Название: Logic: Reference Book for Computer Scientists: The 2nd Revised, Modified, and Enlarged Edition of “Logics for Computer and Data Sciences, and Artificial Intelligence”
Автор: Lech T. Polkowski
Издательство: Springer
Год: 2023
Страниц: 489
Язык: английский
Формат: pdf (true), epub
Размер: 33.0 MB

The book gives all interested in Computer Science, a deep review of relevant aspects of logic. In its scope are classical and non-classical logics. The content will be valid as well for those interested in linguistic, philosophy and many other areas of research both in humane and technical branches of science as logic permeates all genuine realms of science. The book contains a substantial part of classical results in logic like those by Godel, Tarski, Church and Rosser as well as later developments like many-valued logics, logics for knowledge engineering, first-order logics plus inductive definitions.

The exposition is rigorous yet without unnecessary abstractionism, so it should be accessible to readers from many disciplines of science. Each chapter contains a problem section, and problems are borrowed from research publications which allows for passing additional information, and it allows readers to test their skills. Extensive bibliography of 270 positions directs readers to research works of importance.

This book concentrates on the presentation of the basic domains of logic which have a great importance for the contemporary state of development of Computer Science (CS) and Artificial Intelligence (AI). This concerns, e.g., application of logic as a very important tool for expressing concepts on which different forms of reasoning can be performed, deep characterization of computational complexity of many different important problems in CS and AI as well as application of Boolean reasoning in different domains of CS and AI.

Moreover, the book also covers theoretical issues which yet have not been considered in the scope of CS or AI applications. Exploiting these issues more may lead to the discovery of new technologies. It is worthwhile mentioning that researchers in AI are gradually discovering the usefulness of advanced tools related to different branches of advanced mathematics and logic, e.g., topology and reasoning in solving the advanced problems related to Machine Learning. One can also observe that nowadays there is also an important call to logicians, especially from AI, for developing new reasoning tools based on the relevant computing model necessary for solving challenges, related to, e.g., Intelligent Systems dealing with complex phenomena.

The material is presented in a very condensed and precise way. This concerns the whole book starting from the preliminary chapter which can serve as a basis for a quite a few courses for graduate and Ph.D. students from CS and AI. It should be also noted that all theorems are presented together with the detailed proofs.




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