Overview
- A comprehensive treatise of various logics, notably those that are of relevance for computer and data science
- Covers basic issues concerning different logical systems, e.g. propositional logic
- Includes the proofs of the main theories Augmented with about 280 problems
Part of the book series: Studies in Computational Intelligence (SCI, volume 992)
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Table of contents (8 chapters)
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Logics for Computer and Data Sciences, and Artificial Intelligence
Authors: Lech T. Polkowski
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-91680-0
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-91679-4Published: 18 December 2021
Softcover ISBN: 978-3-030-91682-4Published: 19 December 2022
eBook ISBN: 978-3-030-91680-0Published: 01 January 2022
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVIII, 362
Number of Illustrations: 31 b/w illustrations
Topics: Computational Intelligence, Data Engineering, Artificial Intelligence