Vicarious Fpc, Inc.

Deepmind Technologies Limited

Gdm Holding LLC

Miguel Lazaro-Gredilla

Dileep George

Nishad Gothoskar

Meet Kirankumar Dave

Kenneth Alan Kansky

Wolfgang Lehrach

Sivaramakrishnan Swaminathan

David A Mely

Tom Silver

Mohamed Eldawy

Antoine Dedieu

Yasemin Bekiroglu

Abhishek Agarwal

Guangyao Zhou

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a graph model representing an environment being interacted with by an agent. In one aspect, one of the methods include: obtaining experience data; using the experience data to update a visitation count for each of one or more state-action pairs represented by the graph model; and at each of multiple environment exploration steps: computing a utility measure for each of the one or more state-action pairs represented by the graph model; determining, based on the utility measures, a sequence of one or more planned actions that have an information gain that satisfies a threshold; and controlling the agent to perform the sequence of one or more planned actions to cause the environment to transition from a state characterized by a last observation received after a last action in the experience data into a different state.

Fast exploration and learning of latent graph models

A method for robot control using visual feedback including determining a generative model S, training the generative model S, and controlling the robot using the trained generative model S

Method and system for robot control using visual feedback

The method for query training can include: determining a graphical representation, determining an inference network based on the graphical representation, determining a query distribution, sampling one or more train queries from the query distribution, and optionally determining a trained inference network by training the untrained inference network using the train query. The method can optionally include determining an inference query and determining an inference query result for the inference query using the trained inference network.

Method and system for query training

A system for event prediction using schema networks includes a first antecedent entity state that represents a first entity at a first time; a first consequent entity state that represents the first entity at a second time; a second antecedent entity state that represents a second entity at the first time; and a first schema factor that couples the first and second antecedent entity states to the first consequent entity state; wherein the first schema factor is configured to predict the first consequent entity state from the first and second antecedent entity states.

Systems and methods for event prediction using schema networks

Growing community of inventors

Union City, CA, United States of America

Miguel Lazaro-Gredilla