In recent years, sales of agricultural products in Taiwan have been transformed into electronic marketing, and agricultural products with better consumer orientation have been recommended, and farmers’ income has been improved through sales websites. In the past, A/B testing was used to determine the degree of preference for website solutions, which required a large number of tests for evaluation, and could not respond to environmental variables that made it difficult to predict the actual recommendation in advance. Therefore, in this study, the reinforcement learning model combined with different contextual Multiarmed Bandit algorithms can be tested in data sets of different complexity, which can actually perform well in changing products. It is helpful to predict the preferences of the promotion model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.