US Patent 11003860 System and method for learning preferences in dialogue personalization

The present teaching relates to method, system, medium, and implementations for user machine dialogue. Historic dialogue data related to past dialogues are accessed and used to learn, via machine learning, expected utilities. During a dialogue involving a user and a machine agent, a representation of a shared mindset between the user and the agent is obtained to characterize the current state of the dialogue, which is then used to update the expected utilities. Continuous expected utility functions are then generated based on the updated expected utilities, wherein the continuous expected utility functions are to be used in determining how to conduct a dialogue with a user.