This monograph introduces a novel multiset-based conceptual, mathematical and knowledge engineering paradigm, called multigrammatical framework (MGF), used for planning and scheduling in resource-consuming, resource-producing (industrial) and resource-distributing (economical) sociotechnological systems (STS). This framework is meant to enable smart operation not only in a “business-as-usual” mode, but also in extraordinary, highly volatile or hazardous environments. It is the result of convergence and deep integration into a unified, flexible and effectively implemented formalism operating on multisets of several well-known paradigms from classical operations research and modern knowledge engineering, such as: mathematical programming, game theory, optimal scheduling, logic programming and constraint programming.
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Prof. Dr. Igor Sheremet is Deputy Director for Science at the Russian Foundation for Basic Research and full member of the Russian Academy of Sciences. Over the last twenty years, using techniques from optimization theory and knowledge engineering, he has developed a theory of recursive multisets that has applications to digital economies, resource-based games, the modelling of large sociotechnological systems and the assessment of their resilience to various destructive impacts. Igor Sheremet has (co)authored more than 20 monographs, including the Springer edited volume “Resilience in the Digital Age”. Between 2014 and 2020, he was a member of the Science Advisory Committee of the International Institute of Applied Systems Analysis (IIASA). Since 2018, he is co-chair of the Advanced Mathematical Tools for Data-Driven Applied Systems Analysis task group established by the Committee on Data (CODATA) of the International Science Council. Between 2020 and 2022, he was chair of the joint IIASA-CODATA workgroup on Open Data, Big Data and Systems Analysis. Among thirty-two mathematicians and thought leaders from across the globe, he is co-author of the recent book “Mathematics for Action. Supporting Science-Based Decision-Making” published by UNESCO in 2022.
This monograph introduces a novel multiset-based conceptual, mathematical and knowledge engineering paradigm, called multigrammatical framework (MGF), used for planning and scheduling in resource-consuming, resource-producing (industrial) and resource-distributing (economical) sociotechnological systems (STS). This framework is meant to enable smart operation not only in a “business-as-usual” mode, but also in extraordinary, highly volatile or hazardous environments. It is the result of convergence and deep integration into a unified, flexible and effectively implemented formalism operating on multisets of several well-known paradigms from classical operations research and modern knowledge engineering, such as: mathematical programming, game theory, optimal scheduling, logic programming and constraint programming.
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This monograph introduces a novel multiset-based conceptual, mathematical and knowledge engineering paradigm, called multigrammatical framework (MGF), used for planning and scheduling in resource-consuming, resource-producing (industrial) and resourc. Bestandsnummer des Verkäufers 1155872006
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This monograph introduces a novel multiset-based conceptual, mathematical and knowledge engineering paradigm, called multigrammatical framework (MGF), used for planning and scheduling in resource-consuming, resource-producing (industrial) and resource-distributing (economical) sociotechnological systems (STS). This framework is meant to enable smart operation not only in a 'business-as-usual' mode, but also in extraordinary, highly volatile or hazardous environments. It is the result of convergence and deep integration into a unified, flexible and effectively implemented formalism operating on multisets of several well-known paradigms from classical operations research and modern knowledge engineering, such as: mathematical programming, game theory, optimal scheduling, logic programming and constraint programming.The mathematical background needed for MGF, its algorithmics, applications, implementation issues, as well as its nexus with known models from operations research and theoretical computer science areas are considered. The resilience and recovery issues of an STS are studied by applying the MGF toolkit and on paying special attention to the multigrammatical assessment of resilience of energy infrastructures. MGF-represented resource-based games are introduced, and directions for further development are discussed. The author presents multiple applications to business intelligence, critical infrastructure, ecology, economy and industry.This book is addressed to scholars working in the areas of theoretical and applied computer science, artificial intelligence, systems analysis, operations research, mathematical economy and critical infrastructure protection, to engineers developing software-intensive solutions for implementation of the knowledge-based digital economy and Industry 4.0, as well as to students, aspirants and university staff. Foundational knowledge of set theory, mathematicallogic and routine operations on data bases is needed to read this book. The content of the monograph is gradually presented, from simple to complex, in a well-understandable step-by-step manner. Multiple examples and accompanying figures are included in order to support the explanation of the various notions, expressions and algorithms. 476 pp. Englisch. Bestandsnummer des Verkäufers 9783031138607
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Taschenbuch. Zustand: Neu. Multigrammatical Framework for Knowledge-Based Digital Economy | Igor A. Sheremet | Taschenbuch | xiv | Englisch | 2023 | Springer International Publishing | EAN 9783031138607 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Bestandsnummer des Verkäufers 127803749
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