Springer Logics for Computer and Data Sciences, and Artificial Intelligence: 992 (Studies in Computational Intelligence, 992)

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.  From the Back Cover 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.