Patent ID: 11971884
Assignee: ADOBE INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G  H | IPC G  H

Claim 7:
8. A method comprising:
receiving a history of user actions in an interactive session between a user and an agent, the history of user actions including a search query provided by the user to the agent;
defining a reinforcement learning model having a state that includes a length of the interactive session;
using the reinforcement learning model to generate, based at least in part on the history of user actions, a probability distribution corresponding to a plurality of possible next agent actions that can be taken in response to a user action, each of the possible next agent actions associated with (a) a user task that the corresponding possible next agent action is intended to cause the user to complete, and (b) a corresponding probability in the probability distribution;
selecting a particular one of the possible next agent actions based at least in part on the probability distribution, wherein the selected particular next agent action is associated with an additional information provision user task and an auxiliary reward;
transmitting a message to a user device, for displaying on the user device, the message based at least in part on the selected particular next agent action;
receiving a user response to the message;
incrementing a cumulative reward based on the auxiliary reward;
generating an updated probability distribution based on the user response; and
using the updated probability distribution to select a subsequent agent action.