LIMIDs - Representing and Solving Decision Problems with Limited Information

Wednesday, December 4, 2002 - 1:30pm - 2:20pm
Keller 3-180
Steffen Lauritzen (Aalborg University)
The notion of a Limited Memory Influence Diagram (LIMID) is introduced as a Bayesian network augmented with nodes representing decisions and utility functions. For each decision it is specified what information is available at the time when the decision is to be made. In contrast with traditional influence diagrams, the assumption of no forgetting is relaxed, and there is no additional constraints on the order in which decisions are to be taken. This allows for multiple decision makers and decision makers with limited memory, and reduces complexity of strategies. We give a local computation algorithm for finding locally optimal policies, conditions for the policies to be globally optimal, and indicate how this can be exploited to obtain bounds for the loss of utility, for example in partially observed Markov decision processes (POMDPs). The lecture is largely based upon:

Lauritzen, S.L. and Nilsson, D. (2001). Representing and Solving Decision Problems with Limited Information, Management Science, 47, 1238-1251.

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