ABSTRACT
Advances in artificial intelligence (AI), soft computing, and related scientific fields have brought new opportunities and challenges for researchers to deal with complex and uncertain problems and systems, which could not be solved by traditional methods. Many traditional approaches that have been developed for mathematically well-defined problems with accurate models may lack in autonomy and decision-making ability and hence cannot provide adequate solutions under uncertain and fuzzy environments. Intelligent systems represent a new approach to addressing those complex problems with uncertainties. Intelligent systems are defined with such attributes as high degree of autonomy, reasoning under uncertainty, higher performance in a goal seeking manner, high level of abstraction, data fusion from a multitude of sensors, learning and adaptation in a heterogeneous environment, etc. (Shoureshi and Wormley, 1990).
