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Author : Derek Partridge,Yorick Wilks
Publisher : Cambridge University Press
Page : 516 pages
File Size : 47,6 Mb
Release : 1990-04-26
Category : Computers
ISBN : 0521359449
This outstanding collection is designed to address the fundamental issues and principles underlying the task of Artificial Intelligence.
Author : Derek Partridge,Wilks Yorick
Publisher : Unknown
Page : 498 pages
File Size : 45,8 Mb
Release : 1990
Category : Artificial intelligence
ISBN : OCLC:726823750
Author : Michael R. Genesereth,Nils J. Nilsson
Publisher : Morgan Kaufmann
Page : 427 pages
File Size : 47,9 Mb
Release : 2012-07-05
Category : Computers
ISBN : 9780128015544
Intended both as a text for advanced undergraduates and graduate students, and as a key reference work for AI researchers and developers, Logical Foundations of Artificial Intelligence is a lucid, rigorous, and comprehensive account of the fundamentals of artificial intelligence from the standpoint of logic. The first section of the book introduces the logicist approach to AI--discussing the representation of declarative knowledge and featuring an introduction to the process of conceptualization, the syntax and semantics of predicate calculus, and the basics of other declarative representations such as frames and semantic nets. This section also provides a simple but powerful inference procedure, resolution, and shows how it can be used in a reasoning system. The next several chapters discuss nonmonotonic reasoning, induction, and reasoning under uncertainty, broadening the logical approach to deal with the inadequacies of strict logical deduction. The third section introduces modal operators that facilitate representing and reasoning about knowledge. This section also develops the process of writing predicate calculus sentences to the metalevel--to permit sentences about sentences and about reasoning processes. The final three chapters discuss the representation of knowledge about states and actions, planning, and intelligent system architecture. End-of-chapter bibliographic and historical comments provide background and point to other works of interest and research. Each chapter also contains numerous student exercises (with solutions provided in an appendix) to reinforce concepts and challenge the learner. A bibliography and index complete this comprehensive work.
Author : Anonim
Publisher : Unknown
Page : 346 pages
File Size : 45,9 Mb
Release : 1991
Category : Artificial intelligence
ISBN : OCLC:165456356
Author : Michael F. McTear,Norman Creaney
Publisher : Springer Science & Business Media
Page : 393 pages
File Size : 55,7 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9781447135425
This book contains the edited versions of papers presented at the 3rd Irish Conference on Artificial Intelligence and Cognitive Science, which was held at the University of Ulster at Jordanstown, Northern Ireland on 20-21 September 1990. The main aims of this annual conference are to promote AI research in Ireland, to provide a forum for the exchange of ideas amongst the different disciplines concerned with the study of cognition, and to provide an opportunity for industry to see what research is being carried out in Ireland and how they might benefit from the results of this research. Although most of the partiCipants at the conference came from universities and companies within Ireland, a positive feature of the conference was the extent of interest shown outside of Ireland, resulting in partiCipants from USA, Canada, Austria, and England. The keynote speakers were Professor David Chin, University of Hawaii, and Professor Derek Partridge, University of Exeter, and the topics included machine learning, AI tools and methods, expert systems, speech, vision, natural language, reasoning with uncertain information, and explanation. The sponsors of the conference were Digital Equipment Co (Galway) and the Industrial Development Board for Northern Ireland.
Author : Pei Wang,Ben Goertzel
Publisher : Springer Science & Business Media
Page : 334 pages
File Size : 48,6 Mb
Release : 2012-08-31
Category : Computers
ISBN : 9789491216626
This book is a collection of writings by active researchers in the field of Artificial General Intelligence, on topics of central importance in the field. Each chapter focuses on one theoretical problem, proposes a novel solution, and is written in sufficiently non-technical language to be understandable by advanced undergraduates or scientists in allied fields. This book is the very first collection in the field of Artificial General Intelligence (AGI) focusing on theoretical, conceptual, and philosophical issues in the creation of thinking machines. All the authors are researchers actively developing AGI projects, thus distinguishing the book from much of the theoretical cognitive science and AI literature, which is generally quite divorced from practical AGI system building issues. And the discussions are presented in a way that makes the problems and proposed solutions understandable to a wide readership of non-specialists, providing a distinction from the journal and conference-proceedings literature. The book will benefit AGI researchers and students by giving them a solid orientation in the conceptual foundations of the field (which is not currently available anywhere); and it would benefit researchers in allied fields by giving them a high-level view of the current state of thinking in the AGI field. Furthermore, by addressing key topics in the field in a coherent way, the collection as a whole may play an important role in guiding future research in both theoretical and practical AGI, and in linking AGI research with work in allied disciplines
Author : G. M. P. O'Hare,N. R. Jennings
Publisher : John Wiley & Sons
Page : 598 pages
File Size : 54,9 Mb
Release : 1996-04-05
Category : Computers
ISBN : 0471006750
Distributed Artificial Intelligence (DAI) is a dynamic area of research and this book is the first comprehensive, truly integrated exposition of the discipline presenting influential contributions from leaders in the field. Commences with a solid introduction to the theoretical and practical issues of DAI, followed by a discussion of the core research topics--communication, coordination, planning--and how they are related to each other. The third section describes a number of DAI testbeds, illustrating particular strategies commissioned to provide software environments for building and experimenting with DAI systems. The final segment contains contributions which consider DAI from different perspectives.
Author : Frank van Harmelen,Vladimir Lifschitz,Bruce Porter
Publisher : Elsevier
Page : 1034 pages
File Size : 43,6 Mb
Release : 2008-01-08
Category : Computers
ISBN : 0080557023
Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter * Handle qualitative and uncertain information * Improve computational tractability to solve your problems easily
Author : Mayuri Mehta,Vasile Palade,Indranath Chatterjee
Publisher : Springer Nature
Page : 273 pages
File Size : 47,6 Mb
Release : 2022-10-19
Category : Technology & Engineering
ISBN : 9783031128073
This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas. The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.
Author : Ronald Chrisley,Sander Begeer
Publisher : Taylor & Francis
Page : 550 pages
File Size : 40,8 Mb
Release : 2000
Category : Computers
ISBN : 041519332X
Author : Mehryar Mohri,Afshin Rostamizadeh,Ameet Talwalkar
Publisher : MIT Press
Page : 505 pages
File Size : 52,6 Mb
Release : 2018-12-25
Category : Computers
ISBN : 9780262351362
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.
Author : Rajiv Khosla
Publisher : Springer Science & Business Media
Page : 421 pages
File Size : 54,8 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461562238
Engineering Intelligent Hybrid Multi-Agent Systems is about building intelligent hybrid systems. Included is coverage of applications and design concepts related to fusion systems, transformation systems and combination systems. These applications are in areas involving hybrid configurations of knowledge-based systems, case-based reasoning, fuzzy systems, artificial neural networks, genetic algorithms, and in knowledge discovery and data mining. Through examples and applications a synergy of these subjects is demonstrated. The authors introduce a multi-agent architectural theory for engineering intelligent associative hybrid systems. The architectural theory is described at both the task structure level and the computational level. This problem-solving architecture is relevant for developing knowledge agents and information agents. An enterprise-wide system modeling framework is outlined to facilitate forward and backward integration of systems developed in the knowledge, information, and data engineering layers of an organization. In the modeling process, software engineering aspects like agent oriented analysis, design and reuse are developed and described. Engineering Intelligent Hybrid Multi-Agent Systems is the first book in the field to provide details of a multi-agent architecture for building intelligent hybrid systems.
Author : David L. Poole,Alan K. Mackworth
Publisher : Cambridge University Press
Page : 898 pages
File Size : 51,6 Mb
Release : 2023-07-13
Category : Computers
ISBN : 9781009258210
Fully revised and updated, this third edition includes three new chapters on neural networks and deep learning including generative AI, causality, and the social, ethical and regulatory impacts of artificial intelligence. All parts have been updated with the methods that have been proven to work. The book's novel agent design space provides a coherent framework for learning, reasoning and decision making. Numerous realistic applications and examples facilitate student understanding. Every concept or algorithm is presented in pseudocode and open source AIPython code, enabling students to experiment with and build on the implementations. Five larger case studies are developed throughout the book and connect the design approaches to the applications. Each chapter now has a social impact section, enabling students to understand the impact of the various techniques as they learn them. An invaluable teaching package for undergraduate and graduate AI courses, this comprehensive textbook is accompanied by lecture slides, solutions, and code.
Author : David L. Poole,Alan K. Mackworth
Publisher : Cambridge University Press
Page : 821 pages
File Size : 48,7 Mb
Release : 2017-09-25
Category : Computers
ISBN : 9781107195394
Artificial Intelligence presents a practical guide to AI, including agents, machine learning and problem-solving simple and complex domains.
Author : Sun, Zhaohao,Wu, Zhiyou
Publisher : IGI Global
Page : 425 pages
File Size : 51,8 Mb
Release : 2022-03-11
Category : Computers
ISBN : 9781799890188
Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.
