Description
Condition: BRAND NEW
ISBN: 9780818672002
Year: 1996
Publisher: John Wiley & Sons Inc (US)
Pages: 668
Description:
Mathematical Methods in Artificial Intelligence introduces the
student to the important mathematical foundations and tools in AI
and describes their applications to the design of AI algorithms.
This useful text presents an introductory AI course based on the
most important mathematics and its applications. It focuses on
important topics that are proven useful in AI and involve the most
broadly applicable mathematics.
The book explores AI from three different viewpoints: goals,
methods or tools, and achievements and failures. Its goals of
reasoning, planning, learning, or language understanding and use
are centered around the expert system idea. The tools of AI are
presented in terms of what can be incorporated in the data
structures. The book looks into the concepts and tools of limited
structure, mathematical logic, logic-like representation, numerical
information, and nonsymbolic structures.
The text emphasizes the main mathematical tools for representing
and manipulating knowledge symbolically. These are various forms of
logic for qualitative knowledge, and probability and related
concepts for quantitative knowledge. The main tools for
manipulating knowledge nonsymbolically, as neural nets, are
optimization methods and statistics. This material is covered in
the text by topics such as trees and search, classical mathematical
logic, and uncertainty and reasoning. A solutions diskette is
available, please call for more information.
ISBN: 9780818672002
Year: 1996
Publisher: John Wiley & Sons Inc (US)
Pages: 668
Description:
Mathematical Methods in Artificial Intelligence introduces the
student to the important mathematical foundations and tools in AI
and describes their applications to the design of AI algorithms.
This useful text presents an introductory AI course based on the
most important mathematics and its applications. It focuses on
important topics that are proven useful in AI and involve the most
broadly applicable mathematics.
The book explores AI from three different viewpoints: goals,
methods or tools, and achievements and failures. Its goals of
reasoning, planning, learning, or language understanding and use
are centered around the expert system idea. The tools of AI are
presented in terms of what can be incorporated in the data
structures. The book looks into the concepts and tools of limited
structure, mathematical logic, logic-like representation, numerical
information, and nonsymbolic structures.
The text emphasizes the main mathematical tools for representing
and manipulating knowledge symbolically. These are various forms of
logic for qualitative knowledge, and probability and related
concepts for quantitative knowledge. The main tools for
manipulating knowledge nonsymbolically, as neural nets, are
optimization methods and statistics. This material is covered in
the text by topics such as trees and search, classical mathematical
logic, and uncertainty and reasoning. A solutions diskette is
available, please call for more information.