This text covers all the material essential to an introductory theory of computation course for undergraduate students. The text has a solid mathematical base, and provides precise mathematical statements of theorems and definitions, giving an intuitive motivation for constructions and proofs. Proofs and arguments are clearly stated, without excessive mathematical detail, to help students understand the basic principles. The text is illustrated with integrated examples of new concepts as well as an abundance of exercises to aid in the development of problem solving skills.

   "These two volumes must be regarded as a landmark in algebraical literature. The enormous wealth of material, the depth of treatment, and the masterly exposition render these volumes exceptionally valuable. All courses on algebra, from the second undergraduate year to the specialist studies for doctoral students, can benefit from this authoritative treatise by Professor Jacobson." Walter Ledermann, University of Sussex Volume1

   This book should be of interest to graduates.

   "I recommend this book highly, it is beautifully done..." -- Robert Aumann, Hebrew University

A Course in Game Theory presents the main ideas of game theory at a level suitable for graduate students and advanced undergraduates, emphasizing the theory's foundations and interpretations of its basic concepts. The authors provide precise definitions and full proofs of results, sacrificing generalities and limiting the scope of the material in order to do so. The text is organized in four parts: strategic games, extensive games with perfect information, extensive games with imperfect information, and coalitional games. It includes over 100 exercises. More about this book

   In one of the finest treatments for upper undergraduate and graduate level students, Professor Suppes presents axiomatic set theory: the basic paradoxes and history of set theory, and advanced topics such as relations and functions, equipollence, finite sets and cardinal numbers, rational and real numbers and more. Exercises. References. Indexes.

   Category theory is a branch of pure mathematics that is becoming an increasingly important tool in theoretical computer science, especially in programming language semantics, domain theory, and concurrency, where it is already a standard language of discourse. Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Four case studies illustrate applications of category theory to programming language design, semantics, and the solution of recursive domain equations. A brief literature survey offers suggestions for further study in more advanced texts. Benjamin C. Pierce received his doctoral degree from Carnegie Mellon University.

Contents: Tutorial. Applications. Further Reading.

   This paperback edition is not available in the U.S. and Canada.

There are books on algorithms that are rigorous but incomplete and others that cover masses of material but lack rigor. Introduction to Algorithms combines rigor and comprehensiveness.

The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

The first edition became the standard reference for professionals and a widely used text in universities worldwide. The second edition features new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming, as well as extensive revisions to virtually every section of the book. In a subtle but important change, loop invariants are introduced early and used throughout the text to prove algorithm correctness. Without changing the mathematical and analytic focus, the authors have moved much of the mathematical foundations material from Part I to an appendix and have included additional motivational material at the beginning.

   This book is designed for use by students with a wide range of ability and maturity. The stronger the students, the harder the exercises that can be assigned. The book can be used for one-quarter, two-quarter, or one-semester course depending on how much material is used.
Combinatorical reasoning underlies all analysis of computer systems. It plays a similar role in discrete operations research problems and in finite probability. This book teaches students in the mathematical sciences how to reason and model combinatorically. It seeks to develop proficiency in basic discrete math problem solving in the way that a calculus textbook develops proficiency in basic analysis problem solving.
The three principle aspects of combinatorical reasoning emphasized in this book are: the systematic analysis of different possibilities, the exploration of the logical structure of a problem (e.g. finding manageable subpieces or first solving the problem with three objects instead of n), and ingenuity. Although important uses of combinatorics in computer science, operations research, and finite probability are mentioned, these applications are often used solely for motivation. Numerical examples involving the same concepts use more interesting settings such as poker probabilities or logical games.

   This work makes available to readers without specialized training in mathematics complete proofs of the fundamental metatheorems of standard (i.e., basically truth-functional) first order logic. Included is a complete proof, accessible to non-mathematicians, of the undecidability of first order logic, the most important fact about logic to emerge from the work of the last half-century. Hunter explains concepts of mathematics and set theory along the way for the benefit of non-mathematicians. He also provides ample exercises with comprehensive answers.

   Everything is a symbol, and symbols can combine to form patterns. Patterns are beautiful and revelatory of larger truths. These are the central ideas in the thinking of Kurt Gödel, M.C. Escher, and Johann Sebastian Bach, perhaps the three greatest minds of the past quarter-millennium. In a stunning work of humanism, Hofstadter ties together the work of mathematician Gödel, graphic artist Escher, and composer Bach.

Gödel, Escher, Bach, a Pulitzer prize-winning treatise on genius, explores the workings of brilliant people's brains with the help of historical examples and brainteaser puzzles. Not for the dim or the lazy, this book shows you, more clearly than most any other, what it means to see symbols and patterns where others see only the universe. Touching on math, computers, literature, music, and artificial intelligence, Gödel, Escher, Bach is a challenging and potentially life-changing piece of writing.