Patents by Inventor John Reeder

John Reeder 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).

  • WATER DISPENSING ASSEMBLY FOR CONNECTING TO A FIRE HYDRANT
    Publication number: 20240133163
    Abstract: A water dispensing assembly is provided that is adapted to connect to a fire hydrant water outlet, the fire hydrant being connected to a water supply, for safely dispensing clean water for filling water bottles and the like. The water dispensing assembly is a self-contained unit that is relatively compact and low maintenance. The water dispensing assembly can be housed in an enclosed box-like housing structure that is tamper proof so that it cannot be accessed or modified by the public at large.
    Type: Application
    Filed: October 20, 2022
    Publication date: April 25, 2024
    Inventors: John Reeder, Dayna Livingston, Travis Schneider, Tyler Noyes, Daren Marshall, Shawn C. Robins, Todd Toews, Troy Hannant, Craig Banasch, Allen J. Pribyl, Graeme Dennis, Stuart Bonneville, Pat Bohan
  • Method for performing multi-agent reinforcement learning in the presence of unreliable communications via distributed consensus
    Patent number: 11321635
    Abstract: A system is provided for performing a predetermined function within a total area of operation, wherein the system includes a plurality of autonomous agents. Each autonomous agent is able to detect respective local parameters. Each autonomous agent uses a Kalman filter component to establish an environment state based a plurality of state measurements over time. The output of the Kalman filter component within a respective agent is applied to reinforcement learning by an actor-critic task controller, within the respective agent, to determine a subsequent action to be performed by the respective agent in accordance with a reward function. Each agent includes a Kalman consensus filter that addresses errors of the plurality of state measurements over time.
    Type: Grant
    Filed: May 29, 2019
    Date of Patent: May 3, 2022
    Assignee: United States of America as represented by the Secretary of the Navy
    Inventors: Michael W. Walton, Benjamin J. Migliori, John Reeder
  • Method for Performing Multi-Agent Reinforcement Learning in the Presence of Unreliable Communications Via Distributed Consensus
    Publication number: 20200380401
    Abstract: A system is provided for performing a predetermined function within a total area of operation, wherein the system includes a plurality of autonomous agents. Each autonomous agent is able to detect respective local parameters. Each autonomous agent uses a Kalman filter component to establish an environment state based a plurality of state measurements over time. The output of the Kalman filter component within a respective agent is applied to reinforcement learning by an actor-critic task controller, within the respective agent, to determine a subsequent action to be performed by the respective agent in accordance with a reward function. Each agent includes a Kalman consensus filter that addresses errors of the plurality of state measurements over time.
    Type: Application
    Filed: May 29, 2019
    Publication date: December 3, 2020
    Applicant: United States of America as represented by the Secretary of the Navy
    Inventors: Michael W. Walton, Benjamin J. Migliori, John Reeder