Artificial Intelligence With Uncertainty
by Deyi Li /
2007 / English / PDF
14.7 MB Download
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.
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.
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.
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.