Representing and Solving Asymmetric Bayesian Decision Problems

This paper deals with the representation and solution of asymmetric Bayesian decision problems. We present a formal framework, termed asymmetric influence diagrams, that is based on the influence diagram and al­ lows an efficient representation of asymmet­ ric decision problems. As opposed to exist­ ing frameworks, the asymmetric influence di­ agram primarily encodes asymmetry at the qualitative level and it can therefore be read directly from the model. We give an algorithm for solving asymmetric influence diagrams. The algorithm initially decomposes the asymmetric decision problem into a structure of symmetric subproblems organized as a tree. A solution to the de­ cision problem can then be found by propa­ gating from the leaves towards the root using existing evaluation methods to solve the sub­ problems.