Scaling the weight parameters in Markov logic networks and relational logistic regression models

arXiv:2103.15140v3 Announce Type: replace-cross
Abstract: We consider Markov logic networks and relational logistic regression as two fundamental representation formalisms in statistical relational artificial intelligence that use weighted formulas in their specification. However, Markov logic networks are based on undirected graphs, while relational logistic regression is based on directed acyclic graphs. We show that when scaling the weight parameters with the domain size, the asymptotic behaviour of a relational logistic regression model is transparently controlled by the parameters, and we supply …

abstract artificial artificial intelligence arxiv cs.ai cs.lg cs.lo fundamental graphs however intelligence logic logistic logistic regression markov networks parameters regression relational replace representation scaling statistical type while