Polkowski L. Logics for Computer and Data Sciences, and AI 2022

Textbook in PDF format

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.
Propositional Logic
First-Order Logic
Propositional Modal Logic
Epistemic, Default and Dynamic Logics
Temporal Logics
Many-Valued Logics
Approximate Reasoning: Rough Logics
Beyond First-Order Logics