Solving Decision Trees with Imprecise Probabilities through Linear Programming
Ricardo Shirota Filho, Daniel Kikuti, Fábio Gagliardi Cozman · 2009
Previous algorithms that generate policies in decision trees with imprecise probabilities [1, 7] employ multilinear programming to compute expected values for policies, that is, a program where the objective function involves a summation of products of variables, and the constraints are linear functions dening