Hardback (ISBN-13: 9780521888240)
43 line figures
Page extent: 288 pages
Size: 253 x 177 mm
This book is concerned with partial differential equations applied to fluids problems in science and engineering and is designed for two potential audiences. First, this book can function as a text for a course in mathematical methods in fluid mechanics in non-mathematics departments or in mathematics service courses. The authors have taught both. Second, this book is designed to help provide serious readers of journals (professionals, researchers, and graduate students) in analytical science and engineering with tools to explore and extend the missing steps in an analysis. The topics chosen for the book are those that the authors have found to be of considerable use in their own research careers. These topics are applicable in many areas, such as aeronautics and astronautics; biomechanics; chemical, civil, and mechanical engineering; fluid mechanics; and geophysical flows. Continuum ideas arise in other contexts, and the techniques included have applications there as well.
* Unique unified presentation of most recent results coming from experiments,
numerical simulations and theoretical analysis * Unique discussion of advanced
linear and nonlinear theories/models * Deep analysis of the main remaining
open problems
1. Review of analytic function theory; 2. Special functions; 3. Eigenvalue problems and eigenfunction expansions; 4. Green’s functions for boundary-value problems; 5. Laplace transform methods; 6. Fourier transform methods; 7. Particular physical problems; 8. Asymptotic expansions of integrals.
Hardback (ISBN-13: 9780521898850)
10 line figures 1 table 55 exercises 50 worked examples
Page extent: 360 pages
Size: 222 x 152 mm
Combinatory logic and lambda-calculus, originally devised in the 1920s, have since developed into linguistic tools, especially useful in programming languages. The authors’ previous book served as the main reference for introductory courses on lambda-calculus for over 20 years: this long-awaited new version is thoroughly revised and offers a fully up-to-date account of the subject, with the same authoritative exposition. The grammar and basic properties of both combinatory logic and lambda-calculus are discussed, followed by an introduction to type-theory. Typed and untyped versions of the systems, and their differences, are covered. Lambda-calculus models, which lie behind much of the semantics of programming languages, are also explained in depth. The treatment is as non-technical as possible, with the main ideas emphasized and illustrated by examples. Many exercises are included, from routine to advanced, with solutions to most at the end of the book.
* The authors' 1986 version of this book is widely recognised as the best
introduction to these topics for the reader with some previous experience
of logic; this version builds and updates that framework * Accessible and
clear: a non-technical treatment of the subject with the main ideas emphasized
and illustrated by examples * Exercises are designed to give practice to
beginners and range from elementary to advanced, with solutions to most
found at the end of the book
Preface; 1. The λ-calculus; 2. Combinatory logic; 3. The power of λ and CL; 4. Computable functions; 5. Undecidability; 6. Formal theories; 7. Extensionality in λ-calculus; 8. Extensionality in CL; 9. Correspondence between λ and CL; 10. Simple typing, Church-style; 11. Simple typing, Curry-style in CL; 12. Simple typing, Curry-style in λ; 13. Generalizations of typing; 14. Models of CL; 15. Models of λ ; 16. Scott’s D∞ and other models; Appendix A1. α-conversion; Appendix A2. Confluence proofs; Appendix A3. Normalization proofs; Appendix A4. Care of your pet combinator; Appendix A5. Answers to starred exercises; Bibliography; Index.
Hardback (ISBN-13: 9780521865715)
5 halftones 47 tables 263 exercises
Page extent: 480 pages
Size: 253 x 177 mm
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book’s supporting website to help course instructors prepare their lectures.
* Introduces all key concepts, requiring little prior knowledge * All concepts
are illustrated with figures and examples * Supporting web site features
lecture slides that follow the book, and a solutions manual for lecturers
1. Information retrieval using the Boolean model; 2. The dictionary and postings lists; 3. Tolerant retrieval; 4. Index construction; 5. Index compression; 6. Scoring and term weighting; 7. Vector space retrieval; 8. Evaluation in information retrieval; 9. Relevance feedback and query expansion; 10. XML retrieval; 11. Probabilistic information retrieval; 12. Language models for information retrieval; 13. Text classification and Naive Bayes; 14. Vector space classification; 15. Support vector machines and kernel functions; 16. Flat clustering; 17. Hierarchical clustering; 18. Dimensionality reduction and latent semantic indexing; 19. Web search basics; 20. Web crawling and indexes; 21. Link analysis.
Hardback (ISBN-13: 9780521899437)
14 tables
Page extent: 480 pages
Size: 253 x 177 mm
Multiagent systems combine multiple autonomous entities, each having diverging interests or different information. This overview of the field offers a computer science perspective, but also draws on ideas from game theory, economics, operations research, logic, philosophy and linguistics. It will serve as a reference for researchers in each of these fields, and be used as a text for advanced undergraduate or graduate courses. The authors emphasize foundations to create a broad and rigorous treatment of their subject, with thorough presentations of distributed problem solving, game theory, multiagent communication and learning, social choice, mechanism design, auctions, cooperative game theory, and modal logics of knowledge and belief. For each topic, basic concepts are introduced, examples are given, proofs of key results are offered, and algorithmic considerations are examined. An appendix covers background material in probability theory, classical logic, Markov decision processes and mathematical programming.
* First rigorous introduction covering multiagent systems * Covers broad
area including computer science, game theory, and logic * Does not require
knowledge beyond typical undergraduate study and offers background material
for probability theory, classical logic, and mathematical programming
1. Distributed constraint satisfaction; 2. Distributed optimization; 3. Introduction to non-cooperative game theory; 4. Computing solution concepts of normal-form games; 5. Games with sequential actions; 6. Richer representations; 7. Learning and teaching; 8. Communication; 9. Aggregating preferences; 10. Protocols for strategic agents; 11. Protocols for multiagent resource allocation; 12. Teams of selfish agents; 13. Logics of knowledge and belief; 14. Beyond belief.