Information sets in decision theory
Information sets were first defined by von Neumann and Morgenstern in 1944 in the context of extensive form games. In this paper, we examine the use of information sets for representing Bayesian decision problems. We call a decision tree with information sets a game tree. We also describe a roll-back procedure for solving game trees using local computation.
KeywordsDecision Tree Expected Profit Tree Representation Decision Node Game Tree
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