Logic for Computer Science and Artificial Intelligence (PDF)

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.