Logics for Computer and Data Sciences, and Artificial Intelligence

This book provides a comprehensive account of logic branches essential for computer science, data science, and artificial intelligence, including propositional, predicate, modal, epistemic, dynamic, temporal, many-valued, and rough logics. It also covers second-order logics and approximate logics and concludes with appendices on set theory, algebraic structures, computability, complexity, MV-algebras, and transition systems.

Format: Paperback / softback
Length: 362 pages
Publication date: 19 December 2022
Publisher: Springer Nature Switzerland AG

This comprehensive volume provides a thorough and systematic exploration of branches of logic that are instrumental in computer science, data science, and artificial intelligence. It delves into various areas of logic, including propositional, predicate, modal, epistemic, dynamic, temporal, many-valued logics, and logics of concepts (rough logics). The book offers a comprehensive overview of second-order logics and approximate logics of parts. Additionally, it includes appendices covering set theory, algebraic structures, computability, complexity, MV-algebras, and transition systems, automata, and formal grammars. By structuring the text in this manner, the reader gains access to a self-contained exposition that serves as a textbook for logics and related disciplines, as well as a valuable reference text.

The study of logic plays a crucial role in these fields as it provides a framework for reasoning, analysis, and the development of algorithms. Logics are used to formalize and validate statements, to prove theorems, and to design and analyze complex systems. They are also used in areas such as natural language processing, computer vision, and machine learning, where they are used to represent and manipulate data and to make decisions based on that data.

The book "Logic for Computer Science, Data Science, and Artificial Intelligence" aims to provide a comprehensive introduction to the various branches of logic that are relevant to these fields. It covers a wide range of topics, including propositional logic, predicate logic, modal logic, epistemic logic, dynamic logic, temporal logic, many-valued logic, rough logic, and second-order logic. Each topic is presented in a clear and concise manner, with examples and exercises to help the reader understand the concepts and apply them to real-world scenarios.

One of the key features of the book is its emphasis on the practical applications of logic. It shows how logic can be used to solve problems in computer science, data science, and artificial intelligence, and how it can be integrated with other fields such as mathematics, computer science, and philosophy. The book also includes a number of case studies and examples that illustrate the use of logic in real-world applications, such as decision-making, natural language processing, and machine learning.

Another important aspect of the book is its accessibility. It is written in a clear and concise language that is easy to understand, and it includes a number of diagrams and illustrations to help the reader visualize the concepts. The book also includes a glossary of terms and a bibliography that provides further resources for the reader who wants to explore the topic in more depth.

In conclusion, "Logic for Computer Science, Data Science, and Artificial Intelligence" is a valuable resource for anyone who wants to learn about the foundations of logic and its applications in these fields. It provides a comprehensive and systematic exploration of the various branches of logic, with a focus on their practical applications. The book is written in a clear and concise language that is accessible to a wide range of readers, and it includes a number of examples and exercises to help the reader understand the concepts and apply them to real-world scenarios. Whether you are a computer scientist, data scientist, or artificial intelligence researcher, this book will be a valuable addition to your library.

Weight: 581g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030916824
Edition number: 1st ed. 2022