Xerox Corporation

Palo Alto Research Center Inc.

Toyota Jidosha Kabushiki Kaisha

Toyota Research Institute, Inc.

Conduent Business Services, LLC

Matthew Klenk

Shiwali Mohan

John Turner Maxwell, Iii

Kent J Evans

Matthew Adam Shreve

Aaron Ang

Victoria M Bellotti

Johan De Kleer

Daniel H Greene

Ion Matei

Christian Fritz

Yanxia Zhang

Kyle D Dent

Shekhar Gupta

Rong Yang

Filip Dvorak

Marzieh Nabi-Abdolyousefi

Embodiments of the present disclosure are directed to systems and methods to display a plurality of items in a spatial layout, monitor an eye gaze of the user while making sequential decisions about the plurality of items, determine that a drift has occurred, automatically regularize a plurality of alternative choice options, learn and identify an upper boundary and a lower boundary based on whether the user chooses or rejects at least one alternative choice, model the drift using machine learning based at least in part on a history of user decision responses, predict a drift direction of the drift and a relevance impact of different attributes into a drift state, classify the drift states into a risk-averse classification and a risk-seeking classification by clustering drift parameters over different behavioral measures to learn an attentive drift of the user, and output a desirable behavior model for machine learning.

Systems and methods for detecting and regularizing drift in sequential decisions

A method is provided. The method includes obtaining a state graph that represents a set of objects within an environment and a set of positions of the set of objects within the environment. The state graph includes a set of object nodes and a set of property nodes. The method also includes obtaining user input data. The user input data is generated based on a natural language input. The method further includes updating the state graph based on the user input data to generate an enhanced state graph. The enhanced state graph includes additional nodes generated based on the user input data. The method further includes providing the enhanced state graph to a planning module. The planning modules generates instructions for operating a mechanical system based on the enhanced state graph.

Interacting with machines using natural language input and an enhanced state graph

In one embodiment, a method is provided. The method includes obtaining sensor data indicative of a set of objects detected within an environment. The method also includes determining a set of positions of the set of objects and a set of properties of the set of objects based on the sensor data. The method further includes generating a state graph based on the sensor data. The state graph represents the set of objects and the set of positions of the set of objects. The state graph includes a set of object nodes to represent the set of objects and a set of property nodes to represent the set of properties of the set of objects. The state graph is provided to a graph enhancement module that updates the state graph with additional data to generate an enhanced state graph.

Interacting with machines using natural language input and a state graph

A method is provided. The method includes obtaining sensor data indicative of a set of objects detected within an environment. The method also includes generating a state graph based on the sensor data. The state graph includes a set of object nodes and a set of property nodes. The method further includes obtaining user input data generated based on a natural language input. The method further includes updating the state graph based on the user input data to generate an enhanced state graph. The enhanced state graph includes additional nodes generated based on the user input data. The method further includes generating a set of instructions for a set of mechanical systems based on the enhanced state graph. The method further includes operating the set of mechanical systems to achieve a set of objectives based on the set of instructions.

System for interacting with machines using natural language input

The techniques disclosed herein help designers find interesting designs for small electrical, mechanical, and/or hydraulic mechanisms by exhaustively enumerating the design space given a library of components and a maximum number of components allowed per design. Some embodiments work by creating a design space grammar of designs, solving the equations associated with parts of the grammar, and putting the solutions into equivalence classes. This dramatically reduces the number of designs that have to be evaluated to see if they satisfy the design criteria. The result is often a small number of base designs that show the range of possible solutions to the design problem.

Method for generating designs based on automatically built design space grammars

Systems and methods described receive a request for a transportation plan for a user, wherein the request comprises a starting point and an ending point for a route. Systems and methods then generate a set of potential transportation plans for the route, determine an impact of a subset of plans in the set of potential transportation plans and estimate a likelihood of acceptance of the subset of plans in the set of potential transportation plans based on a personal preference model for the user. Systems and methods also select an influence strategy of the user based on a user model and generate a message recommending a selected plan from the subset of plans for the user, wherein the message is generated based on the selected influence strategy.

User behavior influence in transportation systems

A method is provided. The method includes obtaining an enhanced state graph. The enhanced state graph represents a set of objects within an environment and a set of positions of the set of objects. The enhanced state graph includes a set of object nodes, a set of property nodes and a set of goal nodes to represent a set of objectives. The method also includes generating a set of instructions for a set of mechanical systems based on the enhanced state graph. The set of mechanical systems is configured to interact with one or more of the set of objects within the environment. The method further includes operating the set of mechanical systems to achieve the set of objectives based on the set of instructions.

Controlling mechanical systems based on natural language input

A system and method for optimization of on-demand microtransit is provided. A list of possible stops of one or more vehicles is maintained. A plurality of requests for transportation are received, each of the requests associated with at least one traveler. Travelers to be transported by one of the vehicles are selected. A set of a minimal number of the stops is selected, the set comprising at least one stop that is within a predefined walking distance of the origin location of each of the selected travelers and at least one stop within the predefined walking distance of the destination location of each of the selected travelers. Potential routes are identified for the vehicle that include the stops in the set. The potential routes are evaluated using a plurality of constraints and one of the routes is selected for fulfilling the requests of the selected travelers.

System and method for optimization of on-demand microtransit

Systems and methods described receive a request for a transportation plan for a user, wherein the request comprises a starting point and an ending point for a route and generate a set of potential transportation plans for the route. The systems and methods determine an estimated travel time and an estimated fuel consumption for at least a first subset of plans in the set of potential transportation plans and estimate an impact on a transportation system of at least a second subset of plans in the set of potential transportation plans. Based at least in part on the estimated time, the estimated fuel, and the estimated impact on the transportation system, a plan is selected.

Generating collaboratively optimal transport plans

One embodiment of the present invention provides a system for providing assistance to a user of a product in diagnosing faults in the product. During operation, the system receives, at a help server, data associated with current and/or past operation of the product; performs an optimization to determine a sequence of diagnostic actions that is expected to maximize a net benefit to the user. The sequence of diagnostic actions includes one or more actions that require the user to perform at least one task, and performing the optimization involves accounting for costs to the user for performing the at least one task and savings to the user for correcting the faults. The system then interacts with the user, which involves presenting the sequence of diagnostic actions to the user.

Growing community of inventors

San Francisco, CA, United States of America

Matthew Klenk