Search Results - "Spieker, Helge"

Predictive Machine Learning of Objective Boundaries for Solving COPs by Spieker, Helge, Gotlieb, Arnaud

“…Solving Constraint Optimization Problems (COPs) can be dramatically simplified by boundary estimation, that is providing tight boundaries of cost functions. By…”
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Adaptive metamorphic testing with contextual bandits by Spieker, Helge, Gotlieb, Arnaud

“…•Adaptive Metamorphic Testing (AMT) is an iterative variant of metamorphic testing.•AMT repeatedly chooses metamorphic relations to generate follow-up test…”
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Mutation‐Guided Metamorphic Testing of Optimality in AI Planning by Mazouni, Quentin, Gotlieb, Arnaud, Spieker, Helge, Acher, Mathieu, Combemale, Benoit

“…ABSTRACT Autonomous systems such as space‐ or underwater‐exploration robots or elderly people assistance robots often include an artificial intelligence (AI)…”
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Detecting Intentional AIS Shutdown in Open Sea Maritime Surveillance Using Self-Supervised Deep Learning by Bernabe, Pierre, Gotlieb, Arnaud, Legeard, Bruno, Marijan, Dusica, Sem-Jacobsen, Frank Olaf, Spieker, Helge

“…In maritime traffic surveillance, detecting illegal activities, such as illegal fishing or transshipment of illicit products is a crucial task of the coastal…”
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Query-driven Qualitative Constraint Acquisition by Belaid, Mohamed-Bachir, Belmecheri, Nassim, Gotlieb, Arnaud, Lazaar, Nadjib, Spieker, Helge

“…Many planning, scheduling or multi-dimensional packing problems involve the design of subtle logical combinations of temporal or spatial constraints. Recently,…”
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Learning input-aware performance models of configurable systems: An empirical evaluation by Lesoil, Luc, Spieker, Helge, Gotlieb, Arnaud, Acher, Mathieu, Temple, Paul, Blouin, Arnaud, Jézéquel, Jean-Marc

“…Modern software-based systems are highly configurable and come with a number of configuration options that impact the performance of the systems. However,…”
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Multi-stage evolution of single- and multi-objective MCLP by Spieker, Helge, Hagg, Alexander, Gaier, Adam, Meilinger, Stefanie, Asteroth, Alexander

“…Maximal covering location problems have efficiently been solved using evolutionary computation. The multi-stage placement of charging stations for electric…”
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Multi-stage evolution of single- and multi-objective MCLP: Successive placement of charging stations by Spieker, Helge, Hagg, Alexander, Gaier, Adam, Meilinger, Stefanie, Asteroth, Alexander

“…Maximal covering location problems have efficiently been solved using evolutionary computation. The multi-stage placement of charging stations for electric…”
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Enhancing RL Safety with Counterfactual LLM Reasoning by Gross, Dennis, Spieker, Helge

“…Reinforcement learning (RL) policies may exhibit unsafe behavior and are hard to explain. We use counterfactual large language model reasoning to enhance RL…”
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Safety-Oriented Pruning and Interpretation of Reinforcement Learning Policies by Gross, Dennis, Spieker, Helge

“…Pruning neural networks (NNs) can streamline them but risks removing vital parameters from safe reinforcement learning (RL) policies. We introduce an…”
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A fine-grained data set and analysis of tangling in bug fixing commits by Herbold, Steffen, Trautsch, Alexander, Ledel, Benjamin, Aghamohammadi, Alireza, Ghaleb, Taher A., Chahal, Kuljit Kaur, Bossenmaier, Tim, Nagaria, Bhaveet, Makedonski, Philip, Ahmadabadi, Matin Nili, Szabados, Kristof, Spieker, Helge, Madeja, Matej, Hoy, Nathaniel, Lenarduzzi, Valentina, Wang, Shangwen, Rodríguez-Pérez, Gema, Colomo-Palacios, Ricardo, Verdecchia, Roberto, Singh, Paramvir, Qin, Yihao, Chakroborti, Debasish, Davis, Willard, Walunj, Vijay, Wu, Hongjun, Marcilio, Diego, Alam, Omar, Aldaeej, Abdullah, Amit, Idan, Turhan, Burak, Eismann, Simon, Wickert, Anna-Katharina, Malavolta, Ivano, Sulír, Matúš, Fard, Fatemeh, Henley, Austin Z., Kourtzanidis, Stratos, Tuzun, Eray, Treude, Christoph, Shamasbi, Simin Maleki, Pashchenko, Ivan, Wyrich, Marvin, Davis, James, Serebrenik, Alexander, Albrecht, Ella, Aktas, Ethem Utku, Strüber, Daniel, Erbel, Johannes

“…Context Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they…”
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Constraint-Guided Reinforcement Learning: Augmenting the Agent-Environment-Interaction by Spieker, Helge

“…Reinforcement Learning (RL) agents have great successes in solving tasks with large observation and action spaces from limited feedback. Still, training the…”
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Constraint-Guided Reinforcement Learning: Augmenting the Agent-Environment-Interaction by Spieker, Helge

“…Reinforcement Learning (RL) agents have great successes in solving tasks with large observation and action spaces from limited feedback. Still, training the…”
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Probabilistic Model Checking of Stochastic Reinforcement Learning Policies by Gross, Dennis, Spieker, Helge

“…We introduce a method to verify stochastic reinforcement learning (RL) policies. This approach is compatible with any RL algorithm as long as the algorithm and…”
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Predictive Machine Learning of Objective Boundaries for Solving COPs by Spieker, Helge, Gotlieb, Arnaud

“…AI 2021, 2, 527-551 Solving Constraint Optimization Problems (COPs) can be dramatically simplified by boundary estimation, that is, providing tight boundaries…”
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Summary of: Adaptive Metamorphic Testing with Contextual Bandits by Spieker, Helge, Gotlieb, Arnaud

“…Metamorphic Testing (MT) is a software testing paradigm that aims at using user-specified properties of a program under test to either check its expected…”
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Learning Objective Boundaries for Constraint Optimization Problems by Spieker, Helge, Gotlieb, Arnaud

“…In: Nicosia G. et al. (eds) Machine Learning, Optimization, and Data Science. LOD 2020. Lecture Notes in Computer Science, vol 12566. Springer, Cham Constraint…”
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Constraint-Guided Test Execution Scheduling: An Experience Report at ABB Robotics by Gotlieb, Arnaud, Mossige, Morten, Spieker, Helge

“…Automated test execution scheduling is crucial in modern software development environments, where components are frequently updated with changes that impact…”
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Adaptive Metamorphic Testing with Contextual Bandits by Spieker, Helge, Gotlieb, Arnaud

“…Journal of Systems and Software (JSS) Vol. 165 (2020) 110574 Metamorphic Testing is a software testing paradigm which aims at using necessary properties of a…”
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Efficient Milling Quality Prediction with Explainable Machine Learning by Gross, Dennis, Spieker, Helge, Gotlieb, Arnaud, Knoblauch, Ricardo, Elmansori, Mohamed

“…This paper presents an explainable machine learning (ML) approach for predicting surface roughness in milling. Utilizing a dataset from milling aluminum alloy…”
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