Patents by Inventor Connor LAWLESS

Connor LAWLESS has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • TRADE PLATFORM WITH REINFORCEMENT LEARNING
    Publication number: 20230342619
    Abstract: Systems are methods are provided for training an automated agent. The automated agent maintains a reinforcement learning neural network and generates, according to outputs of the reinforcement learning neural network, signals for communicating resource task requests. First and second task data are received. The task data are processed to compute a first performance metric reflective of performance of the automated agent relative to other entities in a first time interval, and a second performance metric reflective of performance of the automated agent relative to other entities in a second time interval. A reward for the reinforcement learning neural network that reflects a difference between the second performance metric and the first performance metric is computed and provided to the reinforcement learning neural network to train the automated agent.
    Type: Application
    Filed: June 13, 2023
    Publication date: October 26, 2023
    Inventors: Hasham BURHANI, Shary MUDASSIR, Xiao Qi SHI, Connor LAWLESS, Weiguang DING
  • Trade platform with reinforcement learning
    Patent number: 11715017
    Abstract: Systems are methods are provided for training an automated agent. The automated agent maintains a reinforcement learning neural network and generates, according to outputs of the reinforcement learning neural network, signals for communicating resource task requests. First and second task data are received. The task data are processed to compute a first performance metric reflective of performance of the automated agent relative to other entities in a first time interval, and a second performance metric reflective of performance of the automated agent relative to other entities in a second time interval. A reward for the reinforcement learning neural network that reflects a difference between the second performance metric and the first performance metric is computed and provided to the reinforcement learning neural network to train the automated agent.
    Type: Grant
    Filed: May 30, 2019
    Date of Patent: August 1, 2023
    Assignee: ROYAL BANK OF CANADA
    Inventors: Hasham Burhani, Shary Mudassir, Xiao Qi Shi, Connor Lawless, Weiguang Ding
  • TRADE PLATFORM WITH REINFORCEMENT LEARNING
    Publication number: 20190370649
    Abstract: Systems are methods are provided for training an automated agent. The automated agent maintains a reinforcement learning neural network and generates, according to outputs of the reinforcement learning neural network, signals for communicating resource task requests. First and second task data are received. The task data are processed to compute a first performance metric reflective of performance of the automated agent relative to other entities in a first time interval, and a second performance metric reflective of performance of the automated agent relative to other entities in a second time interval. A reward for the reinforcement learning neural network that reflects a difference between the second performance metric and the first performance metric is computed and provided to the reinforcement learning neural network to train the automated agent.
    Type: Application
    Filed: May 30, 2019
    Publication date: December 5, 2019
    Inventors: Hasham BURHANI, Shary MUDASSIR, Xiao Qi SHI, Connor LAWLESS