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Tobias Rodemann and Kai Kitamura , "Simulation-based Design and Evaluation of a Smart Energy Manager", Computer Aided Systems Theory – EUROCAST 2019, Springer, LNCS, LNAI, LNBI, vol. 12014, 2020.
AbstractIn this work we describe an advanced development environment for energy management systems using a combination of a Modelica-based simulation tool for multi-physics systems and a controller implemented in the Python scripting language, exchanging information via the FMI (Functional Mockup Interface) standard. As an example, we present the development of a simple but robust Electric Vehicle (EV) charging controller for a smart home with a Photo Vo...
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Hao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao , "Towards Novel Meta-heuristic Algorithms for Dynamic Capacitated Arc Routing Problems", Parallel Problem Solving from Nature (PPSN), 2020.
AbstractThe Capacitated Arc Routing Problem (CARP) is an abstraction for typical real world applications, like waste collection, winter gritting and mail delivery, to allow the development of efficient optimization algorithms. Most research work focuses on the static CARP, where all information in the problem remains unchanged over time. However, in the real world, dynamic changes may happen when the vehicles are in service, requiring routes to be resche...
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Florian Schulze , "Development of a Simulation Framework for Deep Reinforcement Learning in the Context of ConceptFormation", Ilmenau University of technology, 2020.
AbstractAs modern robotics finds its way more and more into the human society, the need for a natural interaction with artificial agents increases. However, the human world is very complex. The sheer complexity of human interaction cannot be reached with standard robotic systems. These are often based on a finite set of rules. Anyway, finite rules make communication with robots uninteresting and unnatural to humans, as humans tend to find the limita...
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Takahiro Ishihara and Steffen Limmer , "Optimizing the Hyperparameters of a Mixed Integer Linear Programming Solver to Speed Up Electric Vehicle Charging Control", Applications of Evolutionary Computation 2020, pp. 37-53, 2020.
AbstractOptimization of charging profiles for controlled charging of electric vehicles is commonly done via mixed integer linear programming. The runtime of the optimization can represent an issue for the practical use. However, by tuning the parameter setting of the employed solver, it is possible to speed up the optimization process. The present work evaluates two popular hyperparameter tuning tools – irace and SMAC – for the optimization of parameters...
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Hesham Elsayed, Mayra Donaji Barrera Machuca, Christian Schaarschmidt, Karola Marky, Florian Müller, Jan Riemann, Andrii Matviienko, Martin Schmitz, Martin Weigel, Max Mühlhäuser , "VRSketchPen: Unconstrained Haptic Assistance for Sketching in Virtual 3D Environments", Proceedings of the 26th ACM Symposium on Virtual Reality Software and Technology, 2020.
AbstractAccurate sketching in virtual 3D environments is challenging due to aspects like limited depth perception or the absence of physical support. To address this issue, we propose VRSketchPen - a pen that uses two haptic modalities to support virtual sketching without constraining user actions: (1) pneumatic force feedback to simulate the contact pressure of the pen against virtual surfaces and (2) vibrotactile feedback to mimic textures while moving...
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Malte Probst , "Harmless Overfitting: Using Denoising Autoencoders in Estimation of Distribution Algorithms", Journal of Machine Learning Research, vol. 21, no. 78, pp. 1-31, 2020.
AbstractEstimation of Distribution Algorithms (EDAs) are metaheuristics where learning a model and sampling new solutions replaces the variation operators recombination and mutation used in standard Genetic Algorithms. The choice of these models as well as the corresponding training processes are subject to the bias/variance tradeoff, also known as under- and overfitting: simple models cannot capture complex interactions between problem variables, w...
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Christian Limberg, Heiko Wersing, Helge Ritter, Jan Philip Goepfert , "Prototype-Based Online Learning on Homogeneously Labeled Streaming Data", International Conference on Artificial Neural Networks (ICANN), 2020.
AbstractAlgorithms in machine learning commonly require training data to be independent and identically distributed. This assumption is not always valid, e. g. in online learning, when data becomes available in homogeneously labeled blocks, which can severely impede especially instance-based learning algorithms. In this work, we analyze and visu- alize this issue, and we propose and evaluate strategies for Learning Vector Quantization to compensate...
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Mariusz Bujny , "Level Set Topology Optimization for Crashworthiness using Evolutionary Algorithms and Machine Learning", Technical University of Munich, 2020.
AbstractDue to the rising complexity of the development process in the automotive industry, it becomes very difficult to rely solely on the engineering intuition when designing car components. At the same time, the use of simulation methods in industry is now a common standard, leading to a transformation of the traditional design process towards the model-based concept. As a consequence, automatic generation of mechanical structures based on optimizatio...
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Christian Limberg, Heiko Wersing, Helge Ritter , "Accuracy Estimation for an Incrementally Learning Cooperative Inventory Assistant Robot", International Conference on Neural Information Processing ICONIP 2020, 2020.
AbstractInteractive teaching from a human can be applied to extend the knowledge of a service robot according to novel task demands. This is particularly attractive if it is either inefficient or not feasible to pre-train all relevant object knowledge beforehand. Like in a normal human teacher and student situation it is then vital to estimate the learning progress of the robot in order to judge its competence in carrying out the desired task. Whi...
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Newton Masinde and Kalman György Graffi , "Peer-to-Peer based Social Networks: A Comprehensive Survey", Springer SN Computer Science, vol. 1, no. 299, pp. 1-51, 2020.
AbstractOnline social networks, such as Facebook and Twitter, are a growing phenomenon in today’s world, with various platforms providing capabilities for individuals to collaborate through messaging and chatting as well as sharing of content such as videos and photos. Most, if not all, of these platforms are based on centralized computing systems meaning that the control and management of the systems lies in the hand of one provider, which must be trust...
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