Seoul National University

Min Whoo Lee

Byoung-Tak Zhang

Minsu Lee

Junseok Park

Hyun Seok Oh

Kibeom Kim

Ganghun Lee

Yoonsung Kim

Kwanyoung Park

Disclosed herein are a computing apparatus and method for performing reinforcement learning using a multimodal artificial intelligence agent. The method for performing reinforcement learning using a multimodal artificial intelligence agent includes: dividing frames, included in images acquired by capturing a virtual environment, into a plurality of sections; and performing reinforcement learning by applying any one of a plurality of guidance types to each of the plurality of sections and then allowing a multimodal artificial intelligence agent to interact with the virtual environment through the images. The plurality of guidance types is classified into three or more types according to their guidance level. Performing the reinforcement learning is performing reinforcement learning by applying a moderate-level guidance type to the sections of predetermined critical periods and also applying any one of the plurality of guidance types to the other sections.

Computing apparatus and method for performing reinforcement learning using multimodal artificial intelligence agent

A target-oriented reinforcement learning method according to an embodiment includes: collecting data related to the target of reinforcement learning as target data in the process of performing the reinforcement learning; learning the collected target data as auxiliary learning for the reinforcement learning; and incorporating the results of the learning of the target data into the performance of the reinforcement learning.

Target-oriented reinforcement learning method and apparatus for performing the same

Growing community of inventors

Yongin-si, South Korea

Min Whoo Lee