Artificial Intelligence with Uncertainty: 1st Edition (Hardback) book cover

Artificial Intelligence with Uncertainty

1st Edition

By Deyi Li, Yi Du

Chapman and Hall/CRC

376 pages | 196 B/W Illus.

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pub: 2007-09-27
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Description

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.

Reviews

"There are many good examples included in the book . . . clearly written from an AI and computer science perspective."

– Thomas Studer, in Zentralblatt Math, 2009

Table of Contents

PREFACE

THE 50-YEAR HISTORY OF ARTIFICIAL INTELLIGENCE

Departure 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 Methodology

Connectionism Methodology

Behaviorism Methodology

Reflection on Methodologies

ON UNCERTAINTIES OF KNOWLEDGE

On Randomness

On Fuzziness

Uncertainties in Natural Languages

Uncertainties in Commonsense Knowledge

Other Uncertainties of Knowledge

MATHEMATICAL FOUNDATION OF AI WITH UNCERTAINTY

Probability Theory

Fuzzy Set Theory

Rough Set Theory

Chaos and Fractal

Kernel Functions and Principal Curves

QUALITATIVE AND QUANTITATIVE TRANSFORM MODEL-CLOUD MODEL

Perspectives in the Study of AI with Uncertainty

Representing Concepts Using Cloud Models

Normal Cloud Generator

Mathematical Properties of Normal Cloud

On the Pervasiveness of the Normal Cloud Model

DISCOVERING KNOWLEDGE WITH UNCERTAINTY THROUGH METHODOLOGIES IN PHYSICS

From Perception of Physical World to Perception of Human Self

Data Field

Uncertainty in Concept Hierarchy

Knowledge Discovery State Space

DATA MINING FOR DISCOVERING KNOWLEDGE WITH UNCERTAINTY

Uncertainty in Data Mining

Classification and Clustering with Uncertainty

Discovery of Association Rules with Uncertainty

Time Series Data Mining and Forecasting

REASONING AND CONTROL OF QUALITATIVE KNOWLEDGE

Qualitative Rule Construction by Cloud

Qualitative Control Mechanism

Inverted Pendulum: An Example of Intelligent Control with Uncertainty

A NEW DIRECTION OF AI WITH UNCERTAINTY

Computing with Words

Study on Cognitive Physics

Complex Networks with Small World and Scale-Free Models

Long Way to Go for AI with Uncertainty

INDEX

Subject Categories

BISAC Subject Codes/Headings:
BUS061000
BUSINESS & ECONOMICS / Statistics
COM000000
COMPUTERS / General
COM012040
COMPUTERS / Programming / Games
COM051240
COMPUTERS / Software Development & Engineering / Systems Analysis & Design