Reasoning About Knowledge

Author: Ronald Fagin
Publisher: MIT Press
ISBN: 9780262562003
Category : Business & Economics
Languages : en
Pages : 576

Book Description
Reasoning about knowledge—particularly the knowledge of agents who reason about the world and each other's knowledge—was once the exclusive province of philosophers and puzzle solvers. More recently, this type of reasoning has been shown to play a key role in a surprising number of contexts, from understanding conversations to the analysis of distributed computer algorithms. Reasoning About Knowledge is the first book to provide a general discussion of approaches to reasoning about knowledge and its applications to distributed systems, artificial intelligence, and game theory. It brings eight years of work by the authors into a cohesive framework for understanding and analyzing reasoning about knowledge that is intuitive, mathematically well founded, useful in practice, and widely applicable. The book is almost completely self-contained and should be accessible to readers in a variety of disciplines, including computer science, artificial intelligence, linguistics, philosophy, cognitive science, and game theory. Each chapter includes exercises and bibliographic notes.

Reasoning About Knowledge

Author: Ronald Fagin
Publisher: MIT Press
ISBN: 0262307820
Category : Business & Economics
Languages : en
Pages : 533

Knowledge Representation and Reasoning

Author: Ronald Brachman
Publisher: Morgan Kaufmann
ISBN: 1558609326
Category : Computers
Languages : en
Pages : 414

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.

Knowledge Representation, Reasoning, and the Design of Intelligent Agents

Author: Michael Gelfond
Publisher: Cambridge University Press
ISBN: 1107782872
Category : Computers
Languages : en
Pages : 363

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.

Knowledge Representation, Reasoning and Declarative Problem Solving

Author: Chitta Baral
Publisher: Cambridge University Press
ISBN: 1139436449
Category : Computers
Languages : en
Pages : 546

Book Description
Baral shows how to write programs that behave intelligently, by giving them the ability to express knowledge and to reason. This book will appeal to practising and would-be knowledge engineers wishing to learn more about the subject in courses or through self-teaching.

Rules, Reason, and Self-Knowledge

Author: Julia Tanney
Publisher: Harvard University Press
ISBN: 0674071727
Category : Philosophy
Languages : en
Pages : 425

Book Description
Julia Tanney offers a sustained criticism of today’s canon in philosophy of mind, which conceives the workings of the rational mind as the outcome of causal interactions between mental states that have their bases in the brain. With its roots in physicalism and functionalism, this widely accepted view provides the philosophical foundation for the cardinal tenet of the cognitive sciences: that cognition is a form of information-processing. Rules, Reason, and Self-Knowledge presents a challenge not only to the cognitivist approach that has dominated philosophy and the special sciences for the last fifty years but, more broadly, to metaphysical-empirical approaches to the study of the mind. Responding to a tradition that owes much to the writings of Davidson, early Putnam, and Fodor, Tanney challenges this orthodoxy on its own terms. In untangling its internal inadequacies, starting with the paradoxes of irrationality, she arrives at a view these philosophers were keen to rebut—one with affinities to the work of Ryle and Wittgenstein and all but invisible to those working on the cutting edge of analytic philosophy and mind research today. This is the view that rational explanations are embedded in “thick” descriptions that are themselves sophistications upon ever ascending levels of discourse, or socio-linguistic practices. Tanney argues that conceptual cartography rather than metaphysical-scientific explanation is the basic tool for understanding the nature of the mind. Rules, Reason, and Self-Knowledge clears the path for a return to the world-involving, circumstance-dependent, normative practices where the rational mind has its home.

Reasoning about Uncertainty, second edition

Author: Joseph Y. Halpern
Publisher: MIT Press
ISBN: 0262533804
Category : Computers
Languages : en
Pages : 505

Book Description
Formal ways of representing uncertainty and various logics for reasoning about it; updated with new material on weighted probability measures, complexity-theoretic considerations, and other topics. In order to deal with uncertainty intelligently, we need to be able to represent it and reason about it. In this book, Joseph Halpern examines formal ways of representing uncertainty and considers various logics for reasoning about it. While the ideas presented are formalized in terms of definitions and theorems, the emphasis is on the philosophy of representing and reasoning about uncertainty. Halpern surveys possible formal systems for representing uncertainty, including probability measures, possibility measures, and plausibility measures; considers the updating of beliefs based on changing information and the relation to Bayes' theorem; and discusses qualitative, quantitative, and plausibilistic Bayesian networks. This second edition has been updated to reflect Halpern's recent research. New material includes a consideration of weighted probability measures and how they can be used in decision making; analyses of the Doomsday argument and the Sleeping Beauty problem; modeling games with imperfect recall using the runs-and-systems approach; a discussion of complexity-theoretic considerations; the application of first-order conditional logic to security. Reasoning about Uncertainty is accessible and relevant to researchers and students in many fields, including computer science, artificial intelligence, economics (particularly game theory), mathematics, philosophy, and statistics.

Knowledge Engineering

Author: Gheorghe Tecuci
Publisher: Cambridge University Press
ISBN: 1107122562
Category : Business & Economics
Languages : en
Pages : 481

Book Description
Using robust software, this book focuses on learning assistants for evidence-based reasoning that learn complex problem solving from humans.

Qualitative Reasoning

Author: Benjamin Kuipers
Publisher: MIT Press
ISBN: 9780262111904
Category : Computers
Languages : en
Pages : 464

Book Description
Qualitative models are better able than traditional models to express states of incomplete knowledge about continuous mechanisms. Qualitative simulation guarantees to find all possible behaviors consistent with the knowledge in the model. This expressive power and coverage is important in problem solving for diagnosis, design, monitoring, explanation, and other applications of artificial intelligence.

How People Learn II

Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309459672
Category : Education
Languages : en
Pages : 347

Book Description
There are many reasons to be curious about the way people learn, and the past several decades have seen an explosion of research that has important implications for individual learning, schooling, workforce training, and policy. In 2000, How People Learn: Brain, Mind, Experience, and School: Expanded Edition was published and its influence has been wide and deep. The report summarized insights on the nature of learning in school-aged children; described principles for the design of effective learning environments; and provided examples of how that could be implemented in the classroom. Since then, researchers have continued to investigate the nature of learning and have generated new findings related to the neurological processes involved in learning, individual and cultural variability related to learning, and educational technologies. In addition to expanding scientific understanding of the mechanisms of learning and how the brain adapts throughout the lifespan, there have been important discoveries about influences on learning, particularly sociocultural factors and the structure of learning environments. How People Learn II: Learners, Contexts, and Cultures provides a much-needed update incorporating insights gained from this research over the past decade. The book expands on the foundation laid out in the 2000 report and takes an in-depth look at the constellation of influences that affect individual learning. How People Learn II will become an indispensable resource to understand learning throughout the lifespan for educators of students and adults.