An algorithms for bayesian networks structure learning based on genetic algorithms and reinforcement learning
Ben Zhou · Microcomputer & its Applications · 2007
Genetic algorithm is a kind of searching and optimization method which is based on the adaptation principles of the genetic laws found in nature. Bayesian networks are the main methods which are applied to conduction of modeling and reasoning for uncertainty knowledge, and the study problem over Bayesian networks is known to be NP-hard. Reinforcement learning is an online study method by using the new sequence data to update the study result. In this paper, we developed an efficient approach to the structure of Bayesian networks by using a reinforcement learning controller to direct a genetic algorithm.