公开(公告)号：US20200167437A1

公开(公告)日：2020-05-28

申请号：US16201872

申请日：2018-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Sunil Mallya Kasaragod ,  Sahika Genc ,  Leo Parker Dirac ,  Bharathan Balaji ,  Eric Li Sun ,  Marthinus Coenraad De Clercq Wentzel ,  Brian James Townsend ,  Pramod Ravikumar Kumar

IPC: G06F17/50 ,  G06N20/00

Abstract: A simulation workflow manager obtains a set of parameters for simulation of a system and training of a reinforcement learning model for optimizing an application of the system. In response to obtaining the set of parameters, the simulation workflow manager configures a first compute node that includes a training application for training the reinforcement learning model. The simulation workflow manager also configures a second compute note with a simulation application to perform the simulation of the system in a simulation environment. Data is generated through execution of the simulation in the second compute node that is provided to the first compute node to cause the training application to use the data to train the reinforcement learning model.

公开(公告)号：US12118456B1

公开(公告)日：2024-10-15

申请号：US16198730

申请日：2018-11-21

Applicant: Amazon Technologies, Inc.

Inventor： Sahika Genc ,  Bharathan Balaji ,  Urvashi Chowdhary ,  Leo Parker Dirac ,  Saurabh Gupta ,  Vineet Khare ,  Sunil Mallya Kasaragod

IPC: G06N3/08 ,  G06F30/20

CPC classification number: G06N3/08 ,  G06F30/20

Abstract: A machine learning environment utilizing training data generated by customer networks. A reinforcement learning machine learning environment receives and processes training data generated by simulated hosted, or integrated, customer networks. The reinforcement learning machine learning environment corresponds to machine learning clusters that receive and process training data sets provided by the integrated customer networks. The customer networks include an agent process that collects training data and forwards the training data to the machine learning clusters. The machine learning clusters can be configured in a manner to automatically process the training data without requiring additional user inputs or controls to configure the application of the reinforcement learning machine learning processes.

公开(公告)号：US11861490B1

公开(公告)日：2024-01-02

申请号：US16198726

申请日：2018-11-21

Applicant: Amazon Technologies, Inc.

Inventor： Saurabh Gupta ,  Bharathan Balaji ,  Leo Parker Dirac ,  Sahika Genc ,  Vineet Khare ,  Ragav Venkatesan ,  Gurumurthy Swaminathan

IPC: G06N3/08 ,  G06N3/04 ,  G06F18/214 ,  G06F18/21

CPC classification number: G06N3/08 ,  G06F18/214 ,  G06F18/2178 ,  G06N3/04

Abstract: A machine learning environment utilizing training data generated by customer environments. A reinforced learning machine learning environment receives and processes training data generated by independently hosted, or decoupled, customer environments. The reinforced learning machine learning environment corresponds to machine learning clusters that receive and process training data sets provided by the decoupled customer environments. The customer environments include an agent process that collects training data and forwards the training data to the machine learning clusters without exposing the customer environment. The machine learning clusters can be configured in a manner to automatically process the training data without requiring additional user inputs or controls to configured the application of the reinforced learning machine learning processes.