Estimating the Value of Computation in Flexible Information Refinement

Michael C. Horsch and David Poole

In Proceedings of the 15th Conference on Uncertainty in Artificial Intelligence (UAI-99), Stockholm, Sweden. July 1999.


We outline a method to estimate the value of computation for a flexible algorithm using empirical data. To determine a reasonable trade-off between cost and value, we build an empirical model of the value obtained through computation, and apply this model to estimate the value of computation for quite different problems. In particular, we investigate this trade-off for the problem of constructing policies for decision problems represented as influence diagrams. We show how two features of our anytime algorithm provide reasonable estimates of the value of computation in this domain.

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