GAME TREES FOR DECISION-ANALYSIS

Game trees (or extensive-form games) were first defined by von Neumann and Morgenstern in 1944. In this paper we examine the use of game tre es for representing Bayesian decision problems. We propose a method fo r solving game trees using local computation. This method is a special case of a method due to Wilson for computing equilibria in 2-person g ames. Game trees differ from decision trees in the representations of information constraints and uncertainty. We compare the game tree repr esentation and solution technique with other techniques for decision a nalysis such as decision trees, influence diagrams, and valuation netw orks.