Intelligent decision making : an AI-based approach
Author(s)
Bibliographic Information
Intelligent decision making : an AI-based approach
（Studies in computational intelligence, v. 97）
Springer, c2008
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Includes bibliographical references
Description and Table of Contents
Description
Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends. This book will be an invaluable resource to anyone interested in the current state of knowledge and key research gaps in the rapidly developing field of intelligent decision support.
Table of Contents
Background: Human Decision Making.- Understanding Human Decision Making - A Fundamental Step Towards Effective Intelligent Decision Support.- Cognitive Elements of Human Decision Making.- Methods: Computational Intelligence.- to Computational Intelligence for Decision Making.- Collaborative Decision Making Amongst Human and Artificial Beings.- Decision Analysis with Fuzzy Targets.- An Approximation Kuhn-Tucker Approach for Fuzzy Linear Bilevel Decision Making.- A Replanning Support for Critical Decision Making Situations: A Modelling Approach.- A Unifying Multimodel Taxonomy and Agent-Supported Multisimulation Strategy for Decision-Support.- Applications: Intelligent Decision Support.- A Consensus Support System for Group Decision Making Problems with Heterogeneous Information.- Evaluating Medical Decision Making Heuristics and Other Business Heuristics with Neural Networks.- Building Intelligent Sensor Networks with Multiagent Graphical Models.- An Intelligent Expert Systems' Approach to Layout Decision Analysis and Design under Uncertainty.- Using Self Organising Feature Maps to Unravel Process Complexity in a Hospital Emergency Department: A Decision Support Perspective.- Future Directions: Building a Decision Making Framework Using Agent Teams.
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