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Jiawen Kong, "Learning Class-Imbalanced Problems from the Perspective of Data Intrinsic Characteristics", Leiden University, 2023.

Abstract

The class-imbalance problem is a challenging classification task and is frequently encountered in real-world applications. Various techniques have been developed to improve the imbalanced classification performance theoretically and practically. Apart from developing new approaches, researchers also address the importance of understanding the data itself, which will provide more insight into what actually hinders the imbalanced classification per...



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Sibghat Ullah, "Model-assisted robust optimization for continuous black-box problems", Leiden University, 2023.

Abstract

While solving real-world optimization problems, e.g., in the area of automotive engineering, building construction, and steel production, the issue of uncertainty and noise is frequently-encountered. Common sources of uncertainty and noise include search/decision variables (that describe the system to be optimized), the environmental variables or operating conditions the system is subject to, the evaluation of the (physical) system (or model of t...



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Margarita Veshchezerova, Mikhail Somov, David Bertsche, Steffen Limmer, Sebastian Schmitt, Michael Perelshtein, Ayush Joshi, "A Hybrid Quantum-Classical Approach to the Electric Mobility Problem", IEEE Quantum Week 2023, 2023.

Abstract

We suggest a hybrid quantum-classical routine for the NP-hard Electric Vehicle Fleet Charging and Allocation Problem. The original formulation is a Mixed Integer Linear Program with continuous variables and inequality constraints. To separate inequality constraints that are difficult for quantum routines we use a decomposition in master and pricing problems: the former targets the assignment of vehicles to reservations and the latter suggests veh...



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Felix Lanfermann, "Concept Identification for Complex Data Sets", Bielefeld University, 2023.

Abstract

Large and complex data sets play an essential role in many engineering and computer science applications. Revealing structures within data sets, such as groups of similar data samples or correlations between feature values, is often desirable. But generating such insights is far from trivial. The field of concept identification targets to automatically find groups of data samples in large and complex data sets which share common properties. Such ...



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Frank Joublin, Antonello Ceravola, Pavel Smirnov, Felix Ocker, Jörg Deigmöller, Anna Belardinelli, Chao Wang, Daniel Tanneberg, Stephan Hasler, Michael Gienger, "CoPal: Planning Robot Actions using Large Language Models", Arxiv, no. arXiv:2310.07263, 2023.

Abstract

Recent advances in the field of pretrained Large Language Models (LLM) made commonsense knowledge available "out of the box" for a vast range of scenarios including content generation, customer service, and voice assistants. The release of GPT-3.5 (known as ChatGPT) opened prospectives for building highly contextualizable conversational agents, capable to hold a dialog and reflect about various situations as well as on behalf of different social ...



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Ahmed Sadik, Sebastian Brulin, Markus Olhofer, "CODING BY DESIGN: GPT-4 EMPOWERS AGILE MODEL DRIVEN DEVELOPMENT", arxiv, 2023.

Abstract

Generating code from a natural language using Large Language Models (LLMs) such as ChatGPT, seems groundbreaking. Yet, with more extensive use, it's evident that this approach has its own limitations. The inherent ambiguity of natural language presents challenges for complex software designs. Accordingly, our research offers an Agile Model-Driven Development (MDD) approach that enhances code auto-generation using OpenAI's GPT-4. Our work emphasiz...



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Sebastian Brulin, Mariusz Bujny, Tim Puphal, Stefan Menzel, "Data-driven Evolutionary Optimization of eVTOL Design Concepts based on Multi-agent Simulations", American Institute of Aeronautics and Astronautics SciTech Forum, 2023.

Abstract

Electric vertical take-off and landing (eVTOL) aircraft design concepts are currently developed by many companies and research consortia. A relevant topic in the design process is very early on the optimal vehicle specification to maximize the operational profit of the fleet. This paper proposes a novel method that combines open vehicle design concepts with an Evolutionary Algorithm optimization scheme to find the optimal aircraft specifications,...



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Tim Puphal, "Improved Behavior Planning with Cooperation and Group-awareness", IEEE International Conference on Intelligent Transportation Systems, 2023.

Abstract

Invited talk about Risk Maps planning in the workshop "Probabilistic Prediction and Comprehensible Motion Planning for Automated Vehicles – Approaches and Benchmarking" at the International Conference on Intelligent Transportation Systems (ITSC 2023). Recent works on intelligent driving by improved behavior planning with cooperation and group-awareness was presented. You can find more information about the workshop here: https://kit-mrt.githu...



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Hua-Ming Huang, Elena Raponi, Fabian Duddeck, Stefan Menzel, Mariusz Bujny, "Topology Optimization of Periodic Structures for Crash and Static Load Cases using the Evolutionary Level Set Method", Optimization and Engineering, 2023.

Abstract

Assembly complexity and manufacturing costs of engineering structures can be significantly reduced by using periodic mechanical components, which are defined by combining multiple identical unit cells into a global topology. Additionally, the superior energy-absorbing properties of lattice-based periodic structures can potentially enhance the overall performance in crash-related applications. Recent research developments in periodic topology opti...



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Nico Steinhardt, Raphael Wenzel, Malte Probst , Markus Amann, "Lateral Model Predictive Control for Autonomous Vehicle Prototypes", IFAC World Congress 2023, 2023.

Abstract

This paper shows a (lateral) Model Predictive Control (MPC) implementation on an Autonomous Driving (AD) prototype. Rapid prototyping and testing of AD functions in a realistic environment is a crucial step to understanding the advantages and shortcomings of algorithms in research and development of AD. Prototype vehicles show a specific set of requirements which differ from the control deployed in the final products. Vehicles are equipped with s...



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