@unpublished{16396,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},
}
@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{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{149,
abstract = {In this paper we consider a strategic variant of the online facility location problem. Given is a graph in which each node serves two roles: it is a strategic client stating requests as well as a potential location for a facility. In each time step one client states a request which induces private costs equal to the distance to the closest facility. Before serving, the clients may collectively decide to open new facilities, sharing the corresponding price. Instead of optimizing the global costs, each client acts selfishly. The prices of new facilities vary between nodes and also change over time, but are always bounded by some fixed value α. Both the requests as well as the facility prices are given by an online sequence and are not known in advance.We characterize the optimal strategies of the clients and analyze their overall performance in comparison to a centralized offline solution. If all players optimize their own competitiveness, the global performance of the system is O(√α⋅α) times worse than the offline optimum. A restriction to a natural subclass of strategies improves this result to O(α). We also show that for fixed facility costs, we can find strategies such that this bound further improves to O(√α).},
author = {Drees, Maximilian and Feldkord, Björn and Skopalik, Alexander},
booktitle = {Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA)},
pages = {593----607},
title = {{Strategic Online Facility Location}},
doi = {10.1007/978-3-319-48749-6_43},
year = {2016},
}
@proceedings{163,
editor = {Dressler, Falko and Meyer auf der Heide, Friedhelm},
location = {Paderborn, Germany},
publisher = {ACM},
title = {{Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc)}},
doi = {10.1145/2942358},
year = {2016},
}
@inproceedings{207,
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 series = {LNCS}},
author = {Mäcker, Alexander and Malatyali, Manuel and Meyer auf der Heide, Friedhelm and Riechers, Sören},
booktitle = {Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA)},
pages = {578----592},
title = {{Cost-efficient Scheduling on Machines from the Cloud}},
doi = {10.1007/978-3-319-48749-6_42},
year = {2016},
}
@misc{187,
booktitle = {Transactions on Parallel Computing (TOPC)},
editor = {Meyer auf der Heide, Friedhelm},
number = {1},
pages = {1},
title = {{Introduction to the Special Issue on SPAA 2014}},
doi = {10.1145/2936716},
year = {2016},
}
@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{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{17655,
author = {Polevoy, Gleb and de Weerdt, M.M. and Jonker, C.M.},
booktitle = {Proceedings of the 2016 European Conference on Artificial Intelligence},
keyword = {agents, action, repeated reciprocation, fixed, floating, network, Nash equilibrium, social welfare, price of anarchy, price of stability, convex combination},
pages = {417--425},
title = {{The Game of Reciprocation Habits}},
doi = {10.3233/978-1-61499-672-9-417},
volume = {Volume 285: ECAI 2016},
year = {2016},
}