[{"publisher":"Springer","date_updated":"2023-10-16T12:54:29Z","date_created":"2023-08-04T07:21:17Z","author":[{"last_name":"Aspar","full_name":"Aspar, Pelin","first_name":"Pelin"},{"last_name":"Kerschke","full_name":"Kerschke, Pascal","first_name":"Pascal"},{"first_name":"Vera","full_name":"Steinhoff, Vera","last_name":"Steinhoff"},{"full_name":"Trautmann, Heike","id":"100740","orcid":"0000-0002-9788-8282","last_name":"Trautmann","first_name":"Heike"},{"first_name":"Christian","last_name":"Grimme","full_name":"Grimme, Christian"}],"title":"Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization","doi":"10.1007/978-3-030-72062-9_25","year":"2021","place":"Heidelberg, Berlin","citation":{"short":"P. Aspar, P. Kerschke, V. Steinhoff, H. Trautmann, C. Grimme, in: H. et al. Ishibuchi (Ed.), Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings, Springer, Heidelberg, Berlin, 2021, pp. 311–322.","mla":"Aspar, Pelin, et al. “Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization.” <i>Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings</i>, edited by H. et al. Ishibuchi, Springer, 2021, pp. 311–322, doi:<a href=\"https://doi.org/10.1007/978-3-030-72062-9_25\">10.1007/978-3-030-72062-9_25</a>.","bibtex":"@inproceedings{Aspar_Kerschke_Steinhoff_Trautmann_Grimme_2021, place={Heidelberg, Berlin}, title={Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization}, DOI={<a href=\"https://doi.org/10.1007/978-3-030-72062-9_25\">10.1007/978-3-030-72062-9_25</a>}, booktitle={Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings}, publisher={Springer}, author={Aspar, Pelin and Kerschke, Pascal and Steinhoff, Vera and Trautmann, Heike and Grimme, Christian}, editor={et al. Ishibuchi, H.}, year={2021}, pages={311–322} }","apa":"Aspar, P., Kerschke, P., Steinhoff, V., Trautmann, H., &#38; Grimme, C. (2021). Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization. In H. et al. Ishibuchi (Ed.), <i>Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings</i> (pp. 311–322). Springer. <a href=\"https://doi.org/10.1007/978-3-030-72062-9_25\">https://doi.org/10.1007/978-3-030-72062-9_25</a>","ama":"Aspar P, Kerschke P, Steinhoff V, Trautmann H, Grimme C. Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization. In: et al. Ishibuchi H, ed. <i>Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings</i>. Springer; 2021:311–322. doi:<a href=\"https://doi.org/10.1007/978-3-030-72062-9_25\">10.1007/978-3-030-72062-9_25</a>","ieee":"P. Aspar, P. Kerschke, V. Steinhoff, H. Trautmann, and C. Grimme, “Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization,” in <i>Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings</i>, 2021, pp. 311–322, doi: <a href=\"https://doi.org/10.1007/978-3-030-72062-9_25\">10.1007/978-3-030-72062-9_25</a>.","chicago":"Aspar, Pelin, Pascal Kerschke, Vera Steinhoff, Heike Trautmann, and Christian Grimme. “Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization.” In <i>Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings</i>, edited by H. et al. Ishibuchi, 311–322. Heidelberg, Berlin: Springer, 2021. <a href=\"https://doi.org/10.1007/978-3-030-72062-9_25\">https://doi.org/10.1007/978-3-030-72062-9_25</a>."},"page":"311–322","_id":"46311","user_id":"15504","department":[{"_id":"34"},{"_id":"819"}],"language":[{"iso":"eng"}],"type":"conference","publication":"Evolutionary Multi-Criterion Optimization: 11$^th$ International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings","abstract":[{"lang":"eng","text":"In this work we examine the inner mechanisms of the recently developed sophisticated local search procedure SOMOGSA. This method solves multimodal single-objective continuous optimization problems by first expanding the problem with an additional objective (e.g., a sphere function) to the bi-objective space, and subsequently exploiting local structures and ridges of the resulting landscapes. Our study particularly focusses on the sensitivity of this multiobjectivization approach w.r.t. (i) the parametrization of the artificial second objective, as well as (ii) the position of the initial starting points in the search space.\r\n\r\nAs SOMOGSA is a modular framework for encapsulating local search, we integrate Gradient and Nelder-Mead local search (as optimizers in the respective module) and compare the performance of the resulting hybrid local search to their original single-objective counterparts. We show that the SOMOGSA framework can significantly boost local search by multiobjectivization. Combined with more sophisticated local search and metaheuristics this may help in solving highly multimodal optimization problems in future."}],"editor":[{"first_name":"H.","full_name":"et al. Ishibuchi, H.","last_name":"et al. Ishibuchi"}],"status":"public"},{"language":[{"iso":"eng"}],"_id":"46317","department":[{"_id":"34"},{"_id":"819"}],"user_id":"15504","abstract":[{"lang":"eng","text":"One of the most significant recent technological developments concerns the development and implementation of ‘intelligent machines’ that draw on recent advances in artificial intelligence (AI) and robotics. However, there are growing tensions between human freedoms and machine controls. This article reports the findings of a workshop that investigated the application of the principles of human freedom throughout intelligent machine development and use. Forty IS researchers from ten different countries discussed four contemporary AI and humanity issues and the most relevant IS domain challenges. This article summarizes their experiences and opinions regarding four AI and humanity themes: Crime & conflict, Jobs, Attention, and Wellbeing. The outcomes of the workshop discussions identify three attributes of humanity that need preservation: a critique of the design and application of AI, and the intelligent machines it can create; human involvement in the loop of intelligent machine decision-making processes; and the ability to interpret and explain intelligent machine decision-making processes. The article provides an agenda for future AI and humanity research."}],"status":"public","publication":"International Journal of Information Management","type":"journal_article","title":"What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective","doi":"10.1016/j.ijinfomgt.2021.102311","date_updated":"2023-10-16T12:58:02Z","volume":58,"date_created":"2023-08-04T07:27:14Z","author":[{"last_name":"Coombs","full_name":"Coombs, Crispin","first_name":"Crispin"},{"last_name":"Stacey","full_name":"Stacey, Patrick","first_name":"Patrick"},{"first_name":"Peter","last_name":"Kawalek","full_name":"Kawalek, Peter"},{"full_name":"Simeonova, Boyka","last_name":"Simeonova","first_name":"Boyka"},{"last_name":"Becker","full_name":"Becker, Jörg","first_name":"Jörg"},{"first_name":"Katrin","last_name":"Bergener","full_name":"Bergener, Katrin"},{"first_name":"João Álvaro","full_name":"Carvalho, João Álvaro","last_name":"Carvalho"},{"last_name":"Fantinato","full_name":"Fantinato, Marcelo","first_name":"Marcelo"},{"first_name":"Niels F.","last_name":"Garmann-Johnsen","full_name":"Garmann-Johnsen, Niels F."},{"first_name":"Christian","last_name":"Grimme","full_name":"Grimme, Christian"},{"last_name":"Stein","full_name":"Stein, Armin","first_name":"Armin"},{"orcid":"0000-0002-9788-8282","last_name":"Trautmann","id":"100740","full_name":"Trautmann, Heike","first_name":"Heike"}],"year":"2021","intvolume":"        58","citation":{"apa":"Coombs, C., Stacey, P., Kawalek, P., Simeonova, B., Becker, J., Bergener, K., Carvalho, J. Á., Fantinato, M., Garmann-Johnsen, N. F., Grimme, C., Stein, A., &#38; Trautmann, H. (2021). What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective. <i>International Journal of Information Management</i>, <i>58</i>. <a href=\"https://doi.org/10.1016/j.ijinfomgt.2021.102311\">https://doi.org/10.1016/j.ijinfomgt.2021.102311</a>","mla":"Coombs, Crispin, et al. “What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective.” <i>International Journal of Information Management</i>, vol. 58, 2021, doi:<a href=\"https://doi.org/10.1016/j.ijinfomgt.2021.102311\">10.1016/j.ijinfomgt.2021.102311</a>.","bibtex":"@article{Coombs_Stacey_Kawalek_Simeonova_Becker_Bergener_Carvalho_Fantinato_Garmann-Johnsen_Grimme_et al._2021, title={What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective}, volume={58}, DOI={<a href=\"https://doi.org/10.1016/j.ijinfomgt.2021.102311\">10.1016/j.ijinfomgt.2021.102311</a>}, journal={International Journal of Information Management}, author={Coombs, Crispin and Stacey, Patrick and Kawalek, Peter and Simeonova, Boyka and Becker, Jörg and Bergener, Katrin and Carvalho, João Álvaro and Fantinato, Marcelo and Garmann-Johnsen, Niels F. and Grimme, Christian and et al.}, year={2021} }","short":"C. Coombs, P. Stacey, P. Kawalek, B. Simeonova, J. Becker, K. Bergener, J.Á. Carvalho, M. Fantinato, N.F. Garmann-Johnsen, C. Grimme, A. Stein, H. Trautmann, International Journal of Information Management 58 (2021).","ieee":"C. Coombs <i>et al.</i>, “What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective,” <i>International Journal of Information Management</i>, vol. 58, 2021, doi: <a href=\"https://doi.org/10.1016/j.ijinfomgt.2021.102311\">10.1016/j.ijinfomgt.2021.102311</a>.","chicago":"Coombs, Crispin, Patrick Stacey, Peter Kawalek, Boyka Simeonova, Jörg Becker, Katrin Bergener, João Álvaro Carvalho, et al. “What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective.” <i>International Journal of Information Management</i> 58 (2021). <a href=\"https://doi.org/10.1016/j.ijinfomgt.2021.102311\">https://doi.org/10.1016/j.ijinfomgt.2021.102311</a>.","ama":"Coombs C, Stacey P, Kawalek P, et al. What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective. <i>International Journal of Information Management</i>. 2021;58. doi:<a href=\"https://doi.org/10.1016/j.ijinfomgt.2021.102311\">10.1016/j.ijinfomgt.2021.102311</a>"}},{"language":[{"iso":"ger"}],"department":[{"_id":"563"}],"user_id":"45402","_id":"21272","status":"public","editor":[{"full_name":"Hartmann, Ernst A.","last_name":"Hartmann","first_name":"Ernst A."}],"publication":"Digitalisisierung souverän gestalten","type":"conference","title":"Forschungsfelder für Künstliche Intelligenz in der strategischen Produktplanung","date_created":"2021-02-24T13:07:33Z","author":[{"last_name":"Ködding","id":"45402","full_name":"Ködding, Patrick","first_name":"Patrick"},{"last_name":"Dumitrescu","id":"16190","full_name":"Dumitrescu, Roman","first_name":"Roman"}],"date_updated":"2023-10-06T12:32:24Z","publisher":"Springer Vieweg","page":"pp. 59-73","citation":{"mla":"Ködding, Patrick, and Roman Dumitrescu. “Forschungsfelder für Künstliche Intelligenz in der strategischen Produktplanung.” <i>Digitalisisierung souverän gestalten</i>, edited by Ernst A. Hartmann, Springer Vieweg, 2021, pp. 59–73.","short":"P. Ködding, R. Dumitrescu, in: E.A. Hartmann (Ed.), Digitalisisierung souverän gestalten, Springer Vieweg, Berlin, Heidelberg, 2021, pp. 59–73.","bibtex":"@inproceedings{Ködding_Dumitrescu_2021, place={Berlin, Heidelberg}, title={Forschungsfelder für Künstliche Intelligenz in der strategischen Produktplanung}, booktitle={Digitalisisierung souverän gestalten}, publisher={Springer Vieweg}, author={Ködding, Patrick and Dumitrescu, Roman}, editor={Hartmann, Ernst A.}, year={2021}, pages={59–73} }","apa":"Ködding, P., &#38; Dumitrescu, R. (2021). Forschungsfelder für Künstliche Intelligenz in der strategischen Produktplanung. In E. A. Hartmann (Ed.), <i>Digitalisisierung souverän gestalten</i> (pp. 59–73). Springer Vieweg.","ama":"Ködding P, Dumitrescu R. Forschungsfelder für Künstliche Intelligenz in der strategischen Produktplanung. In: Hartmann EA, ed. <i>Digitalisisierung souverän gestalten</i>. Springer Vieweg; 2021:59-73.","ieee":"P. Ködding and R. Dumitrescu, “Forschungsfelder für Künstliche Intelligenz in der strategischen Produktplanung,” in <i>Digitalisisierung souverän gestalten</i>, 2021, pp. 59–73.","chicago":"Ködding, Patrick, and Roman Dumitrescu. “Forschungsfelder für Künstliche Intelligenz in der strategischen Produktplanung.” In <i>Digitalisisierung souverän gestalten</i>, edited by Ernst A. Hartmann, 59–73. Berlin, Heidelberg: Springer Vieweg, 2021."},"place":"Berlin, Heidelberg","year":"2021","publication_status":"published"},{"_id":"48286","user_id":"15504","department":[{"_id":"34"},{"_id":"820"}],"language":[{"iso":"eng"}],"type":"conference","publication":"Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing","status":"public","date_updated":"2023-10-19T12:04:40Z","publisher":"Association for Computational Linguistics","date_created":"2023-10-19T08:21:43Z","author":[{"last_name":"Habernal","id":"101881","full_name":"Habernal, Ivan","first_name":"Ivan"}],"title":"When differential privacy meets NLP: The devil is in the detail","doi":"10.18653/v1/2021.emnlp-main.114","publication_status":"published","year":"2021","citation":{"ama":"Habernal I. When differential privacy meets NLP: The devil is in the detail. In: <i>Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing</i>. Association for Computational Linguistics; 2021. doi:<a href=\"https://doi.org/10.18653/v1/2021.emnlp-main.114\">10.18653/v1/2021.emnlp-main.114</a>","chicago":"Habernal, Ivan. “When Differential Privacy Meets NLP: The Devil Is in the Detail.” In <i>Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing</i>. Association for Computational Linguistics, 2021. <a href=\"https://doi.org/10.18653/v1/2021.emnlp-main.114\">https://doi.org/10.18653/v1/2021.emnlp-main.114</a>.","ieee":"I. Habernal, “When differential privacy meets NLP: The devil is in the detail,” 2021, doi: <a href=\"https://doi.org/10.18653/v1/2021.emnlp-main.114\">10.18653/v1/2021.emnlp-main.114</a>.","mla":"Habernal, Ivan. “When Differential Privacy Meets NLP: The Devil Is in the Detail.” <i>Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing</i>, Association for Computational Linguistics, 2021, doi:<a href=\"https://doi.org/10.18653/v1/2021.emnlp-main.114\">10.18653/v1/2021.emnlp-main.114</a>.","short":"I. Habernal, in: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2021.","bibtex":"@inproceedings{Habernal_2021, title={When differential privacy meets NLP: The devil is in the detail}, DOI={<a href=\"https://doi.org/10.18653/v1/2021.emnlp-main.114\">10.18653/v1/2021.emnlp-main.114</a>}, booktitle={Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing}, publisher={Association for Computational Linguistics}, author={Habernal, Ivan}, year={2021} }","apa":"Habernal, I. (2021). When differential privacy meets NLP: The devil is in the detail. <i>Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing</i>. <a href=\"https://doi.org/10.18653/v1/2021.emnlp-main.114\">https://doi.org/10.18653/v1/2021.emnlp-main.114</a>"}},{"quality_controlled":"1","issue":"3","year":"2021","date_created":"2021-09-14T20:52:57Z","title":"Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems","publication":"IEEE Transactions on Cognitive and Developmental Systems","abstract":[{"text":"One objective of current research in explainable intelligent systems is to implement social aspects in order to increase the relevance of explanations. In this paper, we argue that a novel conceptual framework is needed to overcome shortcomings of existing AI systems with little attention to processes of interaction and learning. Drawing from research in interaction and development, we first outline the novel conceptual framework that pushes the design of AI systems toward true interactivity with an emphasis on the role of the partner and social relevance. We propose that AI systems will be able to provide a meaningful and relevant explanation only if the process of explaining is extended to active contribution of both partners that brings about dynamics that is modulated by different levels of analysis. Accordingly, our conceptual framework comprises monitoring and scaffolding as key concepts and claims that the process of explaining is not only modulated by the interaction between explainee and explainer but is embedded into a larger social context in which conventionalized and routinized behaviors are established. We discuss our conceptual framework in relation to the established objectives of transparency and autonomy that are raised for the design of explainable AI systems currently.","lang":"eng"}],"file":[{"file_name":"2020-12-01_explainability_final_version.pdf","file_id":"49081","access_level":"open_access","file_size":626217,"creator":"haebumb","date_created":"2023-11-20T16:33:51Z","date_updated":"2023-11-20T16:33:51Z","relation":"main_file","content_type":"application/pdf"}],"keyword":["Explainability","process ofexplaining andunderstanding","explainable artificial systems"],"ddc":["300"],"language":[{"iso":"eng"}],"has_accepted_license":"1","publication_identifier":{"issn":["2379-8920","2379-8939"]},"publication_status":"published","page":"717-728","intvolume":"        13","citation":{"apa":"Rohlfing, K. J., Cimiano, P., Scharlau, I., Matzner, T., Buhl, H. M., Buschmeier, H., Esposito, E., Grimminger, A., Hammer, B., Haeb-Umbach, R., Horwath, I., Hüllermeier, E., Kern, F., Kopp, S., Thommes, K., Ngonga Ngomo, A.-C., Schulte, C., Wachsmuth, H., Wagner, P., &#38; Wrede, B. (2021). Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems. <i>IEEE Transactions on Cognitive and Developmental Systems</i>, <i>13</i>(3), 717–728. <a href=\"https://doi.org/10.1109/tcds.2020.3044366\">https://doi.org/10.1109/tcds.2020.3044366</a>","mla":"Rohlfing, Katharina J., et al. “Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems.” <i>IEEE Transactions on Cognitive and Developmental Systems</i>, vol. 13, no. 3, 2021, pp. 717–28, doi:<a href=\"https://doi.org/10.1109/tcds.2020.3044366\">10.1109/tcds.2020.3044366</a>.","short":"K.J. Rohlfing, P. Cimiano, I. Scharlau, T. Matzner, H.M. Buhl, H. Buschmeier, E. Esposito, A. Grimminger, B. Hammer, R. Haeb-Umbach, I. Horwath, E. Hüllermeier, F. Kern, S. Kopp, K. Thommes, A.-C. Ngonga Ngomo, C. Schulte, H. Wachsmuth, P. Wagner, B. Wrede, IEEE Transactions on Cognitive and Developmental Systems 13 (2021) 717–728.","bibtex":"@article{Rohlfing_Cimiano_Scharlau_Matzner_Buhl_Buschmeier_Esposito_Grimminger_Hammer_Haeb-Umbach_et al._2021, title={Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems}, volume={13}, DOI={<a href=\"https://doi.org/10.1109/tcds.2020.3044366\">10.1109/tcds.2020.3044366</a>}, number={3}, journal={IEEE Transactions on Cognitive and Developmental Systems}, author={Rohlfing, Katharina J. and Cimiano, Philipp and Scharlau, Ingrid and Matzner, Tobias and Buhl, Heike M. and Buschmeier, Hendrik and Esposito, Elena and Grimminger, Angela and Hammer, Barbara and Haeb-Umbach, Reinhold and et al.}, year={2021}, pages={717–728} }","ama":"Rohlfing KJ, Cimiano P, Scharlau I, et al. Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems. <i>IEEE Transactions on Cognitive and Developmental Systems</i>. 2021;13(3):717-728. doi:<a href=\"https://doi.org/10.1109/tcds.2020.3044366\">10.1109/tcds.2020.3044366</a>","chicago":"Rohlfing, Katharina J., Philipp Cimiano, Ingrid Scharlau, Tobias Matzner, Heike M. Buhl, Hendrik Buschmeier, Elena Esposito, et al. “Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems.” <i>IEEE Transactions on Cognitive and Developmental Systems</i> 13, no. 3 (2021): 717–28. <a href=\"https://doi.org/10.1109/tcds.2020.3044366\">https://doi.org/10.1109/tcds.2020.3044366</a>.","ieee":"K. J. Rohlfing <i>et al.</i>, “Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems,” <i>IEEE Transactions on Cognitive and Developmental Systems</i>, vol. 13, no. 3, pp. 717–728, 2021, doi: <a href=\"https://doi.org/10.1109/tcds.2020.3044366\">10.1109/tcds.2020.3044366</a>."},"date_updated":"2023-12-05T10:15:02Z","oa":"1","volume":13,"author":[{"first_name":"Katharina J.","last_name":"Rohlfing","id":"50352","full_name":"Rohlfing, Katharina J."},{"last_name":"Cimiano","full_name":"Cimiano, Philipp","first_name":"Philipp"},{"orcid":"0000-0003-2364-9489","last_name":"Scharlau","id":"451","full_name":"Scharlau, Ingrid","first_name":"Ingrid"},{"id":"65695","full_name":"Matzner, Tobias","last_name":"Matzner","first_name":"Tobias"},{"first_name":"Heike M.","id":"27152","full_name":"Buhl, Heike M.","last_name":"Buhl"},{"last_name":"Buschmeier","full_name":"Buschmeier, Hendrik","first_name":"Hendrik"},{"full_name":"Esposito, Elena","last_name":"Esposito","first_name":"Elena"},{"first_name":"Angela","full_name":"Grimminger, Angela","id":"57578","last_name":"Grimminger"},{"first_name":"Barbara","last_name":"Hammer","full_name":"Hammer, Barbara"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"},{"last_name":"Horwath","id":"68836","full_name":"Horwath, Ilona","first_name":"Ilona"},{"first_name":"Eyke","id":"48129","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier"},{"first_name":"Friederike","last_name":"Kern","full_name":"Kern, Friederike"},{"first_name":"Stefan","full_name":"Kopp, Stefan","last_name":"Kopp"},{"full_name":"Thommes, Kirsten","id":"72497","last_name":"Thommes","first_name":"Kirsten"},{"first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716"},{"first_name":"Carsten","last_name":"Schulte","id":"60311","full_name":"Schulte, Carsten"},{"last_name":"Wachsmuth","full_name":"Wachsmuth, Henning","id":"3900","first_name":"Henning"},{"first_name":"Petra","full_name":"Wagner, Petra","last_name":"Wagner"},{"first_name":"Britta","last_name":"Wrede","full_name":"Wrede, Britta"}],"doi":"10.1109/tcds.2020.3044366","type":"journal_article","status":"public","_id":"24456","project":[{"grant_number":"438445824","_id":"109","name":"TRR 318: TRR 318 - Erklärbarkeit konstruieren"}],"department":[{"_id":"603"},{"_id":"749"},{"_id":"424"},{"_id":"67"},{"_id":"574"},{"_id":"184"},{"_id":"757"},{"_id":"54"},{"_id":"178"}],"user_id":"42933","article_type":"original","file_date_updated":"2023-11-20T16:33:51Z"},{"language":[{"iso":"eng"}],"keyword":["evolutionary algorithms","evolutionary diversity optimization","knapsack problem","tailored operators"],"publication":"Proceedings of the Genetic and Evolutionary Computation Conference","abstract":[{"text":"In practise, it is often desirable to provide the decision-maker with a rich set of diverse solutions of decent quality instead of just a single solution. In this paper we study evolutionary diversity optimization for the knapsack problem (KP). Our goal is to evolve a population of solutions that all have a profit of at least (1 - {$ϵ$}) {$\\cdot$} OPT, where OPT is the value of an optimal solution. Furthermore, they should differ in structure with respect to an entropy-based diversity measure. To this end we propose a simple ({$\\mu$} + 1)-EA with initial approximate solutions calculated by a well-known FPTAS for the KP. We investigate the effect of different standard mutation operators and introduce biased mutation and crossover which puts strong probability on flipping bits of low and/or high frequency within the population. An experimental study on different instances and settings shows that the proposed mutation operators in most cases perform slightly inferior in the long term, but show strong benefits if the number of function evaluations is severely limited.","lang":"eng"}],"date_created":"2023-11-14T15:58:54Z","publisher":"Association for Computing Machinery","title":"Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms","year":"2021","department":[{"_id":"819"}],"series_title":"GECCO ’21","user_id":"102979","_id":"48853","extern":"1","type":"conference","status":"public","author":[{"first_name":"Jakob","id":"102979","full_name":"Bossek, Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668"},{"first_name":"Aneta","full_name":"Neumann, Aneta","last_name":"Neumann"},{"full_name":"Neumann, Frank","last_name":"Neumann","first_name":"Frank"}],"date_updated":"2023-12-13T10:45:22Z","doi":"10.1145/3449639.3459364","publication_identifier":{"isbn":["978-1-4503-8350-9"]},"publication_status":"published","page":"556–564","citation":{"bibtex":"@inproceedings{Bossek_Neumann_Neumann_2021, place={New York, NY, USA}, series={GECCO ’21}, title={Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms}, DOI={<a href=\"https://doi.org/10.1145/3449639.3459364\">10.1145/3449639.3459364</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Bossek, Jakob and Neumann, Aneta and Neumann, Frank}, year={2021}, pages={556–564}, collection={GECCO ’21} }","mla":"Bossek, Jakob, et al. “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms.” <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, Association for Computing Machinery, 2021, pp. 556–564, doi:<a href=\"https://doi.org/10.1145/3449639.3459364\">10.1145/3449639.3459364</a>.","short":"J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 556–564.","apa":"Bossek, J., Neumann, A., &#38; Neumann, F. (2021). Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms. <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 556–564. <a href=\"https://doi.org/10.1145/3449639.3459364\">https://doi.org/10.1145/3449639.3459364</a>","ama":"Bossek J, Neumann A, Neumann F. Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. GECCO ’21. Association for Computing Machinery; 2021:556–564. doi:<a href=\"https://doi.org/10.1145/3449639.3459364\">10.1145/3449639.3459364</a>","chicago":"Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 556–564. GECCO ’21. New York, NY, USA: Association for Computing Machinery, 2021. <a href=\"https://doi.org/10.1145/3449639.3459364\">https://doi.org/10.1145/3449639.3459364</a>.","ieee":"J. Bossek, A. Neumann, and F. Neumann, “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2021, pp. 556–564, doi: <a href=\"https://doi.org/10.1145/3449639.3459364\">10.1145/3449639.3459364</a>."},"place":"New York, NY, USA"},{"status":"public","type":"conference","extern":"1","user_id":"102979","department":[{"_id":"819"}],"_id":"48855","citation":{"bibtex":"@inproceedings{Bossek_Neumann_Neumann_2021, place={Berlin, Heidelberg}, title={Exact Counting and~Sampling of Optima for the Knapsack Problem}, DOI={<a href=\"https://doi.org/10.1007/978-3-030-92121-7_4\">10.1007/978-3-030-92121-7_4</a>}, booktitle={Learning and Intelligent Optimization}, publisher={Springer-Verlag}, author={Bossek, Jakob and Neumann, Aneta and Neumann, Frank}, year={2021}, pages={40–54} }","mla":"Bossek, Jakob, et al. “Exact Counting And~Sampling of Optima for the Knapsack Problem.” <i>Learning and Intelligent Optimization</i>, Springer-Verlag, 2021, pp. 40–54, doi:<a href=\"https://doi.org/10.1007/978-3-030-92121-7_4\">10.1007/978-3-030-92121-7_4</a>.","short":"J. Bossek, A. Neumann, F. Neumann, in: Learning and Intelligent Optimization, Springer-Verlag, Berlin, Heidelberg, 2021, pp. 40–54.","apa":"Bossek, J., Neumann, A., &#38; Neumann, F. (2021). Exact Counting and~Sampling of Optima for the Knapsack Problem. <i>Learning and Intelligent Optimization</i>, 40–54. <a href=\"https://doi.org/10.1007/978-3-030-92121-7_4\">https://doi.org/10.1007/978-3-030-92121-7_4</a>","ama":"Bossek J, Neumann A, Neumann F. Exact Counting and~Sampling of Optima for the Knapsack Problem. In: <i>Learning and Intelligent Optimization</i>. Springer-Verlag; 2021:40–54. doi:<a href=\"https://doi.org/10.1007/978-3-030-92121-7_4\">10.1007/978-3-030-92121-7_4</a>","ieee":"J. Bossek, A. Neumann, and F. Neumann, “Exact Counting and~Sampling of Optima for the Knapsack Problem,” in <i>Learning and Intelligent Optimization</i>, 2021, pp. 40–54, doi: <a href=\"https://doi.org/10.1007/978-3-030-92121-7_4\">10.1007/978-3-030-92121-7_4</a>.","chicago":"Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Exact Counting And~Sampling of Optima for the Knapsack Problem.” In <i>Learning and Intelligent Optimization</i>, 40–54. Berlin, Heidelberg: Springer-Verlag, 2021. <a href=\"https://doi.org/10.1007/978-3-030-92121-7_4\">https://doi.org/10.1007/978-3-030-92121-7_4</a>."},"page":"40–54","place":"Berlin, Heidelberg","publication_status":"published","publication_identifier":{"isbn":["978-3-030-92120-0"]},"doi":"10.1007/978-3-030-92121-7_4","author":[{"first_name":"Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","id":"102979","full_name":"Bossek, Jakob"},{"full_name":"Neumann, Aneta","last_name":"Neumann","first_name":"Aneta"},{"first_name":"Frank","full_name":"Neumann, Frank","last_name":"Neumann"}],"date_updated":"2023-12-13T10:45:14Z","abstract":[{"lang":"eng","text":"Computing sets of high quality solutions has gained increasing interest in recent years. In this paper, we investigate how to obtain sets of optimal solutions for the classical knapsack problem. We present an algorithm to count exactly the number of optima to a zero-one knapsack problem instance. In addition, we show how to efficiently sample uniformly at random from the set of all global optima. In our experimental study, we investigate how the number of optima develops for classical random benchmark instances dependent on their generator parameters. We find that the number of global optima can increase exponentially for practically relevant classes of instances with correlated weights and profits which poses a justification for the considered exact counting problem."}],"publication":"Learning and Intelligent Optimization","language":[{"iso":"eng"}],"keyword":["Dynamic programming","Exact counting","Sampling","Zero-one knapsack problem"],"year":"2021","title":"Exact Counting and~Sampling of Optima for the Knapsack Problem","date_created":"2023-11-14T15:58:54Z","publisher":"Springer-Verlag"},{"department":[{"_id":"819"}],"series_title":"GECCO ’21","user_id":"102979","_id":"48860","extern":"1","language":[{"iso":"eng"}],"keyword":["evolutionary algorithms","evolutionary diversity optimization","minimum spanning tree","runtime analysis"],"publication":"Proceedings of the Genetic and Evolutionary Computation Conference","type":"conference","status":"public","abstract":[{"text":"In the area of evolutionary computation the calculation of diverse sets of high-quality solutions to a given optimization problem has gained momentum in recent years under the term evolutionary diversity optimization. Theoretical insights into the working principles of baseline evolutionary algorithms for diversity optimization are still rare. In this paper we study the well-known Minimum Spanning Tree problem (MST) in the context of diversity optimization where population diversity is measured by the sum of pairwise edge overlaps. Theoretical results provide insights into the fitness landscape of the MST diversity optimization problem pointing out that even for a population of {$\\mu$} = 2 fitness plateaus (of constant length) can be reached, but nevertheless diverse sets can be calculated in polynomial time. We supplement our theoretical results with a series of experiments for the unconstrained and constraint case where all solutions need to fulfill a minimal quality threshold. Our results show that a simple ({$\\mu$} + 1)-EA can effectively compute a diversified population of spanning trees of high quality.","lang":"eng"}],"author":[{"full_name":"Bossek, Jakob","id":"102979","last_name":"Bossek","orcid":"0000-0002-4121-4668","first_name":"Jakob"},{"full_name":"Neumann, Frank","last_name":"Neumann","first_name":"Frank"}],"date_created":"2023-11-14T15:58:55Z","date_updated":"2023-12-13T10:45:37Z","publisher":"Association for Computing Machinery","doi":"10.1145/3449639.3459363","title":"Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem","publication_identifier":{"isbn":["978-1-4503-8350-9"]},"publication_status":"published","page":"198–206","citation":{"apa":"Bossek, J., &#38; Neumann, F. (2021). Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem. <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 198–206. <a href=\"https://doi.org/10.1145/3449639.3459363\">https://doi.org/10.1145/3449639.3459363</a>","short":"J. Bossek, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 198–206.","mla":"Bossek, Jakob, and Frank Neumann. “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem.” <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, Association for Computing Machinery, 2021, pp. 198–206, doi:<a href=\"https://doi.org/10.1145/3449639.3459363\">10.1145/3449639.3459363</a>.","bibtex":"@inproceedings{Bossek_Neumann_2021, place={New York, NY, USA}, series={GECCO ’21}, title={Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem}, DOI={<a href=\"https://doi.org/10.1145/3449639.3459363\">10.1145/3449639.3459363</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Bossek, Jakob and Neumann, Frank}, year={2021}, pages={198–206}, collection={GECCO ’21} }","chicago":"Bossek, Jakob, and Frank Neumann. “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 198–206. GECCO ’21. New York, NY, USA: Association for Computing Machinery, 2021. <a href=\"https://doi.org/10.1145/3449639.3459363\">https://doi.org/10.1145/3449639.3459363</a>.","ieee":"J. Bossek and F. Neumann, “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2021, pp. 198–206, doi: <a href=\"https://doi.org/10.1145/3449639.3459363\">10.1145/3449639.3459363</a>.","ama":"Bossek J, Neumann F. Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. GECCO ’21. Association for Computing Machinery; 2021:198–206. doi:<a href=\"https://doi.org/10.1145/3449639.3459363\">10.1145/3449639.3459363</a>"},"year":"2021","place":"New York, NY, USA"},{"extern":"1","language":[{"iso":"eng"}],"keyword":["evolutionary algorithms","pseudo-boolean functions","runtime analysis","theory"],"department":[{"_id":"819"}],"user_id":"102979","_id":"48862","status":"public","abstract":[{"text":"Most runtime analyses of randomised search heuristics focus on the expected number of function evaluations to find a unique global optimum. We ask a fundamental question: if additional search points are declared optimal, or declared as desirable target points, do these additional optima speed up evolutionary algorithms? More formally, we analyse the expected hitting time of a target set OPT {$\\cup$} S where S is a set of non-optimal search points and OPT is the set of optima and compare it to the expected hitting time of OPT. We show that the answer to our question depends on the number and placement of search points in S. For all black-box algorithms and all fitness functions we show that, if additional optima are placed randomly, even an exponential number of optima has a negligible effect on the expected optimisation time. Considering Hamming balls around all global optima gives an easier target for some algorithms and functions and can shift the phase transition with respect to offspring population sizes in the (1,{$\\lambda$}) EA on One-Max. Finally, on functions where search trajectories typically join in a single search point, turning one search point into an optimum drastically reduces the expected optimisation time.","lang":"eng"}],"publication":"Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms","type":"book_chapter","title":"Do Additional Optima Speed up Evolutionary Algorithms?","date_created":"2023-11-14T15:58:55Z","author":[{"id":"102979","full_name":"Bossek, Jakob","orcid":"0000-0002-4121-4668","last_name":"Bossek","first_name":"Jakob"},{"first_name":"Dirk","full_name":"Sudholt, Dirk","last_name":"Sudholt"}],"publisher":"Association for Computing Machinery","date_updated":"2023-12-13T10:45:31Z","page":"1–11","citation":{"apa":"Bossek, J., &#38; Sudholt, D. (2021). Do Additional Optima Speed up Evolutionary Algorithms? In <i>Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i> (pp. 1–11). Association for Computing Machinery.","bibtex":"@inbook{Bossek_Sudholt_2021, place={New York, NY, USA}, title={Do Additional Optima Speed up Evolutionary Algorithms?}, booktitle={Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms}, publisher={Association for Computing Machinery}, author={Bossek, Jakob and Sudholt, Dirk}, year={2021}, pages={1–11} }","mla":"Bossek, Jakob, and Dirk Sudholt. “Do Additional Optima Speed up Evolutionary Algorithms?” <i>Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>, Association for Computing Machinery, 2021, pp. 1–11.","short":"J. Bossek, D. Sudholt, in: Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2021, pp. 1–11.","ama":"Bossek J, Sudholt D. Do Additional Optima Speed up Evolutionary Algorithms? In: <i>Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>. Association for Computing Machinery; 2021:1–11.","ieee":"J. Bossek and D. Sudholt, “Do Additional Optima Speed up Evolutionary Algorithms?,” in <i>Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>, New York, NY, USA: Association for Computing Machinery, 2021, pp. 1–11.","chicago":"Bossek, Jakob, and Dirk Sudholt. “Do Additional Optima Speed up Evolutionary Algorithms?” In <i>Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>, 1–11. New York, NY, USA: Association for Computing Machinery, 2021."},"year":"2021","place":"New York, NY, USA","publication_identifier":{"isbn":["978-1-4503-8352-3"]},"publication_status":"published"},{"abstract":[{"text":"Classic automated algorithm selection (AS) for (combinatorial) optimization problems heavily relies on so-called instance features, i.e., numerical characteristics of the problem at hand ideally extracted with computationally low-demanding routines. For the traveling salesperson problem (TSP) a plethora of features have been suggested. Most of these features are, if at all, only normalized imprecisely raising the issue of feature values being strongly affected by the instance size. Such artifacts may have detrimental effects on algorithm selection models. We propose a normalization for two feature groups which stood out in multiple AS studies on the TSP: (a) features based on a minimum spanning tree (MST) and (b) a k-nearest neighbor graph (NNG) transformation of the input instance. To this end we theoretically derive minimum and maximum values for properties of MSTs and k-NNGs of Euclidean graphs. We analyze the differences in feature space between normalized versions of these features and their unnormalized counterparts. Our empirical investigations on various TSP benchmark sets point out that the feature scaling succeeds in eliminating the effect of the instance size. Eventually, a proof-of-concept AS-study shows promising results: models trained with normalized features tend to outperform those trained with the respective vanilla features.","lang":"eng"}],"status":"public","publication":"Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms","type":"book_chapter","keyword":["automated algorithm selection","graph theory","instance features","normalization","traveling salesperson problem (TSP)"],"extern":"1","language":[{"iso":"eng"}],"_id":"48881","department":[{"_id":"819"}],"user_id":"102979","place":"New York, NY, USA","year":"2021","page":"1–15","citation":{"chicago":"Heins, Jonathan, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, and Pascal Kerschke. “On the Potential of Normalized TSP Features for Automated Algorithm Selection.” In <i>Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>, 1–15. New York, NY, USA: Association for Computing Machinery, 2021.","ieee":"J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, and P. Kerschke, “On the Potential of Normalized TSP Features for Automated Algorithm Selection,” in <i>Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>, New York, NY, USA: Association for Computing Machinery, 2021, pp. 1–15.","ama":"Heins J, Bossek J, Pohl J, Seiler M, Trautmann H, Kerschke P. On the Potential of Normalized TSP Features for Automated Algorithm Selection. In: <i>Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>. Association for Computing Machinery; 2021:1–15.","short":"J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, P. Kerschke, in: Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2021, pp. 1–15.","mla":"Heins, Jonathan, et al. “On the Potential of Normalized TSP Features for Automated Algorithm Selection.” <i>Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>, Association for Computing Machinery, 2021, pp. 1–15.","bibtex":"@inbook{Heins_Bossek_Pohl_Seiler_Trautmann_Kerschke_2021, place={New York, NY, USA}, title={On the Potential of Normalized TSP Features for Automated Algorithm Selection}, booktitle={Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms}, publisher={Association for Computing Machinery}, author={Heins, Jonathan and Bossek, Jakob and Pohl, Janina and Seiler, Moritz and Trautmann, Heike and Kerschke, Pascal}, year={2021}, pages={1–15} }","apa":"Heins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H., &#38; Kerschke, P. (2021). On the Potential of Normalized TSP Features for Automated Algorithm Selection. In <i>Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i> (pp. 1–15). Association for Computing Machinery."},"publication_identifier":{"isbn":["978-1-4503-8352-3"]},"title":"On the Potential of Normalized TSP Features for Automated Algorithm Selection","date_updated":"2023-12-13T10:47:23Z","publisher":"Association for Computing Machinery","date_created":"2023-11-14T15:58:58Z","author":[{"last_name":"Heins","full_name":"Heins, Jonathan","first_name":"Jonathan"},{"last_name":"Bossek","orcid":"0000-0002-4121-4668","full_name":"Bossek, Jakob","id":"102979","first_name":"Jakob"},{"first_name":"Janina","full_name":"Pohl, Janina","last_name":"Pohl"},{"first_name":"Moritz","last_name":"Seiler","full_name":"Seiler, Moritz"},{"first_name":"Heike","full_name":"Trautmann, Heike","last_name":"Trautmann"},{"first_name":"Pascal","full_name":"Kerschke, Pascal","last_name":"Kerschke"}]},{"page":"1423–1432","citation":{"ama":"Bossek J, Wagner M. Generating Instances with Performance Differences for More than Just Two Algorithms. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>. GECCO’21. Association for Computing Machinery; 2021:1423–1432. doi:<a href=\"https://doi.org/10.1145/3449726.3463165\">10.1145/3449726.3463165</a>","ieee":"J. Bossek and M. Wagner, “Generating Instances with Performance Differences for More than Just Two Algorithms,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, 2021, pp. 1423–1432, doi: <a href=\"https://doi.org/10.1145/3449726.3463165\">10.1145/3449726.3463165</a>.","chicago":"Bossek, Jakob, and Markus Wagner. “Generating Instances with Performance Differences for More than Just Two Algorithms.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, 1423–1432. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. <a href=\"https://doi.org/10.1145/3449726.3463165\">https://doi.org/10.1145/3449726.3463165</a>.","apa":"Bossek, J., &#38; Wagner, M. (2021). Generating Instances with Performance Differences for More than Just Two Algorithms. <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, 1423–1432. <a href=\"https://doi.org/10.1145/3449726.3463165\">https://doi.org/10.1145/3449726.3463165</a>","mla":"Bossek, Jakob, and Markus Wagner. “Generating Instances with Performance Differences for More than Just Two Algorithms.” <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, Association for Computing Machinery, 2021, pp. 1423–1432, doi:<a href=\"https://doi.org/10.1145/3449726.3463165\">10.1145/3449726.3463165</a>.","bibtex":"@inproceedings{Bossek_Wagner_2021, place={New York, NY, USA}, series={GECCO’21}, title={Generating Instances with Performance Differences for More than Just Two Algorithms}, DOI={<a href=\"https://doi.org/10.1145/3449726.3463165\">10.1145/3449726.3463165</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion}, publisher={Association for Computing Machinery}, author={Bossek, Jakob and Wagner, Markus}, year={2021}, pages={1423–1432}, collection={GECCO’21} }","short":"J. Bossek, M. Wagner, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2021, pp. 1423–1432."},"place":"New York, NY, USA","publication_identifier":{"isbn":["978-1-4503-8351-6"]},"doi":"10.1145/3449726.3463165","author":[{"full_name":"Bossek, Jakob","id":"102979","orcid":"0000-0002-4121-4668","last_name":"Bossek","first_name":"Jakob"},{"first_name":"Markus","full_name":"Wagner, Markus","last_name":"Wagner"}],"date_updated":"2023-12-13T10:47:41Z","status":"public","type":"conference","extern":"1","department":[{"_id":"819"}],"user_id":"102979","series_title":"GECCO’21","_id":"48876","year":"2021","title":"Generating Instances with Performance Differences for More than Just Two Algorithms","date_created":"2023-11-14T15:58:57Z","publisher":"Association for Computing Machinery","abstract":[{"text":"In recent years, Evolutionary Algorithms (EAs) have frequently been adopted to evolve instances for optimization problems that pose difficulties for one algorithm while being rather easy for a competitor and vice versa. Typically, this is achieved by either minimizing or maximizing the performance difference or ratio which serves as the fitness function. Repeating this process is useful to gain insights into strengths/weaknesses of certain algorithms or to build a set of instances with strong performance differences as a foundation for automatic per-instance algorithm selection or configuration. We contribute to this branch of research by proposing fitness-functions to evolve instances that show large performance differences for more than just two algorithms simultaneously. As a proof-of-principle, we evolve instances of the multi-component Traveling Thief Problem (TTP) for three incomplete TTP-solvers. Our results point out that our strategies are promising, but unsurprisingly their success strongly relies on the algorithms’ performance complementarity.","lang":"eng"}],"publication":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","language":[{"iso":"eng"}],"keyword":["evolutionary algorithms","evolving instances","fitness function","instance hardness","traveling thief problem (TTP)"]},{"status":"public","abstract":[{"lang":"eng","text":"Computing diverse sets of high-quality solutions has gained increasing attention among the evolutionary computation community in recent years. It allows practitioners to choose from a set of high-quality alternatives. In this paper, we employ a population diversity measure, called the high-order entropy measure, in an evolutionary algorithm to compute a diverse set of high-quality solutions for the Traveling Salesperson Problem. In contrast to previous studies, our approach allows diversifying segments of tours containing several edges based on the entropy measure. We examine the resulting evolutionary diversity optimisation approach precisely in terms of the final set of solutions and theoretical properties. Experimental results show significant improvements compared to a recently proposed edge-based diversity optimisation approach when working with a large population of solutions or long segments."}],"type":"conference","publication":"Proceedings of the Genetic and Evolutionary Computation Conference","language":[{"iso":"eng"}],"extern":"1","keyword":["evolutionary algorithms","evolutionary diversity optimisation","high-order entropy","traveling salesperson problem"],"user_id":"102979","series_title":"GECCO’21","department":[{"_id":"819"}],"_id":"48893","citation":{"ama":"Nikfarjam A, Bossek J, Neumann A, Neumann F. Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. GECCO’21. Association for Computing Machinery; 2021:600–608. doi:<a href=\"https://doi.org/10.1145/3449639.3459384\">10.1145/3449639.3459384</a>","chicago":"Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 600–608. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. <a href=\"https://doi.org/10.1145/3449639.3459384\">https://doi.org/10.1145/3449639.3459384</a>.","ieee":"A. Nikfarjam, J. Bossek, A. Neumann, and F. Neumann, “Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2021, pp. 600–608, doi: <a href=\"https://doi.org/10.1145/3449639.3459384\">10.1145/3449639.3459384</a>.","mla":"Nikfarjam, Adel, et al. “Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem.” <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, Association for Computing Machinery, 2021, pp. 600–608, doi:<a href=\"https://doi.org/10.1145/3449639.3459384\">10.1145/3449639.3459384</a>.","bibtex":"@inproceedings{Nikfarjam_Bossek_Neumann_Neumann_2021, place={New York, NY, USA}, series={GECCO’21}, title={Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem}, DOI={<a href=\"https://doi.org/10.1145/3449639.3459384\">10.1145/3449639.3459384</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Nikfarjam, Adel and Bossek, Jakob and Neumann, Aneta and Neumann, Frank}, year={2021}, pages={600–608}, collection={GECCO’21} }","short":"A. Nikfarjam, J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 600–608.","apa":"Nikfarjam, A., Bossek, J., Neumann, A., &#38; Neumann, F. (2021). Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem. <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 600–608. <a href=\"https://doi.org/10.1145/3449639.3459384\">https://doi.org/10.1145/3449639.3459384</a>"},"page":"600–608","year":"2021","place":"New York, NY, USA","publication_identifier":{"isbn":["978-1-4503-8350-9"]},"doi":"10.1145/3449639.3459384","title":"Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem","date_created":"2023-11-14T15:59:00Z","author":[{"last_name":"Nikfarjam","full_name":"Nikfarjam, Adel","first_name":"Adel"},{"first_name":"Jakob","full_name":"Bossek, Jakob","id":"102979","last_name":"Bossek","orcid":"0000-0002-4121-4668"},{"last_name":"Neumann","full_name":"Neumann, Aneta","first_name":"Aneta"},{"first_name":"Frank","full_name":"Neumann, Frank","last_name":"Neumann"}],"date_updated":"2023-12-13T10:50:06Z","publisher":"Association for Computing Machinery"},{"publication_identifier":{"isbn":["978-1-4503-8350-9"]},"citation":{"ieee":"A. Neumann, J. Bossek, and F. Neumann, “Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2021, pp. 261–269, doi: <a href=\"https://doi.org/10.1145/3449639.3459385\">10.1145/3449639.3459385</a>.","chicago":"Neumann, Aneta, Jakob Bossek, and Frank Neumann. “Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 261–269. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. <a href=\"https://doi.org/10.1145/3449639.3459385\">https://doi.org/10.1145/3449639.3459385</a>.","ama":"Neumann A, Bossek J, Neumann F. Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. GECCO’21. Association for Computing Machinery; 2021:261–269. doi:<a href=\"https://doi.org/10.1145/3449639.3459385\">10.1145/3449639.3459385</a>","bibtex":"@inproceedings{Neumann_Bossek_Neumann_2021, place={New York, NY, USA}, series={GECCO’21}, title={Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions}, DOI={<a href=\"https://doi.org/10.1145/3449639.3459385\">10.1145/3449639.3459385</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Neumann, Aneta and Bossek, Jakob and Neumann, Frank}, year={2021}, pages={261–269}, collection={GECCO’21} }","mla":"Neumann, Aneta, et al. “Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions.” <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, Association for Computing Machinery, 2021, pp. 261–269, doi:<a href=\"https://doi.org/10.1145/3449639.3459385\">10.1145/3449639.3459385</a>.","short":"A. Neumann, J. Bossek, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 261–269.","apa":"Neumann, A., Bossek, J., &#38; Neumann, F. (2021). Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions. <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 261–269. <a href=\"https://doi.org/10.1145/3449639.3459385\">https://doi.org/10.1145/3449639.3459385</a>"},"page":"261–269","place":"New York, NY, USA","author":[{"full_name":"Neumann, Aneta","last_name":"Neumann","first_name":"Aneta"},{"id":"102979","full_name":"Bossek, Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","first_name":"Jakob"},{"first_name":"Frank","last_name":"Neumann","full_name":"Neumann, Frank"}],"date_updated":"2023-12-13T10:49:25Z","doi":"10.1145/3449639.3459385","type":"conference","status":"public","user_id":"102979","series_title":"GECCO’21","department":[{"_id":"819"}],"_id":"48891","extern":"1","year":"2021","date_created":"2023-11-14T15:58:59Z","publisher":"Association for Computing Machinery","title":"Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions","publication":"Proceedings of the Genetic and Evolutionary Computation Conference","abstract":[{"text":"Submodular functions allow to model many real-world optimisation problems. This paper introduces approaches for computing diverse sets of high quality solutions for submodular optimisation problems with uniform and knapsack constraints. We first present diversifying greedy sampling approaches and analyse them with respect to the diversity measured by entropy and the approximation quality of the obtained solutions. Afterwards, we introduce an evolutionary diversity optimisation (EDO) approach to further improve diversity of the set of solutions. We carry out experimental investigations on popular submodular benchmark problems and analyse trade-offs in terms of solution quality and diversity of the resulting solution sets.","lang":"eng"}],"language":[{"iso":"eng"}],"keyword":["evolutionary algorithms","evolutionary diversity optimisation","sub-modular functions"]},{"author":[{"last_name":"Nikfarjam","full_name":"Nikfarjam, Adel","first_name":"Adel"},{"first_name":"Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","id":"102979","full_name":"Bossek, Jakob"},{"first_name":"Aneta","last_name":"Neumann","full_name":"Neumann, Aneta"},{"last_name":"Neumann","full_name":"Neumann, Frank","first_name":"Frank"}],"date_created":"2023-11-14T15:59:00Z","publisher":"Association for Computing Machinery","date_updated":"2023-12-13T10:49:59Z","title":"Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation","publication_identifier":{"isbn":["978-1-4503-8352-3"]},"citation":{"ama":"Nikfarjam A, Bossek J, Neumann A, Neumann F. Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation. In: <i>Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms</i>. Association for Computing Machinery; 2021:1–11.","chicago":"Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Computing Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation.” In <i>Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms</i>, 1–11. New York, NY, USA: Association for Computing Machinery, 2021.","ieee":"A. Nikfarjam, J. Bossek, A. Neumann, and F. Neumann, “Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation,” in <i>Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms</i>, New York, NY, USA: Association for Computing Machinery, 2021, pp. 1–11.","bibtex":"@inbook{Nikfarjam_Bossek_Neumann_Neumann_2021, place={New York, NY, USA}, title={Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation}, booktitle={Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms}, publisher={Association for Computing Machinery}, author={Nikfarjam, Adel and Bossek, Jakob and Neumann, Aneta and Neumann, Frank}, year={2021}, pages={1–11} }","mla":"Nikfarjam, Adel, et al. “Computing Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation.” <i>Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms</i>, Association for Computing Machinery, 2021, pp. 1–11.","short":"A. Nikfarjam, J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2021, pp. 1–11.","apa":"Nikfarjam, A., Bossek, J., Neumann, A., &#38; Neumann, F. (2021). Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation. In <i>Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms</i> (pp. 1–11). Association for Computing Machinery."},"page":"1–11","year":"2021","place":"New York, NY, USA","user_id":"102979","department":[{"_id":"819"}],"_id":"48892","language":[{"iso":"eng"}],"extern":"1","keyword":["edge assembly crossover (EAX)","evolutionary algorithms","evolutionary diversity optimisation (EDO)","traveling salesperson problem (TSP)"],"type":"book_chapter","publication":"Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms","status":"public","abstract":[{"lang":"eng","text":"Evolutionary algorithms based on edge assembly crossover (EAX) constitute some of the best performing incomplete solvers for the well-known traveling salesperson problem (TSP). Often, it is desirable to compute not just a single solution for a given problem, but a diverse set of high quality solutions from which a decision maker can choose one for implementation. Currently, there are only a few approaches for computing a diverse solution set for the TSP. Furthermore, almost all of them assume that the optimal solution is known. In this paper, we introduce evolutionary diversity optimisation (EDO) approaches for the TSP that find a diverse set of tours when the optimal tour is known or unknown. We show how to adopt EAX to not only find a high-quality solution but also to maximise the diversity of the population. The resulting EAX-based EDO approach, termed EAX-EDO is capable of obtaining diverse high-quality tours when the optimal solution for the TSP is known or unknown. A comparison to existing approaches shows that they are clearly outperformed by EAX-EDO."}]},{"_id":"48854","user_id":"102979","department":[{"_id":"819"}],"keyword":["Dynamic optimization","Evolutionary algorithms","Running time analysis"],"language":[{"iso":"eng"}],"type":"journal_article","publication":"Algorithmica","abstract":[{"lang":"eng","text":"We contribute to the theoretical understanding of randomized search heuristics for dynamic problems. We consider the classical vertex coloring problem on graphs and investigate the dynamic setting where edges are added to the current graph. We then analyze the expected time for randomized search heuristics to recompute high quality solutions. The (1+1) Evolutionary Algorithm and RLS operate in a setting where the number of colors is bounded and we are minimizing the number of conflicts. Iterated local search algorithms use an unbounded color palette and aim to use the smallest colors and, consequently, the smallest number of colors. We identify classes of bipartite graphs where reoptimization is as hard as or even harder than optimization from scratch, i.e., starting with a random initialization. Even adding a single edge can lead to hard symmetry problems. However, graph classes that are hard for one algorithm turn out to be easy for others. In most cases our bounds show that reoptimization is faster than optimizing from scratch. We further show that tailoring mutation operators to parts of the graph where changes have occurred can significantly reduce the expected reoptimization time. In most settings the expected reoptimization time for such tailored algorithms is linear in the number of added edges. However, tailored algorithms cannot prevent exponential times in settings where the original algorithm is inefficient."}],"status":"public","date_updated":"2023-12-13T10:51:34Z","author":[{"first_name":"Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","full_name":"Bossek, Jakob","id":"102979"},{"full_name":"Neumann, Frank","last_name":"Neumann","first_name":"Frank"},{"first_name":"Pan","last_name":"Peng","full_name":"Peng, Pan"},{"full_name":"Sudholt, Dirk","last_name":"Sudholt","first_name":"Dirk"}],"date_created":"2023-11-14T15:58:54Z","volume":83,"title":"Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem","doi":"10.1007/s00453-021-00838-3","publication_identifier":{"issn":["0178-4617"]},"issue":"10","year":"2021","citation":{"apa":"Bossek, J., Neumann, F., Peng, P., &#38; Sudholt, D. (2021). Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. <i>Algorithmica</i>, <i>83</i>(10), 3148–3179. <a href=\"https://doi.org/10.1007/s00453-021-00838-3\">https://doi.org/10.1007/s00453-021-00838-3</a>","short":"J. Bossek, F. Neumann, P. Peng, D. Sudholt, Algorithmica 83 (2021) 3148–3179.","mla":"Bossek, Jakob, et al. “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.” <i>Algorithmica</i>, vol. 83, no. 10, 2021, pp. 3148–3179, doi:<a href=\"https://doi.org/10.1007/s00453-021-00838-3\">10.1007/s00453-021-00838-3</a>.","bibtex":"@article{Bossek_Neumann_Peng_Sudholt_2021, title={Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem}, volume={83}, DOI={<a href=\"https://doi.org/10.1007/s00453-021-00838-3\">10.1007/s00453-021-00838-3</a>}, number={10}, journal={Algorithmica}, author={Bossek, Jakob and Neumann, Frank and Peng, Pan and Sudholt, Dirk}, year={2021}, pages={3148–3179} }","ama":"Bossek J, Neumann F, Peng P, Sudholt D. Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. <i>Algorithmica</i>. 2021;83(10):3148–3179. doi:<a href=\"https://doi.org/10.1007/s00453-021-00838-3\">10.1007/s00453-021-00838-3</a>","chicago":"Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.” <i>Algorithmica</i> 83, no. 10 (2021): 3148–3179. <a href=\"https://doi.org/10.1007/s00453-021-00838-3\">https://doi.org/10.1007/s00453-021-00838-3</a>.","ieee":"J. Bossek, F. Neumann, P. Peng, and D. Sudholt, “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem,” <i>Algorithmica</i>, vol. 83, no. 10, pp. 3148–3179, 2021, doi: <a href=\"https://doi.org/10.1007/s00453-021-00838-3\">10.1007/s00453-021-00838-3</a>."},"page":"3148–3179","intvolume":"        83"},{"publication":"2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","type":"conference","status":"public","_id":"29937","project":[{"name":"PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"department":[{"_id":"27"},{"_id":"518"}],"user_id":"3145","language":[{"iso":"eng"}],"quality_controlled":"1","publication_status":"published","year":"2021","citation":{"bibtex":"@inproceedings{Karp_Podobas_Jansson_Kenter_Plessl_Schlatter_Markidis_2021, title={High-Performance Spectral Element Methods on Field-Programmable Gate Arrays : Implementation, Evaluation, and Future Projection}, DOI={<a href=\"https://doi.org/10.1109/ipdps49936.2021.00116\">10.1109/ipdps49936.2021.00116</a>}, booktitle={2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)}, publisher={IEEE}, author={Karp, Martin and Podobas, Artur and Jansson, Niclas and Kenter, Tobias and Plessl, Christian and Schlatter, Philipp and Markidis, Stefano}, year={2021} }","mla":"Karp, Martin, et al. “High-Performance Spectral Element Methods on Field-Programmable Gate Arrays : Implementation, Evaluation, and Future Projection.” <i>2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)</i>, IEEE, 2021, doi:<a href=\"https://doi.org/10.1109/ipdps49936.2021.00116\">10.1109/ipdps49936.2021.00116</a>.","short":"M. Karp, A. Podobas, N. Jansson, T. Kenter, C. Plessl, P. Schlatter, S. Markidis, in: 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), IEEE, 2021.","apa":"Karp, M., Podobas, A., Jansson, N., Kenter, T., Plessl, C., Schlatter, P., &#38; Markidis, S. (2021). High-Performance Spectral Element Methods on Field-Programmable Gate Arrays : Implementation, Evaluation, and Future Projection. <i>2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)</i>. <a href=\"https://doi.org/10.1109/ipdps49936.2021.00116\">https://doi.org/10.1109/ipdps49936.2021.00116</a>","chicago":"Karp, Martin, Artur Podobas, Niclas Jansson, Tobias Kenter, Christian Plessl, Philipp Schlatter, and Stefano Markidis. “High-Performance Spectral Element Methods on Field-Programmable Gate Arrays : Implementation, Evaluation, and Future Projection.” In <i>2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)</i>. IEEE, 2021. <a href=\"https://doi.org/10.1109/ipdps49936.2021.00116\">https://doi.org/10.1109/ipdps49936.2021.00116</a>.","ieee":"M. Karp <i>et al.</i>, “High-Performance Spectral Element Methods on Field-Programmable Gate Arrays : Implementation, Evaluation, and Future Projection,” 2021, doi: <a href=\"https://doi.org/10.1109/ipdps49936.2021.00116\">10.1109/ipdps49936.2021.00116</a>.","ama":"Karp M, Podobas A, Jansson N, et al. High-Performance Spectral Element Methods on Field-Programmable Gate Arrays : Implementation, Evaluation, and Future Projection. In: <i>2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)</i>. IEEE; 2021. doi:<a href=\"https://doi.org/10.1109/ipdps49936.2021.00116\">10.1109/ipdps49936.2021.00116</a>"},"publisher":"IEEE","date_updated":"2024-01-22T09:59:13Z","date_created":"2022-02-21T14:26:37Z","author":[{"first_name":"Martin","last_name":"Karp","full_name":"Karp, Martin"},{"first_name":"Artur","full_name":"Podobas, Artur","last_name":"Podobas"},{"last_name":"Jansson","full_name":"Jansson, Niclas","first_name":"Niclas"},{"first_name":"Tobias","last_name":"Kenter","id":"3145","full_name":"Kenter, Tobias"},{"first_name":"Christian","last_name":"Plessl","orcid":"0000-0001-5728-9982","id":"16153","full_name":"Plessl, Christian"},{"last_name":"Schlatter","full_name":"Schlatter, Philipp","first_name":"Philipp"},{"full_name":"Markidis, Stefano","last_name":"Markidis","first_name":"Stefano"}],"title":"High-Performance Spectral Element Methods on Field-Programmable Gate Arrays : Implementation, Evaluation, and Future Projection","doi":"10.1109/ipdps49936.2021.00116"},{"citation":{"mla":"Gil, Oliver Fernández, and Anni-Yasmin Turhan. “Answering Regular Path Queries Under Approximate Semantics in Lightweight Description Logics.” <i>Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021</i>, AAAI Press, 2021, pp. 6340–6348, doi:<a href=\"https://doi.org/10.1609/AAAI.V35I7.16787\">10.1609/AAAI.V35I7.16787</a>.","short":"O.F. Gil, A.-Y. Turhan, in: Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, AAAI Press, 2021, pp. 6340–6348.","bibtex":"@inproceedings{Gil_Turhan_2021, title={Answering Regular Path Queries Under Approximate Semantics in Lightweight Description Logics}, DOI={<a href=\"https://doi.org/10.1609/AAAI.V35I7.16787\">10.1609/AAAI.V35I7.16787</a>}, booktitle={Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021}, publisher={AAAI Press}, author={Gil, Oliver Fernández and Turhan, Anni-Yasmin}, year={2021}, pages={6340–6348} }","apa":"Gil, O. F., &#38; Turhan, A.-Y. (2021). Answering Regular Path Queries Under Approximate Semantics in Lightweight Description Logics. <i>Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021</i>, 6340–6348. <a href=\"https://doi.org/10.1609/AAAI.V35I7.16787\">https://doi.org/10.1609/AAAI.V35I7.16787</a>","ama":"Gil OF, Turhan A-Y. Answering Regular Path Queries Under Approximate Semantics in Lightweight Description Logics. In: <i>Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021</i>. 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