This edition emphasizes several new themes. The most important of these is the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming, lazy evaluation, and nondeterministic programming.
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Written by two of the leading researchers in the area, this engaging and accessible book is unique in covering the diverse foundations of multiagent systems, including logic. Its extensive treatment of the interplay between computer science and game theory will define how the subject should be taught.
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This book emphasizes two important areas. First, it reviews the framework within which computer science and the study of algorithms and data structures must fit, in particular, the reasons why we need to study these topics and how understanding these topics helps us to become better problem solvers. Second, we review the Python programming language.
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This book is meant to provide an introduction to vectors, matrices, and least squares methods, basic topics in applied linear algebra. Our goal is to give the beginning student, with little or no prior exposure to linear algebra, a good grounding in the basic ideas, as well as an appreciation for how they are used in many applications.
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This book teaches two different sorts of things, woven together. It teaches you how to read and write mathematical proofs. It provides a survey of basic mathematical objects, notation, and techniques which will be useful in later computer science courses. These include propositional and predicate logic, sets, functions, relations, modular arithmetic, counting, graphs, and trees.
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No, this book won’t turn anyone into a master painter. But, we would not have spent fifteen years writing this edition if we didn’t believe that everyone can design programs and everyone can experience the satisfaction that comes with creative design.
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This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. Designed as a textbook for graduate-level algorithms courses, the book will also serve as a reference for researchers who are interested in the heuristic solution of discrete optimization problems.
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Practical Common Lisp serves as a useful introduction to Common Lisp for folks who are curious about Lisp but maybe not yet curious enough to shell out big bucks for a dead-tree book and a good Common Lisp tutorial for folks who want to get down to real coding right away.
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