| 000 | 05085nam a22006135i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-13858-4 | ||
| 003 | DE-He213 | ||
| 005 | 20240423130120.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 221029s2022 sz | s |||| 0|eng d | ||
| 020 |
_a9783031138584 _9978-3-031-13858-4 |
||
| 024 | 7 |
_a10.1007/978-3-031-13858-4 _2doi |
|
| 050 | 4 | _aQ334-342 | |
| 050 | 4 | _aTA347.A78 | |
| 072 | 7 |
_aUYQ _2bicssc |
|
| 072 | 7 |
_aCOM004000 _2bisacsh |
|
| 072 | 7 |
_aUYQ _2thema |
|
| 082 | 0 | 4 |
_a006.3 _223 |
| 100 | 1 |
_aSheremet, Igor A. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 245 | 1 | 0 |
_aMultigrammatical Framework for Knowledge-Based Digital Economy _h[electronic resource] / _cby Igor A. Sheremet. |
| 250 | _a1st ed. 2022. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022. |
|
| 300 |
_aXIV, 461 p. 43 illus., 26 illus. in color. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
||
| 347 |
_atext file _bPDF _2rda |
||
| 505 | 0 | _aPreface -- Introduction -- Sociotechnological systems and associated problems -- Syntax, semantics and mathematical properties of multiset grammars -- Basic algorithmics of multiset grammars and metagrammars -- Resource-consuming sociotechnological systems -- Industrial sociotechnological systems -- Economical sociotechnological systems and economical combinatorics -- Resilience and recovery of sociotechnological systems -- Resource-based games -- Multigrammatical representation of classic problems of operations research -- Interconnections between multiset grammars and models of computation -- Implementation issues and future developments -- Conclusion -- References -- Index -- List of Acronyms. | |
| 520 | _aThis 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, mathematical logic 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. | ||
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 0 | _aExpert systems (Computer science). | |
| 650 | 0 | _aOperations research. | |
| 650 | 0 | _aManagement science. | |
| 650 | 0 | _aBuilding information modeling. | |
| 650 | 0 | _aGame theory. | |
| 650 | 0 | _aMachine theory. | |
| 650 | 1 | 4 | _aArtificial Intelligence. |
| 650 | 2 | 4 | _aKnowledge Based Systems. |
| 650 | 2 | 4 | _aOperations Research, Management Science. |
| 650 | 2 | 4 | _aBuilding Information Modeling. |
| 650 | 2 | 4 | _aGame Theory. |
| 650 | 2 | 4 | _aFormal Languages and Automata Theory. |
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031138577 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031138591 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031138607 |
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-13858-4 |
| 912 | _aZDB-2-SCS | ||
| 912 | _aZDB-2-SXCS | ||
| 942 | _cSPRINGER | ||
| 999 |
_c185207 _d185207 |
||