Intelligent decision making : an AI-based approach

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.

• Dedication p. V
• Preface p. VII
• Foreword p. IX
• Part I Background: Human Decision Making
• 1 Understanding Human Decision Making - A Fundamental Step Towards Effective Intelligent Decision Support p. 3 Jean-Charles Pomerol and Frederic Adam
• 2 Cognitive Elements of Human Decision Making p. 41 Jens Pohl
• Part II Methods: Computational Intelligence
• 3 Introduction to Computational Intelligence for Decision Making p. 79 Witold Pedrycz and Nikhil Ichalkaranje and Gloria Phillips-Wren and Lakhmi Jain
• 4 Collaborative Decision Making Amongst Human and Artificial Beings p. 97 Daniel I. Thomas and Ljubo B. Vlacic
• 5 Decision Analysis with Fuzzy Targets p. 135 Van-Nam Huynh and Yoshiteru Nakamori and Tetsuya Murai
• 6 An Approximation Kuhn-Tucker Approach for Fuzzy Linear Bilevel Decision Making p. 157 Guangquan Zhang and Jie Lu and Tharam Dillon
• 7 A Replanning Support for Critical Decision Making Situations: A Modelling Approach p. 173 Guy Camilleri and Jean-Luc Soubie and Pascale Zarate
• 8 A Unifying Multimodel Taxonomy and Agent-Supported Multisimulation Strategy for Decision-Support p. 193 Levent Yilmaz and Andreas Tolk
• Part III Applications: Intelligent Decision Support
• 9 A Consensus Support System for Group Decision Making Problems with Heterogeneous Information p. 229 F. Mata and L. Martínez and E. Herrera- Viedma
• 10 Evaluating Medical Decision Making Heuristics and Other Business Heuristics with Neural Networks p. 259 Steven Walczak
• 11 Building Intelligent Sensor Networks with Multiagent Graphical Models p. 289 Yang Xiang
• 12 An Intelligent Export Systems' Approach to Layout Decision Analysis and Design under Uncertainty p. 321 Abdul-Rahim Ahmad and Otman Basir and Khaled Hassanein and Shahid Azam
• 13 Using Self Organising Feature Maps to Unravel Process Complexity in a Hospital Emergency Department: A Decision Support Perspective p. 365 A. Ceglowski and L. Churilov
• 14 Future Directions: Building a Decision Making Framework Using Agent Teams p. 387 Jeffrey Tweedale and Christos Sioutis and Gloria Phillips-Wren and Nikhil Ichalkaranje and Pierre Urlings and Lakhmi G. Jain