Artificial Intelligence with Uncertainty

Artificial Intelligence with Uncertainty

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The information deluge currently assaulting us in the 21st century is having a profound impact on our lifestyles and how we work. We must constantly separate trustworthy and required information from the massive amount of data we encounter each day. Through mathematical theories, models, and experimental computations, Artificial Intelligence with Uncertainty explores the uncertainties of knowledge and intelligence that occur during the cognitive processes of human beings. The authors focus on the importance of natural language-the carrier of knowledge and intelligence-for artificial intelligence (AI) study.This book develops a framework that shows how uncertainty in AI expands and generalizes traditional AI. It describes the cloud model, its uncertainties of randomness and fuzziness, and the correlation between them. The book also centers on other physical methods for data mining, such as the data field and knowledge discovery state space. In addition, it presents an inverted pendulum example to discuss reasoning and control with uncertain knowledge as well as provides a cognitive physics model to visualize human thinking with hierarchy.With in-depth discussions on the fundamentals, methodologies, and uncertainties in AI, this book explains and simulates human thinking, leading to a better understanding of cognitive processes.
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Product details

  • Electronic book text | 376 pages
  • Taylor & Francis Ltd
  • Chapman & Hall/CRC
  • London, United Kingdom
  • 100 equations; 10 Halftones, black and white; 20 Tables, black and white; 196 Illustrations, black and white
  • 1584889993
  • 9781584889991

Table of contents

PREFACETHE 50-YEAR HISTORY OF ARTIFICIAL INTELLIGENCEDeparture from Dartmouth Symposium Expected Goals as Time Goes on AI Achievements in 50 years Major Development of AI in the Information Age The Cross Trend between AI, Brain Science, and Cognitive Science METHODOLOGIES OF AI Symbolism MethodologyConnectionism MethodologyBehaviorism MethodologyReflection on MethodologiesON UNCERTAINTIES OF KNOWLEDGE On Randomness On FuzzinessUncertainties in Natural LanguagesUncertainties in Commonsense KnowledgeOther Uncertainties of KnowledgeMATHEMATICAL FOUNDATION OF AI WITH UNCERTAINTYProbability TheoryFuzzy Set TheoryRough Set TheoryChaos and FractalKernel Functions and Principal CurvesQUALITATIVE AND QUANTITATIVE TRANSFORM MODEL-CLOUD MODELPerspectives in the Study of AI with UncertaintyRepresenting Concepts Using Cloud ModelsNormal Cloud GeneratorMathematical Properties of Normal CloudOn the Pervasiveness of the Normal Cloud ModelDISCOVERING KNOWLEDGE WITH UNCERTAINTY THROUGH METHODOLOGIES IN PHYSICSFrom Perception of Physical World to Perception of Human SelfData FieldUncertainty in Concept HierarchyKnowledge Discovery State SpaceDATA MINING FOR DISCOVERING KNOWLEDGE WITH UNCERTAINTYUncertainty in Data MiningClassification and Clustering with UncertaintyDiscovery of Association Rules with UncertaintyTime Series Data Mining and ForecastingREASONING AND CONTROL OF QUALITATIVE KNOWLEDGEQualitative Rule Construction by CloudQualitative Control MechanismInverted Pendulum: An Example of Intelligent Control with UncertaintyA NEW DIRECTION OF AI WITH UNCERTAINTYComputing with Words Study on Cognitive Physics Complex Networks with Small World and Scale-Free ModelsLong Way to Go for AI with UncertaintyINDEX
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