Logics for Computer and Data Sciences, and Artificial Intelligence

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.

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

Klappentext

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.

Inhalt
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.