高效计算因果网中的干预

Efficient Computation of Intervention in Causal Bayesian Networks

在因果网中,对和积问题因果效果的计算是其首要问题,从有向无环图的角度,研究者们发现每一个因果网都有一个与之对应的贝叶斯网络,干预是因果网的一个基本操作。类似于贝叶斯网络中的剪枝策略,在剪枝掉所有无效结点后,文中设计了一种优化的算法OFDo来计算对因果网中每个结点的完全原子干预。文中接着研究多干预操作,发现多干预操作具有可交换性,并基于多干预操作的可交换性证明了多干预操作的优化计算策略。最后,通过实验证实OFDo计算对因果网中所有结点完全原子干预的效率比目前的算法都好。

In causal Bayesian networks(CBNs),it is a fundamental problem to compute the causal effect of sum product.From the perspective of a directed acyclic graph,we show every CBN has a corresponding Bayesian network.Intervention is a fundamental operation in CBNs.Similar to Bayesian networks,CBNs also have the pruning strategy.After pruning the barren nodes,this paper devises an optimized jointree algorithm to compute the full atomic intervention on each node in a CBN.Then,this paper explores the multiple interventions on multiple nodes,and finds that multiple interventions have the commutative property.On the basis of the commutative property in multiple interventions,this paper proves the strategies,which can be used to optimize the computation of the causal effect of multiple interventions.Finally,we report experimental results to demonstrate the efficiency of our algorithm to compute the causal effects in CBNs.