Learning Optimal Bayesian Networks Using A* Search

Yuan, Changhe; Malone, Brandon M.; Wu, Xiaojian

doi:10.5591/978-1-57735-516-8/IJCAI11-364

Learning Optimal Bayesian Networks Using A* Search

Changhe Yuan, Brandon M. Malone, XiaoJian Wu

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2186-2190.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-364

Abstract

This paper formulates learning optimal Bayesian network as a shortest path finding problem. An A* search algorithm is introduced to solve the problem. With the guidance of a consistent heuristic, the algorithm learns an optimal Bayesian networkby only searching the most promising parts of the solution space. Empirical results show that the A*search algorithm significantly improves the time and space efficiency of existing methods on a set of benchmark datasets.

Changhe Yuan, Brandon M. Malone, and Xiaojian Wu. 2011. Learning Optimal Bayesian Networks Using A* Search. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 2186–2190. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-364

@inproceedings{ijcai2011p364,
  title     = {Learning Optimal Bayesian Networks Using A* Search},
  author    = {Yuan, Changhe and Malone, Brandon M. and Wu, Xiaojian},
  booktitle = {Proceedings of the Twenty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-11}},
  publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
  editor    = {Toby Walsh},
  pages     = {2186--2190},
  year      = {2011},
  month     = {7},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-364},
  url       = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-364},
}

TY  - CPAPER
TI  - Learning Optimal Bayesian Networks Using A* Search
AU  - Yuan, Changhe
AU  - Malone, Brandon M.
AU  - Wu, Xiaojian
T2  - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11
PB  - AAAI Press/International Joint Conferences on Artificial Intelligence
PY  - 2011
SP  - 2186
EP  - 2190
DO  - 10.5591/978-1-57735-516-8/IJCAI11-364
UR  - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-364
ER  -