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Logics for Computer and Data Sciences, and Artificial Intelligence
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Logics for Computer and Data Sciences, and Artificial Intelligence/ by Lech T. Polkowski.
Author:
Polkowski, Lech T.
Description:
XVIII, 362 p. 31 illus.online resource. :
Contained By:
Springer Nature eBook
Subject:
Computational intelligence. -
Online resource:
https://doi.org/10.1007/978-3-030-91680-0
ISBN:
9783030916800
Logics for Computer and Data Sciences, and Artificial Intelligence
Polkowski, Lech T.
Logics for Computer and Data Sciences, and Artificial Intelligence
[electronic resource] /by Lech T. Polkowski. - 1st ed. 2022. - XVIII, 362 p. 31 illus.online resource. - Studies in Computational Intelligence,9921860-9503 ;. - Studies in Computational Intelligence,564.
Propositional logic -- First-order logic -- Propositional modal logic -- Epistemic, default and dynamic logics -- Temporal logics -- Many-valued logics -- Approximate reasoning: Rough logics -- Beyond frst-order logics.
This volume offers the reader a systematic and throughout account of branches of logic instrumental for computer science, data science and artificial intelligence. Addressed in it are propositional, predicate, modal, epistemic, dynamic, temporal logics as well as applicable in data science many-valued logics and logics of concepts (rough logics). It offers a look into second-order logics and approximate logics of parts. The book concludes with appendices on set theory, algebraic structures, computability, complexity, MV-algebras and transition systems, automata and formal grammars. By this composition of the text, the reader obtains a self-contained exposition that can serve as the textbook on logics and relevant disciplines as well as a reference text. .
ISBN: 9783030916800
Standard No.: 10.1007/978-3-030-91680-0doiSubjects--Topical Terms:
568984
Computational intelligence.
LC Class. No.: Q342
Dewey Class. No.: 006.3
Logics for Computer and Data Sciences, and Artificial Intelligence
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This volume offers the reader a systematic and throughout account of branches of logic instrumental for computer science, data science and artificial intelligence. Addressed in it are propositional, predicate, modal, epistemic, dynamic, temporal logics as well as applicable in data science many-valued logics and logics of concepts (rough logics). It offers a look into second-order logics and approximate logics of parts. The book concludes with appendices on set theory, algebraic structures, computability, complexity, MV-algebras and transition systems, automata and formal grammars. By this composition of the text, the reader obtains a self-contained exposition that can serve as the textbook on logics and relevant disciplines as well as a reference text. .
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Intelligent Technologies and Robotics (R0) (SpringerNature-43728)
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