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Author: Leveen Kanal
Publisher: Springer Science & Business Media
ISBN: 1461387884
Category : Computers
Languages : en
Pages : 491
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Book Description
Search is an important component of problem solving in artificial intelligence (AI) and, more generally, in computer science, engineering and operations research. Combinatorial optimization, decision analysis, game playing, learning, planning, pattern recognition, robotics and theorem proving are some of the areas in which search algbrithms playa key role. Less than a decade ago the conventional wisdom in artificial intelligence was that the best search algorithms had already been invented and the likelihood of finding new results in this area was very small. Since then many new insights and results have been obtained. For example, new algorithms for state space, AND/OR graph, and game tree search were discovered. Articles on new theoretical developments and experimental results on backtracking, heuristic search and constraint propaga tion were published. The relationships among various search and combinatorial algorithms in AI, Operations Research, and other fields were clarified. This volume brings together some of this recent work in a manner designed to be accessible to students and professionals interested in these new insights and developments.
Author: Leveen Kanal
Publisher: Springer Science & Business Media
ISBN: 1461387884
Category : Computers
Languages : en
Pages : 491
Get Book Here
Book Description
Search is an important component of problem solving in artificial intelligence (AI) and, more generally, in computer science, engineering and operations research. Combinatorial optimization, decision analysis, game playing, learning, planning, pattern recognition, robotics and theorem proving are some of the areas in which search algbrithms playa key role. Less than a decade ago the conventional wisdom in artificial intelligence was that the best search algorithms had already been invented and the likelihood of finding new results in this area was very small. Since then many new insights and results have been obtained. For example, new algorithms for state space, AND/OR graph, and game tree search were discovered. Articles on new theoretical developments and experimental results on backtracking, heuristic search and constraint propaga tion were published. The relationships among various search and combinatorial algorithms in AI, Operations Research, and other fields were clarified. This volume brings together some of this recent work in a manner designed to be accessible to students and professionals interested in these new insights and developments.
Author: Stuart Russell
Publisher: Createspace Independent Publishing Platform
ISBN: 9781537600314
Category :
Languages : en
Pages : 626
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Book Description
Artificial Intelligence: A Modern Approach offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.
Author: David Kopec
Publisher: Simon and Schuster
ISBN: 1638355231
Category : Computers
Languages : en
Pages : 331
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Book Description
"Whether you're a novice or a seasoned professional, there's an Aha! moment in this book for everyone." - James Watson, Adaptive ”Highly recommended to everyone interested in deepening their understanding of Python and practical computer science.” —Daniel Kenney-Jung, MD, University of Minnesota Key Features • Master formal techniques taught in college computer science classes • Connect computer science theory to real-world applications, data, and performance • Prepare for programmer interviews • Recognize the core ideas behind most “new” challenges • Covers Python 3.7 Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About The Book Programming problems that seem new or unique are usually rooted in well-known engineering principles. Classic Computer Science Problems in Python guides you through time-tested scenarios, exercises, and algorithms that will prepare you for the “new” problems you’ll face when you start your next project. In this amazing book, you'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. As you work through examples for web development, machine learning, and more, you'll remember important things you've forgotten and discover classic solutions that will save you hours of time. What You Will Learn • Search algorithms • Common techniques for graphs • Neural networks • Genetic algorithms • Adversarial search • Uses type hints throughout This Book Is Written For For intermediate Python programmers. About The Author David Kopec is an assistant professor of Computer Science and Innovation at Champlain College in Burlington, Vermont. He is the author of Dart for Absolute Beginners (Apress, 2014), Classic Computer Science Problems in Swift (Manning, 2018), and Classic Computer Science Problems in Java (Manning, 2020) Table of Contents 1. Small problems 2. Search problems 3. Constraint-satisfaction problems 4. Graph problems 5. Genetic algorithms 6. K-means clustering 7. Fairly simple neural networks 8. Adversarial search 9. Miscellaneous problems
Author: Stefan Edelkamp
Publisher: Elsevier
ISBN: 0080919731
Category : Computers
Languages : en
Pages : 865
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Book Description
Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constraint satisfaction and machine learning. While no previous familiarity with heuristic search is necessary the reader should have a basic knowledge of algorithms, data structures, and calculus. Real-world case studies and chapter ending exercises help to create a full and realized picture of how search fits into the world of artificial intelligence and the one around us. - Provides real-world success stories and case studies for heuristic search algorithms - Includes many AI developments not yet covered in textbooks such as pattern databases, symbolic search, and parallel processing units
Author: Judea Pearl
Publisher: Addison Wesley Publishing Company
ISBN:
Category : Computers
Languages : en
Pages : 406
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Book Description
Problem-solving strartegies and the nature of Heuristic informatio n.Heuristics and problem representations. Basic Heuristic-Search procedures. Formal properties of Heuristic methods. Heuristics viewed as information provided by simplified models. Performance analysis of Heuristic methods. Abstract models for quantitative performace analysis. Complexity versus precision of admissible Heuristics. Searching with nonadmissible Heuristics. Game-playing programs. Strategies and models for game-playing programs. Performace analysis for game-searching strategies. Decision quality in game searching. Bibliography. Index.
Author: Weixiong Zhang
Publisher: Springer Science & Business Media
ISBN: 1461215382
Category : Computers
Languages : en
Pages : 215
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Book Description
This book is particularly concerned with heuristic state-space search for combinatorial optimization. Its two central themes are the average-case complexity of state-space search algorithms and the applications of the results notably to branch-and-bound techniques. Primarily written for researchers in computer science, the author presupposes a basic familiarity with complexity theory, and it is assumed that the reader is familiar with the basic concepts of random variables and recursive functions. Two successful applications are presented in depth: one is a set of state-space transformation methods which can be used to find approximate solutions quickly, and the second is forward estimation for constructing more informative evaluation functions.
Author: Youssef Hamadi
Publisher: Springer
ISBN: 3319635166
Category : Computers
Languages : en
Pages : 687
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Book Description
This is the first book presenting a broad overview of parallelism in constraint-based reasoning formalisms. In recent years, an increasing number of contributions have been made on scaling constraint reasoning thanks to parallel architectures. The goal in this book is to overview these achievements in a concise way, assuming the reader is familiar with the classical, sequential background. It presents work demonstrating the use of multiple resources from single machine multi-core and GPU-based computations to very large scale distributed execution platforms up to 80,000 processing units. The contributions in the book cover the most important and recent contributions in parallel propositional satisfiability (SAT), maximum satisfiability (MaxSAT), quantified Boolean formulas (QBF), satisfiability modulo theory (SMT), theorem proving (TP), answer set programming (ASP), mixed integer linear programming (MILP), constraint programming (CP), stochastic local search (SLS), optimal path finding with A*, model checking for linear-time temporal logic (MC/LTL), binary decision diagrams (BDD), and model-based diagnosis (MBD). The book is suitable for researchers, graduate students, advanced undergraduates, and practitioners who wish to learn about the state of the art in parallel constraint reasoning.
Author: John Adrian Bondy
Publisher: London : Macmillan Press
ISBN:
Category : Mathematics
Languages : en
Pages : 290
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Book Description
Author: M. Tim Jones
Publisher: Jones & Bartlett Learning
ISBN: 9781449631154
Category : Computers
Languages : en
Pages : 522
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Book Description
This book offers students and AI programmers a new perspective on the study of artificial intelligence concepts. The essential topics and theory of AI are presented, but it also includes practical information on data input & reduction as well as data output (i.e., algorithm usage). Because traditional AI concepts such as pattern recognition, numerical optimization and data mining are now simply types of algorithms, a different approach is needed. This “sensor / algorithm / effecter” approach grounds the algorithms with an environment, helps students and AI practitioners to better understand them, and subsequently, how to apply them. The book has numerous up to date applications in game programming, intelligent agents, neural networks, artificial immune systems, and more. A CD-ROM with simulations, code, and figures accompanies the book.
Author: Sherenaz W. Al-Haj Baddar
Publisher: Springer Science & Business Media
ISBN: 1461418518
Category : Computers
Languages : en
Pages : 132
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Book Description
Designing Sorting Networks: A New Paradigm provides an in-depth guide to maximizing the efficiency of sorting networks, and uses 0/1 cases, partially ordered sets and Haase diagrams to closely analyze their behavior in an easy, intuitive manner. This book also outlines new ideas and techniques for designing faster sorting networks using Sortnet, and illustrates how these techniques were used to design faster 12-key and 18-key sorting networks through a series of case studies. Finally, it examines and explains the mysterious behavior exhibited by the fastest-known 9-step 16-key network. Designing Sorting Networks: A New Paradigm is intended for advanced-level students, researchers and practitioners as a reference book. Academics in the fields of computer science, engineering and mathematics will also find this book invaluable.
