System for effective use of data for personalization

A method for selecting a new policy based on a previous policy, the method comprising:

• accessing historical data associated with the previous policy, the historical data comprising at least one context, an action determined based on the context, and a reward for the action;
• evaluating, using an off-policy evaluation model, the new policy to determine whether to use the new policy instead of the previous policy, wherein the off-policy evaluation model comprises a combination of a direct model, inverse propensity scoring, and an estimator selected from the group consisting of a quality-agnostic estimator and a quality-based estimator;
• and
• based on determining that the new policy should be used instead of the previous policy:
• generating an action for a context according to the new policy;
• and
• providing an indication of the action to a user device.

A method for off-policy evaluation of a target policy, the method comprising:

• generating a reward predictor for historical data associated with a logging policy;
• determining an off-policy evaluation model, wherein the off-policy evaluation model comprises an estimator selected from the group consisting of a quality-agnostic estimator and a quality-based estimator;
• evaluating, using the off-policy evaluation model, the target policy to determine whether an expected reward metric of the target policy is higher than a reward metric of the logging policy;
• and
• when it is determined that the expected reward metric is higher than the reward metric of the logging policy, generating an indication to use the target policy instead of the logging policy.