Patents by Inventor Bruce F. Davison

Bruce F. Davison 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).

  • Computationally-efficient resource allocation
    Patent number: 11182711
    Abstract: A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose “seed” particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count.
    Type: Grant
    Filed: July 7, 2020
    Date of Patent: November 23, 2021
    Assignee: GoSpace AI Limited
    Inventors: Bruce F. Davison, Elizabeth E. Tweedale
  • Computationally-efficient resource allocation
    Publication number: 20200334601
    Abstract: A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose “seed” particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count.
    Type: Application
    Filed: July 7, 2020
    Publication date: October 22, 2020
    Inventors: Bruce F. Davison, Elizabeth E. Tweedale
  • Computationally-efficient resource allocation
    Patent number: 10706376
    Abstract: A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose “seed” particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count.
    Type: Grant
    Filed: February 26, 2019
    Date of Patent: July 7, 2020
    Assignee: GoSpace AI Limited
    Inventors: Bruce F. Davison, Elizabeth E. Tweedale
  • Computationally-efficient resource allocation
    Publication number: 20200012981
    Abstract: A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose “seed” particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count.
    Type: Application
    Filed: February 26, 2019
    Publication date: January 9, 2020
    Inventors: Bruce F. Davison, Elizabeth E. Tweedale
  • Computationally-efficient resource allocation
    Patent number: 10216546
    Abstract: A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose “seed” particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count.
    Type: Grant
    Filed: July 9, 2018
    Date of Patent: February 26, 2019
    Assignee: Insitu Software Limited
    Inventors: Bruce F. Davison, Elizabeth E. Tweedale