Jain, Lakhmi C.; Lim, Chee Peng (Eds.)

Decision making is a multi-faceted and challenging, yet important task. A decision
maker normally has to take into consideration a number of alternatives, which often
conflict with one another, before reaching a good decision. To cope with the challenges
of decision making, decision support systems have been developed to provide assistance
in human decision making processes. The key to decision support systems is to collect
information/data, analyse the information/data collected, and subsequently make quality
and informed decisions. In this aspect, intelligent reasoning and learning techniques
have emerged as a powerful approach to solving real-world decision making problems.
The main aim of this research handbook is to present a small fraction of techniques
stemmed from artificial intelligence, as well as other complementary methodologies,
that are useful for developing intelligent decision support systems. In addition,
application examples on how the intelligent decision support systems can be deployed
to undertake decision making problems in a variety of domains are presented. Among
the topics covered in this book include modelling and design of intelligent decision
support systems artificial neural networks, genetic algorithm, and fuzzy systems for
intelligent decision making case based reasoning and agent-based systems for
intelligent decision making application of intelligent decision support systems to
business, management, manufacturing, engineering, biomedicine, transportation and food
industries.

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