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Uncertainty Quantification and Uncertainty Propagation under Traditional and AI-Based Data Processing (and Related Topics): Legacy of Grigory Tseytin -

Uncertainty Quantification and Uncertainty Propagation under Traditional and AI-Based Data Processing (and Related Topics): Legacy of Grigory Tseytin

Buch | Hardcover
X, 290 Seiten
2026
Springer International Publishing (Verlag)
978-3-032-16493-3 (ISBN)
CHF 299,55 inkl. MwSt
  • Noch nicht erschienen - erscheint am 30.03.2026
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Why revisit uncertainty? Data processing is now often performed by Large Language Models (LLMs) and other AI tools that use natural-language texts. Many LLMs' results are spectacular, but often, there is no good indication of their accuracy. We need to revisit traditional methods for quantifying and propagating uncertainty, to see how they can help with these new challenges.

The book covers uncertainty of measurement results and uncertainty inherent in natural-languages text -- by using both linguistic and traditional AI techniques (e.g., fuzzy). It contains both general results -- e.g., what can be computed -- and applications to engineering, physics, chemistry, and education. It also analyzes the effect of emerging computing paradigms -- such as quantum computing -- on uncertainty-related computations.

This book can be recommended to everyone -- from students to researchers -- who is eager to learn, apply, and improve the uncertainty-related techniques.

.- Introduction.- C Wigner's Quasidistribution and Dirac's Kets.- C G. S. Tseytin's Seven-Relation Semigroup with Undecidable Word Problem.- Translation of the paper An associative calculus with unsolvable equivalence problem by G. S. Tseytin, etc.

Erscheint lt. Verlag 30.3.2026
Reihe/Serie Studies in Systems, Decision and Control
Zusatzinfo X, 290 p.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik Elektrotechnik / Energietechnik
Schlagworte Computational Intelligence • Grigory Tseytin • Uncertainty • uncertainty propagation • uncertainty quantification
ISBN-10 3-032-16493-1 / 3032164931
ISBN-13 978-3-032-16493-3 / 9783032164933
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
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