Abstract
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.
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References
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© 1993 Springer-Verlag Berlin Heidelberg
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Shenoy, P.P. (1993). Information sets in decision theory. In: Clarke, M., Kruse, R., Moral, S. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1993. Lecture Notes in Computer Science, vol 747. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0028216
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DOI: https://doi.org/10.1007/BFb0028216
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