Research On Dialogue Management Model Based On A3C Algorithm

With the development of Internet and AI related technologies, task-based dialogue system has become a research hot-spot. This paper uses the common characteristics of dialogue management and reinforcement learning in task-based dialogue system to introduce deep reinforcement learning into the process of building dialogue management model, and proposes a dialogue management model based on A3C algorithm to complete the learning task of dialogue strategy. The model is based on Actor-Critical architecture, which can dynamically improve the learning result of dialogue strategies through internal evaluation mechanism, and improve the prediction accuracy of dialogue management model. At the same time, the model is trained in a multi-threaded way, which can execute multiple sub-nets at the same time, and can effectively improve the training efficiency of the model.