Reinforcement learning model for balanced unit recommendation

Abstract

Embodiments are associated with unit recommendations for an online establishment backend service. A reinforcement learning apparatus integrates a reinforcement learning algorithm model into the online establishment backend service and plugs streaming data representing user behavior and unit performance into the model. The reinforcement learning algorithm model is used to generate unit recommendations, and periodically collected relevant data is used to update the reinforcement learning algorithm model. In some embodiments, the reinforcement learning apparatus retrieves relevant unit data from a unit historical data store and user behavior data from an archive user behavior data store. The retrieved data can then be fed, during an offline training phase, into the reinforcement learning algorithm model before integrating the reinforcement learning algorithm model into the online establishment backend service (e.g., to improve system performance).