Patents by Inventor Robert Prescott Goldman

Robert Prescott Goldman 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).

  • Patent number: 11468608
    Abstract: A computing machine accesses a directed graph representing one or more sequences of actions. The directed graph comprises nodes and edges between the nodes. Each node is either a beginning node, an intermediate node, or an end node. Each intermediate is downstream from at least one beginning node and upstream from at least one end node. Each beginning node in at least a subset of the beginning nodes has an explainability value vector. The computing machine computes, for each first node from among a plurality of first nodes that are intermediate nodes or end nodes, a provenance value representing dependency of an explainability value vector of the first node on the one or more nodes upstream from the first node. The computing machine computes, for each first node, the explainability value vector. The computing machine provides a graphical output representing at least an explainability value vector of an end node.
    Type: Grant
    Filed: November 24, 2020
    Date of Patent: October 11, 2022
    Assignee: Smart Information Flow Technologies, LLC
    Inventors: Scott Ehrlich Friedman, Robert Prescott Goldman, Richard Gabriel Freedman, Ugur Kuter, Christopher William Geib, Jeffrey M. Rye
  • Publication number: 20220165007
    Abstract: A computing machine accesses a directed graph representing one or more sequences of actions. The directed graph comprises nodes and edges between the nodes. Each node is either a beginning node, an intermediate node, or an end node. Each intermediate is downstream from at least one beginning node and upstream from at least one end node. Each beginning node in at least a subset of the beginning nodes has an explainability value vector. The computing machine computes, for each first node from among a plurality of first nodes that are intermediate nodes or end nodes, a provenance value representing dependency of an explainability value vector of the first node on the one or more nodes upstream from the first node. The computing machine computes, for each first node, the explainability value vector. The computing machine provides a graphical output representing at least an explainability value vector of an end node.
    Type: Application
    Filed: November 24, 2020
    Publication date: May 26, 2022
    Inventors: Scott Ehrlich Friedman, Robert Prescott Goldman, Richard Gabriel Freedman, Ugur Kuter, Christopher William Geib, Jeffrey M. Rye