Reinforcement Learning Network For Recommendation System In Video Delivery System

A non-transitory computer-readable storage medium containing instructions, that when executed, control a computer system to be configured for:

• receiving user behavior information for a user at a first system, the user behavior information determined by user interaction with a first recommendation list sent to the user by a first network on a video delivery service;
• generating a first state using the received user behavior information and prior user behavior information by the user from a first set of cells that store the prior user behavior;
• inputting the first state into a second network with the first recommendation list from the first network to generate a value that evaluates a performance of recommending the first recommendation list;
• generating a first evaluation score for the first network, wherein first network parameters are updated based on the first evaluation score to generate a first update to the first network parameters;
• generating a second state using the received user behavior information and the prior user behavior information by the user from a second set of cells that store the prior user behavior;
• and
• outputting a second recommendation list using the first network based on the first update to the first network parameters and the second state without being prompted by the user, wherein the second network uses the second recommendation list to generate a second evaluation score for the first network.

An apparatus comprising:

• one or more computer processors;
• and
• a non-transitory computer-readable storage medium comprising instructions, that when executed, control the one or more computer processors to be configured for:
• receiving user behavior information for a user at a first system, the user behavior information determined by user interaction with a first recommendation list sent to the user by a first network on a video delivery service;
• generating a first state using the received user behavior information and prior user behavior information by the user from a first set of cells that store the prior user behavior;
• inputting the first state into a second network with the first recommendation list from the first network to generate a value that evaluates a performance of recommending the first recommendation list;
• generating a first evaluation score for the first network, wherein first network parameters are updated based on the first evaluation score to generate a first update to the first network parameters;
• generating a second state using the received user behavior information and the prior user behavior information by the user from a second set of cells that store the prior user behavior;
• and
• outputting a second recommendation list using the first network based on the first update to the first network parameters and the second state without being prompted by the user, wherein the second network uses the second recommendation list to generate a second evaluation score for the first network.