Study of Multi-agent Search Algorithms of the Structural Learning in Bayesian Network Learning
Structural learning is finding the best network that fits the available data and is optimally complex. This can be accomplished by utilizing a search algorithm over the possible network structures, in this paper, a greater importance is given to the search algorithm because we have assumed that the data will be complete. That is, each element of the database is a valid state of a variable. If there are non-applicable entries in the database then the database is said to be incomplete, In the paper, we explore the search algorithms used in this research. In the algorithms, the arcs are added heuristically and exhaustively.
Search Algorithms Heuristic Search Exhaustive Search
Cao Yonghui
School of Economics & Management, Henan Institute of Science and Technology, Xinxiang. R. China
国际会议
2009 International Workshop on Information Security and Application(2009 信息安全与应用国际研讨会)
青岛
英文
576-579
2009-11-21（万方平台首次上网日期，不代表论文的发表时间）