Illustrateing how to program AI algorithms in Lisp, Prolog, and Java. Topics include: simple production-like system based on logic, logic-based learning, and natural language parsing.

This book, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest.

This book surveys the most important algorithms and data structures in use today. Applications to science, engineering, and industry are a key feature of the book.

This book explores a variety of applications for search methods and techniques in different fields of electrical engineering. By organizing relevant results and apps.

This is your second step to a better understanding of the different types of data structures, focus on lists, hash tables, heaps, priority queues, AVL trees, and B-trees.

This is your first step to a better understanding of the different types of data structures, how they behave, and how to interact with them.

A comprehensive treatment focusing on the creation of efficient data structures and algorithms, using C++.

A comprehensive treatment focusing on the creation of efficient data structures and algorithms, using Java.

This well-organized book takes the reader through the new and rapidly expanding field of genetic algorithms step by step, from a discussion of numerical optimization, to a survey of current extensions to genetic algorithms and applications.

This is a textbook about computer science. It is also about Python. However, there is much more.

This book is an essential, comprehensive reference of Digraphs for students, and researchers in mathematics, operations research and computer science.

This book presents hybrid techniques based on Artificial Neural Network, Fuzzy Sets, Automata Theory, other metaheuristic or classical algorithms, etc.

Integrates contrasting techniques of genetic algorithms, artificial immune systems, particle swarm optimization, and hybrid models to solve many real-world problems.

This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions.

The book describes 45 algorithms from the field of Artificial Intelligence. All algorithm descriptions are complete and consistent to ensure that they are accessible, usable and understandable by a wide audience.

This book is an open set of lecture notes on metaheuristics algorithms, intended for undergraduate students, practitioners, programmers, and other non-experts.

Demonstrates the wide applicability of search algorithms for the purpose of developing useful and practical solutions to problems that arise in a variety of problem domains.

The goal of this book is to provide effective evolutionary algorithms that have been used as an experimental framework within biological evolution and natural selection in the field of artificial life.

This book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers.

This book provides algorithms and ideas for computationalists, whether a working programmer or anyone interested in methods of computation.

This book serves as the primary textbook of choice for any algorithm design course while maintaining its status as the premier practical reference guide to algorithms.

This book uses an index map, a polynomial decomposition, an operator factorization, and a conversion to a filter to develop a very general and efficient description of fast algorithms to calculate the discrete Fourier transform (DFT).

This book is devoted to global optimization algorithms, which are methods to find optimal solutions for given problems.

This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science.

This book is a collection of current research in the application of evolutionary algorithms and other optimal algorithms to solving the TSP problem.

This book covers fundamental, theoretical topics as well as advanced, practical applications of Greedy Algorithms.

This is by far the longest chapter in The Art of Computer Programming, a chapter on combinatorial algorithms that will itself fill four full-sized volumes.

This first fascicle updates The Art of Computer Programming, Vol 1, 3rd Edition: Fundamental Algorithms, and ultimately will become part of the 4th edition of that book.

This book offers techniques with broad applications in linear algebra, signal processing, data mining, computer vision, and statistical analysis.

Provide effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms.

A key factor of this book and its associated implementations is that all algorithms were designed by authors, using the theory of the algorithm in question as a guideline.

The goal of this book is to report original researches on algorithms and applications of Tabu Search to real-world problems.

This book covers many of the hottest area of useful new game theory research, introducing deep new problems, techniques, etc.

This book offers a fresh, compact introduction to the design of traditional data structures in Java.

This is the only book for teaching and referencing of Planning Algorithms in applications including robotics, computational biology, computer graphics, manufacturing, aerospace applications and medicine, etc.

On one level, this is a collection of subroutines, in FORTRAN, for the solution of combinatorial problems.

This textbook introduces Information theory in tandem with applications, alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction.

This is an introductory book on the design and analysis of algorithms. The author uses a careful selection of a few topics to illustrate the tools for algorithm analysis.

This book provides an extensive and varied collection of useful, practical problems on the design, analysis, and verification of algorithms.

This book presents broad and in-depth coverage of the entire field of modern VLSI Design with ordered binary decision diagrams (OBDDs).

It describes methods employed in average case analysis of algorithms, combining both analytical and probabilistic tools in a single volume.

It is the first book that systematically presents the results of work on practical and theoretical algorithmic problems on texts up to the most recent developments in stringology.

The text fully develops an algorithmic approach to Knapsack Problems without losing mathematical rigor.

This is a first-year course in discrete mathematics requireing no calculus or computer programming experience.

This book is the most comprehensive collection of results on polygons currently available and thus earns its place as a standard text in computational geometry.

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