公开(公告)号：US20200167611A1

公开(公告)日：2020-05-28

申请号：US16689563

申请日：2019-11-20

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Seung Hyun YOON ,  Seung Jae SHIN ,  Hong Seok JEON ,  Chung Lae CHO

IPC: G06K9/62 ,  G06N3/08 ,  G06N20/00

Abstract: The present invention relates to a method and apparatus where a reinforcement learning agent ensures quality of an initial control operation of an environment on the basis of reinforcement learning, wherein a first action calculated by using an algorithm is selected at an initial learning stage, and a second action calculated by using a Q function is selected when the initial learning stage is ended.

公开(公告)号：US20220164706A1

公开(公告)日：2022-05-26

申请号：US17474849

申请日：2021-09-14

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Seung Jae SHIN ,  Hong Seok JEON

IPC: G06N20/00

Abstract: The present invention relates to an apparatus and method for porting any hardware or software entity to a reinforcement learning system. The present invention includes receiving, by a proxy, a message including episode initiation information from an agent interface and delivering the message to an entity interface based on first synchronization; receiving, by the proxy, a message including first observation information from the entity interface and delivering the message to the agent interface based on second synchronization; receiving, by the proxy, a message including action information from the agent interface and delivering the message to the entity interface based on first synchronization; and receiving, by the proxy, a message including second observation information and reward information from the entity interface and delivering the message to the agent interface based on second synchronization.

公开(公告)号：US20230171630A1

公开(公告)日：2023-06-01

申请号：US17716114

申请日：2022-04-08

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Seung Hyun YOON ,  Tae Yeon KIM ,  Seung Jae SHIN ,  Hong Seok JEON ,  Chung Lae CHO

IPC: H04W24/10 ,  H04W76/10 ,  H04W76/30 ,  H04W40/02 ,  G06N20/00

CPC classification number: H04W24/10 ,  H04W76/10 ,  H04W76/30 ,  H04W40/02 ,  G06N20/00

Abstract: The present invention related to a method for federated learning method interworking with a mobile core system, the method comprising: querying terminal information of each individual terminal among a plurality of terminals; querying network performance information; selecting participating terminals among the plurality of terminals on the basis of the terminal information and the network performance information; transmitting respective parameters to the participating terminals and requesting local learning; and integrating the parameters.

公开(公告)号：US20210168827A1

公开(公告)日：2021-06-03

申请号：US17104377

申请日：2020-11-25

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Seung Jae SHIN

IPC: H04W72/12 ,  H04L12/24 ,  G06Q10/06

Abstract: The present disclosure relates to an apparatus and method of altruistic scheduling based on reinforcement learning. An altruistic scheduling apparatus according to an embodiment of the present disclosure includes: an external scheduling agent for determining a basic resource share for each process based on information of a resource management system; an internal scheduling agent for determining a basic resource allocation schedule for each process based on information including the basic resource share and a resource leftover based on the basic resource allocation schedule; and a leftover scheduling agent for determining a leftover resource allocation schedule based on information including the resource leftover. According to an embodiment of the present disclosure, it may be expected that reinforcement learning will not only mitigate the diminution of fairness of an altruistic scheduler but also further improve other performance indicators such as completion time and efficiency.