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: Fouad Sabry
Publisher: One Billion Knowledgeable
ISBN:
Category : Computers
Languages : en
Pages : 111
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Book Description
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.
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: 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: Christopher Thornton
Publisher: New Age International
ISBN: 9788122416619
Category : Artificial intelligence
Languages : en
Pages : 388
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Book Description
This Innovative Book On Artificial Intelligence (Ai) Uses The Unifying Thread Of Search To Bring Together The Major Application And Modeling Techniques That Use Symbolic Ai. Each Of The 11 Chapters Is Divided Into 3 Sections:# Section Which Introduces The Techniques# Section Which Develops A Low-Level (Pop-11) Implementation# Section Which Develops A High-Level (Prolog) ImplementationComprehensive Yet Practical, This Book Will Be Of Great Value To Those Experienced In Ai, As Well As To Students With Some Programming Background And Academics And Professionals Looking For A Precise Discussion Of Ai Through Search.This Special Low-Priced Edition Is For Sale In India, Bangladesh, Bhutan, Maldives, Nepal, Myanmar, Pakistan And Sri Lanka Only.
Author:
Publisher: Elsevier
ISBN: 0443137641
Category : Mathematics
Languages : en
Pages : 260
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Book Description
Artificial Intelligence, Volume 49 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics. Chapters in this new release include AI Teacher-Student based Adaptive Structural Deep Learning Model and Its Estimating Uncertainty of Image Data, Machine-derived Intelligence: Computations Beyond the Null Hypothesis, Object oriented basis of artificial intelligence methodologies I in Judicial Systems in India, Artificial Intelligence in Systems Biology, Machine-Learning in Geometry and Physics, Innovation and Machine Learning: Crowdsourcing Open-Source Natural Language Processing (NLP) Algorithms to Advance Public Health Surveillance, and more. Other chapters cover Learning and identity testing of Markov chains, Data privacy for machine learning and statistics, and The interface between AI and Mathematics. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Handbook of Statistics series - Includes the latest information on Artificial Intelligence
Author: Chandra S.S., Vinod
Publisher: PHI Learning Pvt. Ltd.
ISBN: 938934784X
Category : Computers
Languages : en
Pages : 428
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Book Description
Primarily intended for the undergraduate and postgraduate students of computer science and engineering, this textbook (earlier titled as Artificial Intelligence and Machine Learning), now in its second edition, bridges the gaps in knowledge of the seemingly difficult areas of artificial intelligence. This book promises to provide the most number of case studies and worked-out examples among the books of its genre. The text is written in a highly interactive manner which fulfils the curiosity of any reader. Moreover, the content takes off from the introduction to artificial intelligence, which is followed by explaining about intelligent agents. Various problem-solving strategies, knowledge representation schemes are also included with numerous case studies and applications. Different aspects of learning, nature-inspired learning, along with natural language processing are also explained in depth. The algorithms and pseudo codes for each topic make this book useful for students. Book also throws light into areas like planning, expert system and robotics. Book concludes with futuristic artificial intelligence, which explains the fascinating applications, that the world will witness in coming years. KEY FEATURES • Day-to-day examples and practical representations for deeper understanding of the subject. • Learners can easily implement the AI applications. • Effective and useful case studies and worked-out examples for AI problems. Target Audience • Students of B.E./B.Tech Computer Science Engineering • Students of M.E./M.Tech Computer Science Engineering
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: International Joint Conferences on Artificial Intelligence
Publisher: Morgan Kaufmann
ISBN: 9781558604803
Category : Artificial intelligence
Languages : en
Pages : 1720
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Book Description
Author: Pallab Dasgupta
Publisher: Springer Science & Business Media
ISBN: 9783528057084
Category : Computers
Languages : en
Pages : 150
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Book Description
Solutions to most real-world optimization problems involve a trade-off between multiple conflicting and non-commensurate objectives. Some of the most challenging ones are area-delay trade-off in VLSI synthesis and design space exploration, time-space trade-off in computation, and multi-strategy games. Conventional search techniques are not equipped to handle the partial order state spaces of multiobjective problems since they inherently assume a single scalar objective function. Multiobjective heuristic search techniques have been developed to specifically address multicriteria combinatorial optimization problems. This text describes the multiobjective search model and develops the theoretical foundations of the subject, including complexity results . The fundamental algorithms for three major problem formulation schemes, namely state-space formulations, problem-reduction formulations, and game-tree formulations are developed with the support of illustrative examples. Applications of multiobjective search techniques to synthesis problems in VLSI, and operations research are considered. This text provides a complete picture on contemporary research on multiobjective search, most of which is the contribution of the authors.
