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Record Nr. |
UNISA996495171403316 |
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Autore |
Bär Schirin |
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Titolo |
Generic multi-agent reinforcement learning approach for flexible job-shop scheduling / / Schirin Bär |
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Pubbl/distr/stampa |
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Wiesbaden : , : Springer Vieweg, , [2022] |
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©2022 |
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ISBN |
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9783658391799 |
9783658391782 |
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Descrizione fisica |
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1 online resource (163 pages) |
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Disciplina |
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Soggetti |
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Flexible manufacturing systems |
Reinforcement learning |
Aprenentatge per reforç (Intel·ligència artificial) |
Sistemes multiagent |
Sistemes de producció flexibles |
Llibres electrònics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Intro -- Danksagung -- Abstract -- Zusammenfassung -- Contents -- Abbreviations -- List of Figures -- List of Tables -- 1 Introduction -- 1.1 Research Goals -- 1.2 Methodology -- 1.3 Structure of the Thesis -- 2 Requirements for Production Scheduling in Flexible Manufacturing -- 2.1 Foundations of Flexible Job-Shop Scheduling Problems -- 2.2 Requirement Analysis of Flexible Scheduling Solutions -- 2.2.1 Influences on Warehouse Control Systems -- 2.2.2 Influences on Manufacturing Control Systems -- 2.2.3 Derived and Ranked Requirements -- 2.3 State of the Art: Approaches to Solve Job-Shop Scheduling Problems -- 2.3.1 Conventional Scheduling Solutions -- 2.3.2 Reinforcement Learning Scheduling Solutions -- 2.4 Identification of the Research Gap -- 2.5 Contribution of this Work: Extended Flexible Job-Shop Scheduling Problem -- 3 Reinforcement Learning as an Approach for Flexible Scheduling -- 3.1 Understanding the Foundations: Formalization as a Markov Decision Process -- 3.1.1 Agent-Environment Interaction -- 3.1.2 Policies and Value Functions -- |
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