@article{20255, abstract = {{By compiling macroscopic models we analyze the adaptive behavior in a swarm of autonomous robots generated by a bio-inspired, distributed control algorithm. We developed two macroscopic models by taking two different perspectives: A Stock & Flow model, which is simple to implement and fast to simulate, and a spatially resolved model based on diffusion processes. These two models were compared concerning their prediction quality and their analytical power: One model allowed easy identification of the major feedback loops governing the swarm behavior. The other model allowed analysis of the expected shapes and positions of observable robot clusters. We found a high correlation in the challenges posed by both modeling techniques and we highlighted the inherent problems of inferring emergent macroscopic rules from a microscopic description of swarm behavior.}}, author = {{Schmickl, Thomas and Hamann, Heiko and Wörn, Heinz and Crailsheim, Karl}}, issn = {{0921-8890}}, journal = {{Robotics and Autonomous Systems}}, number = {{9}}, pages = {{913--921}}, title = {{{Two different approaches to a macroscopic model of a bio-inspired robotic swarm}}}, doi = {{10.1016/j.robot.2009.06.002}}, volume = {{6}}, year = {{2009}}, } @inproceedings{20259, author = {{Hamann, Heiko and Troch, Inge and Breitenecker, F.}}, booktitle = {{MATHMOD 2009 - 6th Vienna International Conference on Mathematical Modelling}}, title = {{{Pattern Formation as a Transient Phenomenon in the Nonlinear Dynamics of a Multi-Agent System}}}, year = {{2009}}, } @article{17453, author = {{Meyer auf der Heide, Friedhelm and Rammig, Franz-Josef}}, journal = {{Public Service Review: Science and Technology}}, title = {{{Self-Organisation and Self-Optimization}}}, volume = {{04}}, year = {{2009}}, } @article{19031, author = {{Briest, Patrick}}, issn = {{1611-2776}}, journal = {{it - Information Technology}}, number = {{1}}, pages = {{62--65}}, title = {{{Algorithmische und komplexitätstheoretische Aspekte kombinatorischer Preisoptimierung (Computational Aspects of Combinatorial Pricing Problems)}}}, doi = {{10.1524/itit.2009.0524}}, volume = {{51}}, year = {{2009}}, } @inbook{23744, abstract = {{In a Stackelberg pricing game a leader aims to set prices on a subset of a given collection of items, such as to maximize her revenue from a follower purchasing a feasible subset of the items. We focus on the case of computationally bounded followers who cannot optimize exactly over the range of all feasible subsets, but apply some publicly known algorithm to determine the set of items to purchase. This corresponds to general multi-dimensional pricing assuming that consumers cannot optimize over the full domain of their valuation functions but still aim to act rationally to the best of their ability. We consider two versions of this novel type of Stackelberg pricing games. Assuming that items are weighted objects and the follower seeks to purchase a min-cost selection of objects of some minimum weight (the Min-Knapsack problem) and uses a simple greedy 2-approximate algorithm, we show how an extension of the known single-price algorithm can be used to derive a polynomial-time (2 + ε)-approximation algorithm for the leader’s revenue maximization problem based on so-called near-uniform price assignments. We also prove the problem to be strongly NP-hard. Considering the case that items are subsets of some ground set which the follower seeks to cover (the Set-Cover problem) via a standard primal-dual approach, we prove that near-uniform price assignments fail to yield a good approximation guarantee. However, in the special case of elements with frequency 2 (the Vertex-Cover problem) it turns out that exact revenue maximization can be done in polynomial-time. This stands in sharp contrast to the fact that revenue maximization becomes APX-hard already for elements with frequency 3.}}, author = {{Briest, Patrick and Hoefer, Martin and Gualà, Luciano and Ventre, Carmine}}, booktitle = {{Lecture Notes in Computer Science}}, issn = {{0302-9743}}, title = {{{On Stackelberg Pricing with Computationally Bounded Consumers}}}, doi = {{10.1007/978-3-642-10841-9_6}}, year = {{2009}}, } @inproceedings{18138, abstract = {{Modern companies are nowadays confronted with an increasing demand of multiple products, where they need to perform more flexible every day. Cost-intensive decisions are to be confirmed in short times, in order to minimize risks and secure efficient production programs as well as material flows. Tools for this digital planning via simulation methods are one well established possibility to receive decision support. Nevertheless, the creation of the necessary simulation models is a complicated and error-prone process, where complexity of modeling, validation and verification depends on the used tool and its functionalities. This paper presents implemented concepts for an innovative user support in his tasks of verification and validation of simulation models during the execution of a simulation run. Time-intensive procedures like stopping simulation, parameterization and restarting within the problem analysis are simplified. So the user is able to focus on the real problem solving task.}}, author = {{Laroque, Christoph and Fischer, Matthias and Dangelmaier, Wilhelm}}, booktitle = {{European Simulation and Modelling Conference (ESM 2009)}}, publisher = {{EUROSIS-ETI}}, title = {{{Concepts for Model Verification and Validation during Simulation Runtime}}}, year = {{2009}}, } @inbook{18291, author = {{Suess, Tim and Fischer, Matthias and Huber, Daniel and Laroque, Christoph and Dangelmaier, Wilhelm}}, booktitle = {{Augmented & Virtual Reality in der Produktentstehung}}, pages = {{111----126}}, publisher = {{Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn}}, title = {{{Ein System zur aggregierten Visualisierung verteilter Materialflusssimulationen}}}, volume = {{252}}, year = {{2009}}, } @inproceedings{18346, abstract = {{For a fixed virtual scene (=collection of simplices) S and given observer position p, how many elements of S are weakly visible (i.e. not fully occluded by others) from p? The present work explores the trade-off between query time and preprocessing space for these quantities in 2D: exactly, in the approximate deterministic, and in the probabilistic sense. We deduce the EXISTENCE of an O(m^2/n^2) space data structure for S that, given p and time O(log n), allows to approximate the ratio of occluded segments up to arbitrary constant absolute error; here m denotes the size of the Visibility Graph--which may be quadratic, but typically is just linear in the size n of the scene S. On the other hand, we present a data structure CONSTRUCTIBLE in O(n*log(n)+m^2*polylog(n)/k) preprocessing time and space with similar approximation properties and query time O(k*polylog n), where k