1st Edition

Artificial Intelligence with Uncertainty

By Deyi Li, Yi Du Copyright 2007
    376 Pages 196 B/W Illustrations
    by Chapman & Hall

    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.

    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

    Biography

    Deyi Li, Yi Du

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

    – Thomas Studer, in Zentralblatt Math, 2009