1. Abdelbar, A. M., & Hedetniemi, S. M. (1998). Approximating MAPs for belief networks is $\mathcal{NP}$ -hard and other theorems. Artificial Intelligence, 102, 21–38.
2. Breese, J. S., & Horvitz, E. (1990). Ideal reformulation of belief networks. In UAI90 (pp. 129–144).
3. Cooper, G., & Herskovits, E. (1992). A Bayesian method for the induction of probabilistic networks from data. Machine Learning, 9(4), 309–347.
4. Fink, E. (1998). How to solve it automatically: selection among problem-solving methods. In Proceedings of the fourth international conference on artificial intelligence planning systems (pp. 128–136).
5. Fung, R., & Chang, K. C. (1989). Weighting and integrating evidence for stochastic simulation in Bayesian networks. Uncertainty in Artificial Intelligence, 5, 209–219.