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Decision-Analytic Intelligent Systems (Automated Explanation and Knowledge Acquisition)
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Product Details
Author:
David A. Klein
Format:
Paperback
Pages:
232
Publisher:
Taylor & Francis (February 4, 2019)
Language:
English
ISBN-13:
9781138876262
Weight:
12.25oz
Dimensions:
6" x 9"
File:
TAYLORFRANCIS-TayFran_260123055423600-20260123.xml
Folder:
TAYLORFRANCIS
List Price:
$68.99
As low as:
$65.54
Publisher Identifier:
P-CRC
Discount Code:
H
Case Pack:
1
Audience:
Professional and scholarly
Country of Origin:
United States
Pub Discount:
30
Imprint:
Psychology Press
Overview
This book presents a framework for building intelligent systems based on the mathematical decision models of Decision Analysis. The author provides new techniques for automated explanation and knowledge acquisition in formally sound systems that reason about complex tradeoffs in decisions. Also included are specifications for implementing these techniques in computer programs, along with demonstration applications in marketing, process control, and medicine.
Readers with an interest in artificial intelligence will gain a foundation for building formally justifiable, intelligible, modifiable systems for computing decisions involving multiple considerations, with applications across a variety of domains. Beyond decision models, the methodology of the work reported suggests a more general approach to employing formal mathematical models in transparent intelligent systems.
Decision-analysis experts will find a collection of methods for explaining decision-analytic advice to clients in intuitive terms, for simplifying parameter assessment, and for managing changing preferences over time. The book provides sufficient background material to promote understanding by readers who may be unfamiliar with artificial intelligence, with decision analysis, or with both fields, and such material is labeled to increase the well-versed reader's efficiency in skipping particular sections.
Readers with an interest in artificial intelligence will gain a foundation for building formally justifiable, intelligible, modifiable systems for computing decisions involving multiple considerations, with applications across a variety of domains. Beyond decision models, the methodology of the work reported suggests a more general approach to employing formal mathematical models in transparent intelligent systems.
Decision-analysis experts will find a collection of methods for explaining decision-analytic advice to clients in intuitive terms, for simplifying parameter assessment, and for managing changing preferences over time. The book provides sufficient background material to promote understanding by readers who may be unfamiliar with artificial intelligence, with decision analysis, or with both fields, and such material is labeled to increase the well-versed reader's efficiency in skipping particular sections.
