Book description
Logic and its components (propositional, first-order, non-classical)
play a key role in Computer Science and Artificial Intelligence. While a
large amount of information exists scattered throughout various media
(books, journal articles, webpages, etc.), the diffuse nature of these
sources is problematic and logic as a topic benefits from a unified
approach. Logic for Computer Science and Artificial Intelligence
utilizes this format, surveying the tableaux, resolution, Davis and
Putnam methods, logic programming, as well as for example unification
and subsumption. For non-classical logics, the translation method is detailed.
Logic for Computer Science and Artificial Intelligence is the
classroom-tested result of several years of teaching at Grenoble INP
(Ensimag). It is conceived to allow self-instruction for a beginner with
basic knowledge in Mathematics and Computer Science, but is also highly
suitable for use in traditional courses. The reader is guided by clearly
motivated concepts, introductions, historical remarks, side notes
concerning connections with other disciplines, and numerous exercises,
complete with detailed solutions, The title provides the reader with the
tools needed to arrive naturally at practical implementations of the
concepts and techniques discussed, allowing for the design of algorithms
to solve problems.
