Abstract
Abstract This paper describes and compares three formal methods and software implementations for solving decision analysis problems. The comparison includes decision trees, influence diagrams, and a new approach developed by the authors that combines features of trees and influence diagrams. The new approach introduces a language for expressing decision analysis problems and an efficient solution algorithm that exploits structural properties of decision analysis problems. These features allows decision analysis problems to be represented compactly and to be solved very efficiently.
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