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Author: Michael Gelfond. Yulia Kahl
Publisher:
ISBN: 9781107779464
Category :
Languages : en
Pages :
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Book Description
Author: Michael Gelfond. Yulia Kahl
Publisher:
ISBN: 9781107779464
Category :
Languages : en
Pages :
Get Book
Book Description
Author: Michael Gelfond
Publisher: Cambridge University Press
ISBN: 1107782872
Category : Computers
Languages : en
Pages : 363
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Book Description
Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Using logical and probabilistic formalisms based on answer set programming (ASP) and action languages, this book shows how knowledge-intensive systems can be given knowledge about the world and how it can be used to solve non-trivial computational problems. The authors maintain a balance between mathematical analysis and practical design of intelligent agents. All the concepts, such as answering queries, planning, diagnostics, and probabilistic reasoning, are illustrated by programs of ASP. The text can be used for AI-related undergraduate and graduate classes and by researchers who would like to learn more about ASP and knowledge representation.
Author: Ronald Brachman
Publisher: Morgan Kaufmann
ISBN: 1558609326
Category : Computers
Languages : en
Pages : 414
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Book Description
Knowledge representation is at the very core of a radical idea for understanding intelligence. This book talks about the central concepts of knowledge representation developed over the years. It is suitable for researchers and practitioners in database management, information retrieval, object-oriented systems and artificial intelligence.
Author: Gheorghe Tecuci
Publisher: Morgan Kaufmann
ISBN: 9780126851250
Category : Computers
Languages : en
Pages : 356
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Book Description
Building Intelligent Agents is unique in its comprehensive coverage of the subject. The first part of the book presents an original theory for building intelligent agents and a methodology and tool that implement the theory. The second part of the book presents complex and detailed case studies of building different types of agents: an educational assessment agent, a statistical analysis assessment and support agent, an engineering design assistant, and a virtual military commander. Also featured in this book is Disciple, a toolkit for building interactive agents which function in much the same way as a human apprentice. Disciple-based agents can reason both with incomplete information, but also with information that is potentially incorrect. This approach, in which the agent learns its behavior from its teacher, integrates many machine learning and knowledge acquisition techniques, taking advantage of their complementary strengths to compensate for each others weakness. As a consequence, it significantly reduces (or even eliminates) the involvement of a knowledge engineer in the process of building an intelligent agent.
Author: Michael Gelfond
Publisher: Cambridge University Press
ISBN: 1107029562
Category : Computers
Languages : en
Pages : 363
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Book Description
This in-depth introduction for students and researchers shows how to use ASP for intelligent tasks, including answering queries, planning, and diagnostics.
Author: John-Jules Meyer
Publisher: Springer Science & Business Media
ISBN: 3642053009
Category : Computers
Languages : en
Pages : 168
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Book Description
This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Knowledge Representation for Agents and Multi-Agent Systems, KRAMAS 2008, held in Sydney, Australia, in September 2008 as a satellite event of KR 2008, the 11th International Conference on Principles of Knowledge Representation and Reasoning. The 10 revised full papers presented were carefully reviewed and selected from 14 submissions. The papers foster the cross-fertilization between the KR (knowledge representation and reasoning) and agent communities, by discussing knowledge representation theories and techniques for agent-based systems.
Author: Ronald Brachman
Publisher: Elsevier
ISBN: 008048932X
Category : Computers
Languages : en
Pages : 413
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Book Description
Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed. This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and intuitive form, and the basics of reasoning with that representation are explained in detail. This approach gives readers a solid foundation for understanding the more advanced work found in the research literature. The presentation is clear enough to be accessible to a broad audience, including researchers and practitioners in database management, information retrieval, and object-oriented systems as well as artificial intelligence. This book provides the foundation in knowledge representation and reasoning that every AI practitioner needs. Authors are well-recognized experts in the field who have applied the techniques to real-world problems Presents the core ideas of KR&R in a simple straight forward approach, independent of the quirks of research systems Offers the first true synthesis of the field in over a decade
Author: Frank van Harmelen
Publisher: Elsevier
ISBN: 9780080557021
Category : Computers
Languages : en
Pages : 1034
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Book Description
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: John Fox
Publisher: AAAI Press
ISBN:
Category : Computers
Languages : en
Pages : 340
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Book Description
"Fox and Das insist that the same intelligence (artificial and human) must be applied to guaranteeing safety as to assuring acceptable task performance. Medicine is an excellent field for application of this approach, but it also serves as an example for the entire field of design, where issues of safety are never absent."--BOOK JACKET.
Author: Pierre Marquis
Publisher: Springer Nature
ISBN: 3030061647
Category : Technology & Engineering
Languages : en
Pages : 808
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Book Description
The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). Implementing reasoning or decision making processes requires an appropriate representation of the pieces of information to be exploited. This first volume starts with a historical chapter sketching the slow emergence of building blocks of AI along centuries. Then the volume provides an organized overview of different logical, numerical, or graphical representation formalisms able to handle incomplete information, rules having exceptions, probabilistic and possibilistic uncertainty (and beyond), as well as taxonomies, time, space, preferences, norms, causality, and even trust and emotions among agents. Different types of reasoning, beyond classical deduction, are surveyed including nonmonotonic reasoning, belief revision, updating, information fusion, reasoning based on similarity (case-based, interpolative, or analogical), as well as reasoning about actions, reasoning about ontologies (description logics), argumentation, and negotiation or persuasion between agents. Three chapters deal with decision making, be it multiple criteria, collective, or under uncertainty. Two chapters cover statistical computational learning and reinforcement learning (other machine learning topics are covered in Volume 2). Chapters on diagnosis and supervision, validation and explanation, and knowledge base acquisition complete the volume.
