State-Space Search
State-Space Search

Author: Weixiong Zhang

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 215

ISBN-13: 1461215382

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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.

State Space Search
State Space Search

Author: Fouad Sabry

Publisher: One Billion Knowledgeable

Published: 2023-06-28

Total Pages: 111

ISBN-13:

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What Is State Space Search State space search is a technique that is employed in the field of computer science, particularly artificial intelligence (AI), in which consecutive configurations or states of an instance are explored, with the objective of finding a goal state with the desired feature. The term "state space search" comes from the phrase "state space," which refers to the space in which the process takes place. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: State Space Search Chapter 2: Brute-Force Search Chapter 3: Heuristic in Computer Science Chapter 4: Local Search Optimization Chapter 5: Game Tree Chapter 6: Constraint Satisfaction Problem Chapter 7: Adversarial Search Chapter 8: Markov Decision Process Chapter 9: Reinforcement Learning Chapter 10: Combinatorial search (II) Answering the public top questions about state space search. (III) Real world examples for the usage of state space search in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of state space search' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of state space search.

Heuristic Search
Heuristic Search

Author: Stefan Edelkamp

Publisher: Elsevier

Published: 2011-05-31

Total Pages: 865

ISBN-13: 0080919731

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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

State Space Grids
State Space Grids

Author: Tom Hollenstein

Publisher: Springer Science & Business Media

Published: 2012-10-28

Total Pages: 135

ISBN-13: 1461450071

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Human development from birth through adulthood is a complex interplay of many interacting forces. Children’s internal processes are manifest in behaviors that are sculpted by their experiences, most notably with primary caregivers. Because the discipline of psychology explores human behavior and cognition, the techniques employed for developmental analysis must be able to describe, depict, and quantify these complex processes. State Space Grids provides the framework, basic method, rationale, and advanced techniques for translating the behavior of children, adolescents, and parents into visible, traceable data. This seminar-between-covers takes readers step by step from conceptualization through implementation of projects, with examples from a range of current research within and outside child development. Links are included for the GridWare software program and related user resources. And although state space grids need not be used only to analyze dynamic systems, they serve as an excellent tool for honing systemic thinking. Key coverage in this volume includes: Dynamic systems and the origins of state space grids. The state of research using state space grids. Introducing GridWare and how it works. How to use state space grids, from idea through finished project. Within-grid and between-grid analysis. Conducting advanced analysis. State Space Grids is an essential reference for researchers across such disciplines as psychology, neuroscience, economics, computer science, and agricultural science.

Search in Artificial Intelligence
Search in Artificial Intelligence

Author: Leveen Kanal

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 491

ISBN-13: 1461387884

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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.

Artificial Intelligence Through Search
Artificial Intelligence Through Search

Author: Christopher James Thornton

Publisher: Intellect (UK)

Published: 1992

Total Pages: 388

ISBN-13:

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This is an important textbook on artificial intelligence that uses the unifying thread of search to bring together most of the major techniques used in symbolic artificial intelligence. The authors, aware of the pitfalls of being too general or too academic, have taken a practical approach in that they include program code to illustrate their ideas. Furthermore, code is offered in both POP-11 and Prolog, thereby giving a dual perspective, highlighting the merits of these languages. Each chapter covers one technique and divides up into three sections: a section which introduces the technique (and its usual applications) andsuggests how it can be understood as a variant/generalisation of search; a section which developed a `low'-level (POP-11) implementation; a section which develops a high-level (Prolog) implementation of the technique. The authors also include useful notes on alternative treatments to the material, further reading and exercises. As a practical book it will be welcomed by a wide audience including, those already experienced in AI, students with some background in programming who are taking an introductory course in AI, and lecturers looking for a precise, professional and practical text book to use in their AI courses.

Modern Control: State-Space Analysis and Design Methods
Modern Control: State-Space Analysis and Design Methods

Author: Arie Nakhmani

Publisher: McGraw Hill Professional

Published: 2020-05-01

Total Pages: 192

ISBN-13: 126045925X

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Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Apply a state-space approach to modern control system analysis and design Written by an expert in the field, this concise textbook offers hands-on coverage of modern control system engineering. Modern Control: State-Space Analysis and Design Methods features start-to-finish design projects as well as online snippets of MATLAB code with simulations. The essential mathematics are presented along with fully worked-out examples in gradually increasing degrees of difficulty. Readers will receive “just-in-time” math background from a comprehensive appendix and get step-by-step descriptions of the latest analysis and design techniques. Coverage includes: • An introduction to control systems • State-space representations • Pole placement via state feedback • State estimators (observers) • Non-minimal canonical forms • Linearization • Lyapunov stability • Linear quadratic regulators (LQR) • Symmetric root locus (SRL) • Kalman filter • Linear quadratic gaussian control (LQG)

Fundamentals of Artificial Intelligence
Fundamentals of Artificial Intelligence

Author: K.R. Chowdhary

Publisher: Springer Nature

Published: 2020-04-04

Total Pages: 730

ISBN-13: 8132239725

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Fundamentals of Artificial Intelligence introduces the foundations of present day AI and provides coverage to recent developments in AI such as Constraint Satisfaction Problems, Adversarial Search and Game Theory, Statistical Learning Theory, Automated Planning, Intelligent Agents, Information Retrieval, Natural Language & Speech Processing, and Machine Vision. The book features a wealth of examples and illustrations, and practical approaches along with the theoretical concepts. It covers all major areas of AI in the domain of recent developments. The book is intended primarily for students who major in computer science at undergraduate and graduate level but will also be of interest as a foundation to researchers in the area of AI.

Stochastic Local Search
Stochastic Local Search

Author: Holger H. Hoos

Publisher: Morgan Kaufmann

Published: 2005

Total Pages: 678

ISBN-13: 1558608729

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Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems. Offering a systematic treatment of SLS algorithms, this book examines the general concepts and specific instances of SLS algorithms and considers their development, analysis and application.