A Dynamic Algorithm Configuration Framework Using Combinatorial Problem Features and Reinforcement Learning

Bibliographic Details
Title: A Dynamic Algorithm Configuration Framework Using Combinatorial Problem Features and Reinforcement Learning
Authors: Steiner, ElmarAff29, Pferschy, UlrichAff29
Contributors: Hartmanis, Juris, Founding EditorAff1, van Leeuwen, Jan, Series EditorAff2, Hutchison, David, Editorial Board MemberAff3, Kanade, Takeo, Editorial Board MemberAff4, Kittler, Josef, Editorial Board MemberAff5, Kleinberg, Jon M., Editorial Board MemberAff6, Kobsa, Alfred, Series EditorAff7, Mattern, Friedemann, Editorial Board MemberAff8, Mitchell, John C., Editorial Board MemberAff9, Naor, Moni, Editorial Board MemberAff10, Nierstrasz, Oscar, Series EditorAff11, Pandu Rangan, C., Editorial Board MemberAff12, Sudan, Madhu, Series EditorAff13, Terzopoulos, Demetri, Editorial Board MemberAff14, Tygar, Doug, Editorial Board MemberAff15, Weikum, Gerhard, Series EditorAff16, Vardi, Moshe Y, Series EditorAff17, Goos, Gerhard, Founding EditorAff18, Bertino, Elisa, Editorial Board MemberAff19, Gao, Wen, Editorial Board MemberAff20, Steffen, Bernhard, Editorial Board MemberAff21, Yung, Moti, Editorial Board MemberAff22, Woeginger, Gerhard, Editorial Board MemberAff23, Sevaux, Marc, editorAff24, Olteanu, Alexandru-Liviu, editorAff25, Pardo, Eduardo G., editorAff26, Sifaleras, Angelo, editorAff27, Makboul, Salma, editorAff28
Source: Metaheuristics : 15th International Conference, MIC 2024, Lorient, France, June 4–7, 2024, Proceedings, Part II. 14754:142-157
Database: Springer Nature eBooks
Description
ISBN:9783031629211
9783031629228
DOI:10.1007/978-3-031-62922-8_10