarming Systems}}}, doi = {{10.1007/978-3-662-43505-2_74}}, year = {{2015}}, } @inproceedings{19990, author = {{Ding, Hongli and Hamann, Heiko}}, booktitle = {{First International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM 2015)}}, title = {{{Dependability in Swarm Robotics: Error Detection and Correction}}}, year = {{2015}}, } @inproceedings{19991, author = {{Hamann, Heiko and Schmickl, Thomas and Kengyel, Daniela and Zahadat, Payam and Radspieler, Gerald and Wotawa, Franz}}, booktitle = {{Principles and Practice of Multi-Agent Systems (PRIMA 2015)}}, pages = {{201--217}}, title = {{{Potential of Heterogeneity in Collective Behaviors: A Case Study on Heterogeneous Swarms}}}, year = {{2015}}, } @article{19992, author = {{Valentini, Gabriele and Hamann, Heiko}}, issn = {{1935-3812}}, journal = {{Swarm Intelligence}}, pages = {{153--176}}, title = {{{Time-variant feedback processes in collective decision-making systems: influence and effect of dynamic neighborhood sizes}}}, doi = {{10.1007/s11721-015-0108-8}}, year = {{2015}}, }