Abstract: 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.

Abstract: Passive optical Sagnac interferometers for current sensing, method of using the same and method of constructing the same. In one embodiment, the passive optical Sagnac interferometer for current sensing comprises an N×N fibre coupler, wherein N>=3; and a fibre coil disposed on a first side of the N×N fibre coupler, a first port of the N×N fibre coupler coupled to a first end of the fibre coil via a first linear polariser and a second port of the N×N fibre coupler coupled to a second end of the fibre coil via a second linear polariser; wherein the fibre coil is configured to support only one elliptical polarisation state in counter-propagating light signals in the fibre coil.

Abstract: 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.

Abstract: There is described a system for producing electrical energy and utilizing associated heat. The system includes a source of fuel, a source of oxygen and a solid oxide fuel cell configured to oxidize the fuel to create electrical energy and heat. The system also includes at least one unit configured to utilize heat generated by the solid oxide fuel cell. This at least one unit is selected from the group consisting of: a solid waste pyrolysis unit; a hydrothermal carbonization unit; a water distillation unit; a water pasteurization unit; a water heating unit; a room heating and cooling unit; and a biomass drying unit. In a second aspect, the invention is a system for providing utilities used in a multi-residence complex.

Abstract: 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.

Abstract: 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.

Abstract: A system and method for machine understanding, using program induction, includes a visual cognitive computer including a set of components designed to execute predetermined primitive functions. The method includes determining programs using a program induction engine that interfaces with the visual cognitive computer to discover programs using the predetermined primitive functions and/or executes the discovered programs based on an input.

Abstract: A device for filtering air for a user comprising a frame formed in a generally oval-shaped band, the band encircling the user's head, with an upper portion above the user's head and a lower portion proximate to and spaced apart from the user's chin, an intake aperture formed in the frame, and an intake air filter covering the intake aperture. The device includes an air mover chamber attached with an air-tight seal to an inside surface of the frame and communicating on one end with the intake air filter and communicating on another end with a filtered air supply inlet inside the device and an air mover disposed within the air mover chamber and configured to draw air through the intake air filter and push air out the filtered air supply inlet. The device also includes an exhaust aperture formed in the frame and an exhaust air filter covering the exhaust aperture.

Abstract: A device for filtering air for a user comprising a frame formed in a generally oval-shaped band, the band encircling the user’s head with an upper portion extending from the user’s ear to a point above and to the rear of the user’s head and a lower portion extending from the user’s ear to a point below and in front of the user’s mouth. The device includes an air inlet filter mounted on the frame and communicating on one side with ambient air outside the device and on the other side with an inlet duct and an air outlet filter mounted on the frame and communicating on one side with air inside the device and on the other side with ambient air outside the device. The device also includes a battery-powered air mover mounted on the frame and operable to move intake air through the air inlet filter through the inlet duct and into the inside of the device. A rechargeable battery is mounted on the frame to power the air mover.

Abstract: A device for filtering air for a user comprising a frame formed in a generally oval-shaped band, the band encircling the user's head, with an upper portion extending above and behind the user's ears and a lower portion extending below and in front of the user's ears. The device includes components mounted to the frame, comprising an air intake filter mounted on the frame and communicating on one side with ambient air outside the device and on the other side with an inlet duct and an air outlet filter mounted on the frame and communicating on one side with air inside the device and on the other side with ambient air outside the device. The device also includes a battery-powered air mover mounted on the frame and operable to pull air through the air intake filter and through the inlet duct and push air out into the inside of the device and a rechargeable battery mounted on the frame to power the air mover.

Abstract: A hierarchical compositional network, representable in Bayesian network form, includes first, second, third, fourth, and fifth parent feature nodes; first, second, and third pool nodes; first, second, and third weight nodes; and first, second, third, fourth, and fifth child feature nodes.

Abstract: A hierarchical compositional network, representable in Bayesian network form, includes first, second, third, fourth, and fifth parent feature nodes; first, second, and third pool nodes; first, second, and third weight nodes; and first, second, third, fourth, and fifth child feature nodes.

Abstract: A method for robot control using visual feedback including determining a generative model S100, training the generative model S200, and controlling the robot using the trained generative model S300.

Abstract: 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.

Abstract: Methods and systems for conducting batch multi-effect distillation are disclosed. A multi-effect distillation system and one or more isolation devices are provided. A feed stream, consisting of water and a solute, is passed from a feed source into a brine side of the plurality of heat exchangers. The feed source is isolated from the plurality of heat exchangers by closing the one or more isolation devices. A first of the plurality of heat exchangers is heated by the heat source. A steam stream and a brine concentrate stream are produced in all but a last of the plurality of heat exchangers. A condensate stream from the steam stream is produced in all but the first of the plurality of heat exchangers. A warmed feed stream is produced in the last of the plurality of heat exchangers.

Abstract: A method for robot control using visual feedback including determining a generative model S100, training the generative model S200, and controlling the robot using the trained generative model S300.

Abstract: 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.

Abstract: Methods and systems for conducting batch multi-effect distillation are disclosed. A multi-effect distillation system and one or more isolation devices are provided. A feed stream, consisting of water and a solute, is passed from a feed source into a brine side of the plurality of heat exchangers. The feed source is isolated from the plurality of heat exchangers by closing the one or more isolation devices. A first of the plurality of heat exchangers is heated by the heat source. A steam stream and a brine concentrate stream are produced in all but a last of the plurality of heat exchangers. A condensate stream from the steam stream is produced in all but the first of the plurality of heat exchangers. A warmed feed stream is produced in the last of the plurality of heat exchangers.

Abstract: A method for robot control using visual feedback including determining a generative model S100, training the generative model S200, and controlling the robot using the trained generative model S300.

Abstract: 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.