Abstract: Disclosed herein are methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for modeling agents in multi-agent systems as reinforcement learning (RL) agents and training control policies that cause the agents to cooperate towards a common goal. A method can include generating, for each of a group of simulated local agents in an agent network in which the simulated local agents share resources, information, or both, experience tuples having a state for the simulated local agent, an action taken by the simulated local agent, and a local result for the action taken, updating each local policy of each simulated local agent according to the respective local result, providing, to each of the simulated local agents, information representing a global state of the agent network, and updating each local policy of each simulated local agent according to the global state of the agent network.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-readable storage media, for automated camera positioning for feeding behavior monitoring. In some implementations, a system obtains an image of a scene, a spatial model that corresponds to a subfeeder, and calibration parameters of a camera, the system determines a size of the subfeeder in the image of the scene, the system selects an updated position of the camera relative to the subfeeder, the system provides the updated position of the camera relative to the subfeeder to a winch controller, and the system moves the camera to the updated position.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for identification and re-identification of fish. In some implementations, first media representative of aquatic cargo is received. Second media based on the first media is generated, wherein a resolution of the second media is higher than a resolution of the first media. A cropped representation of the second media is generated. The cropped representation is provided to the machine learning model. In response to providing the cropped representation to the machine learning model, an embedding representing the cropped representation is generated using the machine learning model. The embedding is mapped to a high dimensional space. Data identifying the aquatic cargo is provided to a database, wherein the data identifying the aquatic cargo comprises an identifier of the aquatic cargo, the embedding, and a mapped region of the high dimensional space.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-readable storage media, for automated camera positioning for feeding behavior monitoring. In some implementations, a system obtains an image of a scene, a spatial model that corresponds to a subfeeder, and calibration parameters of a camera, the system determines a size of the subfeeder in the image of the scene, the system selects an updated position of the camera relative to the subfeeder, the system provides the updated position of the camera relative to the subfeeder to a winch controller, and the system moves the camera to the updated position.

Abstract: Implementations are directed to improving network anti-fragility. In some aspects, a method includes receiving parameter data from a network of nodes, the parameter data comprising attributes, policies, and action spaces for each node in the network of nodes; configuring one or more interruptive events on one or more nodes included in the network of nodes; determining a first action of each node in the network of nodes in response to the one or more interruptive events; determining a first performance metric, for each node, that corresponds to the first action, wherein the first performance matric is determined based on at least a first reward value associated with the first action; continuously updating the first action in an iterative process to obtain a final action, wherein a performance metric corresponding to the final action satisfies a performance threshold, and transmitting the final action for each node to the network of nodes.

Abstract: Methods and systems including receiving a plurality of shipping bids from a plurality of shipping entities, each entity having goods to ship from locations to destinations, wherein each bid represents an option to ship goods at a shipping price, and wherein each bid comprises a plurality of shipping parameters; receiving a plurality of carrier bids from a plurality of carrier entities, each entity transporting the goods, wherein each bid represents an option to transport the goods at a price, and wherein each bid comprises a plurality of carrier parameters; performing a matching process to generate a plurality of pair-wise partial matches, wherein each match associates a shipping and carrier bid at a modified price, wherein the modified price is based on a deviation between the parameters; providing information representing the matches to the shipping and carrier entities; and generating training data representing which matches were exercised.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for identification and re-identification of fish. In some implementations, first media representative of aquatic cargo is received. Second media based on the first media is generated, wherein a resolution of the second media is higher than a resolution of the first media. A cropped representation of the second media is generated. The cropped representation is provided to the machine learning model. In response to providing the cropped representation to the machine learning model, an embedding representing the cropped representation is generated using the machine learning model. The embedding is mapped to a high dimensional space. Data identifying the aquatic cargo is provided to a database, wherein the data identifying the aquatic cargo comprises an identifier of the aquatic cargo, the embedding, and a mapped region of the high dimensional space.

Abstract: In one aspect, there is provided a method that includes receiving, by a control system having (i) a first camera configured to obtain an image of a scene, (ii) a winch controller, and (iii) a feeding system configured to deliver a feed to aquaculture, instructions to initiate a calibration of the first camera, determining a calibration state of the first camera, determining a sequence of calibration steps based on the calibration state of the first camera, and executing the sequence of calibration steps to calibrate the first camera.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for the automated feeding of fish. In some implementations, a corresponding method may include obtaining meal configuration data including one or more parameters indicating a meal plan for feeding farmed fish; executing the meal plan based on the meal configuration data; receiving sensor data from one or more sensors during execution of the meal plan; and adjusting the execution of the meal plan based on the sensor data from the one or more sensors.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for sensor data processing. The method may include the actions of obtaining sensor data regarding aquatic livestock over periods of time, where the sensor data is captured by at least one sensor at different depths, determining, for each of the periods of time, whether the sensor data captured at different depths during the period of time satisfy one or more evaluation criteria, generating an input data set that concatenates representations of the periods of time, providing the input data set to a machine-learning trained model, receiving, as an output from the machine-learning trained model, an indication of an action to be performed for the aquatic livestock, and initiating performance of the action for the aquatic livestock.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-readable storage media, for automated camera positioning for feeding behavior monitoring. In some implementations, a system obtains an image of a scene, a spatial model that corresponds to a subfeeder, and calibration parameters of a camera, the system determines a size of the subfeeder in the image of the scene, the system selects an updated position of the camera relative to the subfeeder, the system provides the updated position of the camera relative to the subfeeder to a winch controller, and the system moves the camera to the updated position.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-readable storage media, for automated camera positioning for feeding behavior monitoring. In some implementations, a system obtains an image of a scene from one or more cameras and a spatial model that corresponds to a subfeeder. The system determines, based on data from the spatial model and the image of the scene, a current position of the one or more cameras relative to the subfeeder. The system selects an updated position of the one or more cameras relative to the subfeeder. The system moves the one or more cameras to the updated position. In some implementations, the system dynamically selects the updated position of the one or more cameras relative to the subfeeder.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for identification and re-identification of fish. In some implementations, first media representative of aquatic cargo is received. Second media based on the first media is generated, wherein a resolution of the second media is higher than a resolution of the first media. A cropped representation of the second media is generated. The cropped representation is provided to the machine learning model. In response to providing the cropped representation to the machine learning model, an embedding representing the cropped representation is generated using the machine learning model. The embedding is mapped to a high dimensional space. Data identifying the aquatic cargo is provided to a database, wherein the data identifying the aquatic cargo comprises an identifier of the aquatic cargo, the embedding, and a mapped region of the high dimensional space.