We propose a framework for building decision strategies using Bayesian network models and discuss its application to adaptive testing. Dynamic programming and $A{O}^{☆}$ algorithm are used to find optimal adaptive tests. The proposed $A{O}^{☆}$ algorithm is based on a new admissible heuristic function.