Commonsense Reasoning

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Author: Erik T. Mueller
Publisher: Elsevier
ISBN: 9780080476612
Size: 73.82 MB
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Commonsense Reasoning by Erik T. Mueller

Original Title: Commonsense Reasoning

To endow computers with common sense is one of the major long-term goals of Artificial Intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic. Commonsense Reasoning is a detailed, high-level reference on logic-based commonsense reasoning. It uses the event calculus, a highly powerful and usable tool for commonsense reasoning, which Erik T. Mueller demonstrates as the most effective tool for the broadest range of applications. He provides an up-to-date work promoting the use of the event calculus for commonsense reasoning, and bringing into one place information scattered across many books and papers. Mueller shares the knowledge gained in using the event calculus and extends the literature with detailed event calculus solutions to problems that span many areas of the commonsense world. Covers key areas of commonsense reasoning including action, change, defaults, space, and mental states. The first full book on commonsense reasoning to use the event calculus. Contextualizes the event calculus within the framework of commonsense reasoning, introducing the event calculus as the best method overall. Focuses on how to use the event calculus formalism to perform commonsense reasoning, while existing papers and books examine the formalisms themselves. Includes fully worked out proofs and circumscriptions for every example.

Daydreaming In Humans And Machines

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Author: Erik T. Mueller
Publisher: Intellect Books
ISBN: 9780893915629
Size: 71.88 MB
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Daydreaming In Humans And Machines by Erik T. Mueller

Original Title: Daydreaming In Humans And Machines

This volume presents a computer model of human daydreaming to demonstrate how it is useful for creative problem solving and learning in both humans and computers. The model is implemented as the running computer program Daydreaming, which takes simple descriptions of external world events as input and produces descriptions of daydreams and actions as output.

Reasoning Robots

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Author: Michael Thielscher
Publisher: Springer Science & Business Media
ISBN: 140203069X
Size: 78.96 MB
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Reasoning Robots by Michael Thielscher

Original Title: Reasoning Robots

The creation of intelligent robots is surely one of the most exciting and ch- lenginggoals of Arti?cial Intelligence. A robot is, ?rst of all, nothing but an inanimate machine with motors and sensors. In order to bring life to it, the machine needs to be programmed so as to make active use of its hardware c- ponents. This turns a machine into an autonomous robot. Since about the mid nineties of the past century, robot programming has made impressive progress. State-of-the-art robots are able to orient themselves and move around freely in indoor environments or negotiate di?cult outdoor terrains, they can use stereo vision to recognize objects, and they are capable of simple object manipulation with the help of arti?cial extremities. At a time where robots perform these tasks more and more reliably,weare ready to pursue the next big step, which is to turn autonomous machines into reasoning robots.Areasoning robot exhibits higher cognitive capabilities like following complex and long-term strategies, making rational decisions on a high level, drawing logical conclusions from sensor information acquired over time, devising suitable plans, and reacting sensibly in unexpected situations. All of these capabilities are characteristics of human-like intelligence and ultimately distinguish truly intelligent robots from mere autonomous machines.

Inside Case Based Explanation

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Author: Roger C. Schank
Publisher: Psychology Press
ISBN: 9780805810295
Size: 35.78 MB
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Inside Case Based Explanation by Roger C. Schank

Original Title: Inside Case Based Explanation

This book is the third volume in a series that provides a hands-on perspective on the evolving theories associated with Roger Schank and his students. The primary focus of this volume is on constructing explanations. All of the chapters relate to the problem of building computer programs that can develop hypotheses about what might have caused an observed event. Because most researchers in natural language processing don't really want to work on inference, memory, and learning issues, most of their sample text fragments are chosen carefully to de-emphasize the need for non text-related reasoning. The ability to come up with hypotheses about what is really going on in a story is a hallmark of human intelligence. The biggest difference between truly intelligent readers and less intelligent ones is the extent to which the reader can go beyond merely understanding the explicit statements being communicated. Achieving a creative level of understanding means developing hypotheses about questions for which there may be no conclusively correct answer at all. The focus of the lab, during the period documented in this book, was to work on getting a computer program to do that. The volume adopts a case-based approach to the construction of explanations which suggests that the main steps in the process of explaining a given anomaly are as follows: * Retrieve an explanation that might be relevant to the anomaly. * Evaluate whether the retrieved explanation makes sense when applied to the current anomaly. * Adapt the explanation to produce a new variant that fits better if the retrieved explanation doesn't fit the anomaly perfectly.

Human And Machine Thinking

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Author: Philip N. Johnson-Laird
Publisher: Psychology Press
ISBN: 1135440301
Size: 63.88 MB
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Human And Machine Thinking by Philip N. Johnson-Laird

Original Title: Human And Machine Thinking

This book aims to reach an understanding of how the mind carries out three sorts of thinking -- deduction, induction, and creation -- to consider what goes right and what goes wrong, and to explore computational models of these sorts of thinking. Written for students of the mind -- psychologists, computer scientists, philosophers, linguists, and other cognitive scientists -- it also provides general readers with a self-contained account of human and machine thinking. The author presents his point of view, rather than a review, as simply as possible so that no technical background is required. Like the field of research itself, it calls for hard thinking about thinking.

The Robot S Dilemma Revisited

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Author: Kenneth M. Ford
Publisher: Greenwood Publishing Group
ISBN: 9781567501421
Size: 13.72 MB
Format: PDF
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The Robot S Dilemma Revisited by Kenneth M. Ford

Original Title: The Robot S Dilemma Revisited

The chapters in this book have evolved from talks originally presented at The First International Workshop on Human and Machine Cognition. Although the workshop took place in1989, the papers that appear here are more recent, completed some time after the workshop. They reflect both the spontaneous exchanges in that halcyon setting and the extensive review process.

Logic For Applications

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Author: Anil Nerode
Publisher: Springer Science & Business Media
ISBN: 1461206499
Size: 48.12 MB
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Logic For Applications by Anil Nerode

Original Title: Logic For Applications

In writing this book, our goal was to produce a text suitable for a first course in mathematical logic more attuned than the traditional textbooks to the re cent dramatic growth in the applications oflogic to computer science. Thus, our choice oftopics has been heavily influenced by such applications. Of course, we cover the basic traditional topics: syntax, semantics, soundnes5, completeness and compactness as well as a few more advanced results such as the theorems of Skolem-Lowenheim and Herbrand. Much ofour book, however, deals with other less traditional topics. Resolution theorem proving plays a major role in our treatment of logic especially in its application to Logic Programming and PRO LOG. We deal extensively with the mathematical foundations ofall three ofthese subjects. In addition, we include two chapters on nonclassical logics - modal and intuitionistic - that are becoming increasingly important in computer sci ence. We develop the basic material on the syntax and semantics (via Kripke frames) for each of these logics. In both cases, our approach to formal proofs, soundness and completeness uses modifications of the same tableau method in troduced for classical logic. We indicate how it can easily be adapted to various other special types of modal logics. A number of more advanced topics (includ ing nonmonotonic logic) are also briefly introduced both in the nonclassical logic chapters and in the material on Logic Programming and PROLOG.

Knowledge Representation Reasoning And The Design Of Intelligent Agents

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Author: Michael Gelfond
Publisher: Cambridge University Press
ISBN: 1107029562
Size: 72.86 MB
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Knowledge Representation Reasoning And The Design Of Intelligent Agents by Michael Gelfond

Original Title: Knowledge Representation Reasoning And The Design Of Intelligent Agents

This in-depth introduction for students and researchers shows how to use ASP for intelligent tasks, including answering queries, planning, and diagnostics.

Handbook Of Knowledge Representation

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Author: Frank van Harmelen
Publisher: Elsevier
ISBN: 9780080557021
Size: 78.77 MB
Format: PDF
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Handbook Of Knowledge Representation by Frank van Harmelen

Original Title: Handbook Of Knowledge Representation

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

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