Search In Artificial Intelligence
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Search Methods For Artificial Intelligence
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Author : Leonard Bolc
language : en
Publisher:
Release Date : 1992
Search Methods For Artificial Intelligence written by Leonard Bolc and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Computers categories.
This book contains a description of modern search methods that are in use mainly in the field of computer science, though with special stress on artificial intelligence, and go so far as to discuss practical application.
The Dictionary Of Artificial Intelligence
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Author : Utku Taşova
language : en
Publisher: Entropol
Release Date : 2023-11-03
The Dictionary Of Artificial Intelligence written by Utku Taşova and has been published by Entropol this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-03 with Computers categories.
Unveiling the Future: Your Portal to Artificial Intelligence Proficiency In the epoch of digital metamorphosis, Artificial Intelligence (AI) stands as the vanguard of a new dawn, a nexus where human ingenuity intertwines with machine precision. As we delve deeper into this uncharted realm, the boundary between the conceivable and the fantastical continually blurs, heralding a new era of endless possibilities. The Dictionary of Artificial Intelligence, embracing a compendium of 3,300 meticulously curated titles, endeavors to be the torchbearer in this journey of discovery, offering a wellspring of knowledge to both the uninitiated and the adept. Embarking on the pages of this dictionary is akin to embarking on a voyage through the vast and often turbulent seas of AI. Each entry serves as a beacon, illuminating complex terminologies, core principles, and the avant-garde advancements that characterize this dynamic domain. The dictionary is more than a mere compilation of terms; it's a labyrinth of understanding waiting to be traversed. The Dictionary of Artificial Intelligence is an endeavor to demystify the arcane, to foster a shared lexicon that enhances collaboration, innovation, and comprehension across the AI community. It's a mission to bridge the chasm between ignorance and insight, to unravel the intricacies of AI that often seem enigmatic to the outsiders. This profound reference material transcends being a passive repository of terms; it’s an engagement with the multifaceted domain of artificial intelligence. Each title encapsulated within these pages is a testament to the audacity of human curiosity and the unyielding quest for advancement that propels the AI domain forward. The Dictionary of Artificial Intelligence is an invitation to delve deeper, to grapple with the lexicon of a field that stands at the cusp of redefining the very fabric of society. It's a conduit through which the curious become enlightened, the proficient become masters, and the innovators find inspiration. As you traverse through the entries of The Dictionary of Artificial Intelligence, you are embarking on a journey of discovery. A journey that not only augments your understanding but also ignites the spark of curiosity and the drive for innovation that are quintessential in navigating the realms of AI. We beckon you to commence this educational expedition, to explore the breadth and depth of AI lexicon, and to emerge with a boundless understanding and an unyielding resolve to contribute to the ever-evolving narrative of artificial intelligence. Through The Dictionary of Artificial Intelligence, may your quest for knowledge be as boundless and exhilarating as the domain it explores.
Principles Of Artificial Intelligence
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Author : Nils J. Nilsson
language : en
Publisher: Springer Science & Business Media
Release Date : 1982-05-01
Principles Of Artificial Intelligence written by Nils J. Nilsson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982-05-01 with Computers categories.
Previous treatments of Artificial Intelligence (AI) divide the subject into its major areas of application, namely, natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, intelligent data retrieval systems, etc. The major difficulty with this approach is that these application areas are now so extensive, that each could, at best, be only superficially treated in a book of this length. Instead, I have attempted here to describe fundamental AI ideas that underlie many of these applications. My organization of these ideas is not, then, based on the subject matter of their application, but is, instead, based on general computational concepts involving the kinds of data structures used, the types of operations performed on these data struc tures, and the properties of con'trol strategies used by AI systems. I stress, in particular, the important roles played in AI by generalized production systems and the predicate calculus. The notes on which the book is based evolved in courses and seminars at Stanford University and at the University of Massachusetts at Amherst. Although certain topics treated in my previous book, Problem solving Methods in Artificial Intelligence, are covered here as well, this book contains many additional topics such as rule-based systems, robot problem-solving systems, and structured-object representations.
Artificial Intelligence For Robotics
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Author : Dr.P.Kavitha
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-03-01
Artificial Intelligence For Robotics written by Dr.P.Kavitha and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-01 with Computers categories.
Dr.P.Kavitha, Assistant Professor, Department of Computer Applications, Dhanalakshmi Srinivasan College of Arts and Science for Women Autonomous, Perambalur, Tamilnadu, India. Dr.T.Dheepak, Assistant Professor, Department of Computer Science, Centre for Distance and Online Education, Bharathidasan University ,Tiruchirappalli, Tamilnadu, India. Dr.T.Suresh, Assistant Professor, Department of Artificial Intelligence & Machine Learning, K.Ramakrishnan College of Engineering, Tiruchirappalli, Tamil Nadu, India. Dr.S.Kasthuri, Assistant Professor, Department of Computer Science, Srimad Andavan Arts & Science College (Autonomous), Tiruchirappalli, Tamilnadu, India. J.Preethi, Assistant Professor, Department of Computer Applications, Dhanalakshmi Srinivasan College of Arts and Science for Women Autonomous, Perambalur, Tamilnadu, India.
Advanced Artificial Intelligence
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Author : Mr. Rohit Manglik
language : en
Publisher: EduGorilla Publication
Release Date : 2024-04-06
Advanced Artificial Intelligence written by Mr. Rohit Manglik and has been published by EduGorilla Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-06 with Computers categories.
EduGorilla Publication is a trusted name in the education sector, committed to empowering learners with high-quality study materials and resources. Specializing in competitive exams and academic support, EduGorilla provides comprehensive and well-structured content tailored to meet the needs of students across various streams and levels.
Autonomous Search
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Author : Youssef Hamadi
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-01-05
Autonomous Search written by Youssef Hamadi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-05 with Computers categories.
Decades of innovations in combinatorial problem solving have produced better and more complex algorithms. These new methods are better since they can solve larger problems and address new application domains. They are also more complex which means that they are hard to reproduce and often harder to fine-tune to the peculiarities of a given problem. This last point has created a paradox where efficient tools are out of reach of practitioners. Autonomous search (AS) represents a new research field defined to precisely address the above challenge. Its major strength and originality consist in the fact that problem solvers can now perform self-improvement operations based on analysis of the performances of the solving process -- including short-term reactive reconfiguration and long-term improvement through self-analysis of the performance, offline tuning and online control, and adaptive control and supervised control. Autonomous search "crosses the chasm" and provides engineers and practitioners with systems that are able to autonomously self-tune their performance while effectively solving problems. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms. Autonomous search (AS) represents a new research field defined to precisely address the above challenge. Its major strength and originality consist in the fact that problem solvers can now perform self-improvement operations based on analysis of the performances of the solving process -- including short-term reactive reconfiguration and long-term improvement through self-analysis of the performance, offline tuning and online control, and adaptive control and supervised control. Autonomous search "crosses the chasm" and provides engineers and practitioners with systems that are able to autonomously self-tune their performance while effectively solving problems. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms.
Search In Artificial Intelligence
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Author : Leveen Kanal
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Search In Artificial Intelligence written by Leveen Kanal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
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 For Advanced Problem Solving Techniques
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Author : Vlahavas, Ioannis
language : en
Publisher: IGI Global
Release Date : 2008-01-31
Artificial Intelligence For Advanced Problem Solving Techniques written by Vlahavas, Ioannis and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-31 with Education categories.
One of the most important functions of artificial intelligence, automated problem solving, consists mainly of the development of software systems designed to find solutions to problems. These systems utilize a search space and algorithms in order to reach a solution. Artificial Intelligence for Advanced Problem Solving Techniques offers scholars and practitioners cutting-edge research on algorithms and techniques such as search, domain independent heuristics, scheduling, constraint satisfaction, optimization, configuration, and planning, and highlights the relationship between the search categories and the various ways a specific application can be modeled and solved using advanced problem solving techniques.
An Introduction To Artificial Intelligence
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Author : Kenneth H. Rose
language : en
Publisher:
Release Date : 1985
An Introduction To Artificial Intelligence written by Kenneth H. Rose and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Artificial intelligence categories.
Probabilistic Search For Tracking Targets
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Author : Irad Ben-Gal
language : en
Publisher: John Wiley & Sons
Release Date : 2013-03-25
Probabilistic Search For Tracking Targets written by Irad Ben-Gal and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-25 with Mathematics categories.
Presents a probabilistic and information-theoretic framework for a search for static or moving targets in discrete time and space. Probabilistic Search for Tracking Targets uses an information-theoretic scheme to present a unified approach for known search methods to allow the development of new algorithms of search. The book addresses search methods under different constraints and assumptions, such as search uncertainty under incomplete information, probabilistic search scheme, observation errors, group testing, search games, distribution of search efforts, single and multiple targets and search agents, as well as online or offline search schemes. The proposed approach is associated with path planning techniques, optimal search algorithms, Markov decision models, decision trees, stochastic local search, artificial intelligence and heuristic information-seeking methods. Furthermore, this book presents novel methods of search for static and moving targets along with practical algorithms of partitioning and search and screening. Probabilistic Search for Tracking Targets includes complete material for undergraduate and graduate courses in modern applications of probabilistic search, decision-making and group testing, and provides several directions for further research in the search theory. The authors: Provide a generalized information-theoretic approach to the problem of real-time search for both static and moving targets over a discrete space. Present a theoretical framework, which covers known information-theoretic algorithms of search, and forms a basis for development and analysis of different algorithms of search over probabilistic space. Use numerous examples of group testing, search and path planning algorithms to illustrate direct implementation in the form of running routines. Consider a relation of the suggested approach with known search theories and methods such as search and screening theory, search games, Markov decision process models of search, data mining methods, coding theory and decision trees. Discuss relevant search applications, such as quality-control search for nonconforming units in a batch or a military search for a hidden target. Provide an accompanying website featuring the algorithms discussed throughout the book, along with practical implementations procedures.