A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
qYaditionally, constraint satisfaction problems(CSPs) are characterized using a finite set of constraints expressed within a common,shared constraint language. Whenreasoning acros...
We consider how to efficiently allocate computing resources in order to infer the best of a finite set of simulated systems, where best means that the system has the maximal expec...
An important problem in discrete-event stochastic simulation is the selection of the best system from a finite set of alternatives. There are many techniques for ranking and selec...
This article shows how rational analysis can be used to minimize learning cost for a general class of statistical learning problems. We discuss the factors that influence learning...