Neural-Symbolic Cognitive Reasoning PDF Download

Author: Artur S. D'Avila Garcez
Publisher: Springer Science & Business Media
ISBN: 3540732454
Category : Computers
Languages : en
Pages : 200

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Book Description
This book explores why, regarding practical reasoning, humans are sometimes still faster than artificial intelligence systems. It is the first to offer a self-contained presentation of neural network models for many computer science logics.

Author: Artur S. D'Avila Garcez
Publisher: Springer Science & Business Media
ISBN: 3540732462
Category : Computers
Languages : en
Pages : 200

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Book Description
Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it? The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. This book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics. By using a graphical presentation, it explains neural networks through a sound neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capabilities. The book will be invaluable reading for academic researchers, graduate students, and senior undergraduates in computer science, artificial intelligence, machine learning, cognitive science and engineering. It will also be of interest to computational logicians, and professional specialists on applications of cognitive, hybrid and artificial intelligence systems.

Author: Artur S. D'Avila Garcez
Publisher: Springer
ISBN: 9783642092299
Category : Computers
Languages : en
Pages : 0

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Book Description
Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it? The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. This book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics. By using a graphical presentation, it explains neural networks through a sound neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capabilities. The book will be invaluable reading for academic researchers, graduate students, and senior undergraduates in computer science, artificial intelligence, machine learning, cognitive science and engineering. It will also be of interest to computational logicians, and professional specialists on applications of cognitive, hybrid and artificial intelligence systems.

Author: Oleg M. Anshakov
Publisher: Springer Science & Business Media
ISBN: 3540688757
Category : Computers
Languages : en
Pages : 424

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Book Description
Dealing with uncertainty, moving from ignorance to knowledge, is the focus of cognitive processes. Understanding these processes and modelling, designing, and building artificial cognitive systems have long been challenging research problems. This book describes the theory and methodology of a new, scientifically well-founded general approach, and its realization in the form of intelligent systems applicable in disciplines ranging from social sciences, such as cognitive science and sociology, through natural sciences, such as life sciences and chemistry, to applied sciences, such as medicine, education, and engineering. The main subject developed in the book is cognitive reasoning investigated at three levels of abstraction: conceptual, formal, and realizational. The authors offer a model of a cognizing agent for the conceptual theory of cognitive reasoning, and they also present a logically well-founded formal cognitive reasoning framework to handle the various plausible reasoning methods. They conclude with an object model of a cognitive engine. The book is suitable for researchers, scientists, and graduate students working in the areas of artificial intelligence, mathematical logic, and philosophy.

Author: B. Chandrasekaran
Publisher: Menlo Park, Calif. : AAAI Press
ISBN:
Category : Computers
Languages : en
Pages : 816

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Book Description
foreword by Herbert Simon Diagrammatic reasoning -- the understanding of concepts and ideas by the use of diagrams and imagery, as opposed to linguistic or algebraic representations -- not only allows us to gain insight into the way we think, but is a potential base for constructing representations of diagrammatic information that can be stored and processed by computers.Diagrammatic Reasoning brings together recent investigations into the cognitive, the logical, and particularly the computational characteristics of diagrammatic representations and the reasoning that can be done with them. Following a foreword by Herbert Simon and an introduction by the editors, twenty-seven chapters provide an overview of the recent history of the subject, survey and extend the underlying theory of diagrammatic representation, and provide numerous examples of diagrammatic reasoning (human and mechanical) that illustrate both its powers and its limitations.Each of the book's four sections (Historical and Philosophical Background, Theoretical Foundations, Cognitive and Computational Models, and Problem Solving with Diagrams) begins with an introduction by an eminent researcher. These introductions provide interesting personal perspectives as well as place the work in the proper context.Distributed for AAAI Press

Author: Lance J. Rips
Publisher: MIT Press
ISBN: 9780262181532
Category : Philosophy
Languages : en
Pages : 476

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Book Description
Lance Rips describes a unified theory of natural deductive reasoning and fashions a working model of deduction, with strong experimental support, that is capable of playing a central role in mental life.

Author: Susan Howell Brubaker
Publisher:
ISBN: 9780814317600
Category : Aphasic persons
Languages : en
Pages : 0

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Book Description
Directed to the rehabilitation of language dysfunction and cognitive disorders related to neurological impairment. Language tasks have been created to carry over from the clinical environment to the real world by employing the basic language and vocabulary skills used in daily activities. The exercises are appropriate for children of varying grades, brain-damaged or normal, aswell as adults.

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

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

Author: Keith J. Holyoak
Publisher: Oxford University Press, USA
ISBN: 0199313792
Category : Psychology
Languages : en
Pages : 865

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Book Description
The Oxford Handbook of Thinking and Reasoning brings together the contributions of many of the leading researchers in thinking and reasoning to create the most comprehensive overview of research on thinking and reasoning that has ever been available.

Author: Howard Margolis
Publisher: University of Chicago Press
ISBN: 9780226505282
Category : Psychology
Languages : en
Pages : 348

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Book Description
What happens when we think? How do people make judgments? While different theories abound—and are heatedly debated—most are based on an algorithmic model of how the brain works. Howard Margolis builds a fascinating case for a theory that thinking is based on recognizing patterns and that this process is intrinsically a-logical. Margolis gives a Darwinian account of how pattern recognition evolved to reach human cognitive abilities. Illusions of judgment—standard anomalies where people consistently misjudge or misperceive what is logically implied or really present—are often used in cognitive science to explore the workings of the cognitive process. The explanations given for these anomalous results have generally explained only the anomaly under study and nothing more. Margolis provides a provocative and systematic analysis of these illusions, which explains why such anomalies exist and recur. Offering empirical applications of his theory, Margolis turns to historical cases to show how an individual's cognitive repertoire—the available cognitive patterns and their relation to cues—changes or resists changes over time. Here he focuses on the change in worldview occasioned by the Copernican discovery: not only how an individual might come to see things in a radically new way, but how it is possible for that new view to spread and become the dominant one. A reanalysis of the trial of Galileo focuses on social cognition and its interactions with politics. In challenging the prevailing paradigm for understanding how the human mind works, Patterns, Thinking, and Cognition is certain to stimulate fruitful debate.