A computer-implemented method accelerates cognitive intelligence queries to a database using semantic keys. A computing device receives a database. The computing device inserts one or more key-value pairs into the database, where the key is a semantic key that is generated from a binary codeword built from a locality sensitive hashing of one or more vectors in a database embedding model of the database, and where the value is a tuple in the database that identifies entries in the database that share predefined features. The computing device uses the one or more key-value pairs for accelerating cognitive intelligence queries to the database.

A computer-implemented method accelerates cognitive intelligence queries to a database using semantic keys. A computing device receives a database. The computing device inserts one or more key-value pairs into the database, where the key is a semantic key that is generated from a binary codeword built from a locality sensitive hashing of one or more vectors in a database embedding model of the database, and where the value is a tuple in the database that identifies entries in the database that share predefined features. The computing device uses the one or more key-value pairs for accelerating cognitive intelligence queries to the database.

An apparatus comprises a processing device configured to detect a request for parameter values to be utilized in a given iteration of performance testing of an information technology (IT) asset in an IT infrastructure, to determine a current state of the IT asset, the current state comprising two or more performance metric values, and to generate, utilizing a reinforcement learning framework, the parameter values to be utilized in the given iteration of the performance testing of the IT asset based at least in part on the current state. The processing device is also configured to perform the given iteration of performance testing of the IT asset utilizing the generated parameter values, and to update the reinforcement learning framework based at least in part on a subsequent state of the IT asset following the given iteration of performance testing of the IT asset.

A method includes, responsive to first input, actuating a first plurality of valves of a solar board to be in an open position to provide cold water via a first manifold mounted to the solar board to first equipment and to receive hot water from the first equipment. The method further includes, responsive to second input, actuating a second plurality of valves of the solar board to be in the open position to provide the cold water via the first manifold and a second manifold mounted to the solar board to second equipment and to receive the hot water from the second equipment.

Aspects related to game theoretic decision making may be implemented utilizing a sensor, a memory, and a processor. The sensor may detect other vehicles and corresponding attributes as an observation. The memory may store instructions. The processor may execute the instructions to perform acts, actions, or steps, such as constructing a search tree based on the observation, an initial belief, and a vehicle identified as a current opponent vehicle, performing a Monte Carlo Tree Search (MCTS) on the search tree based on a planning horizon and a time allowance to determine a desired action from a set of ego-actions, executing, via vehicle systems, the desired action, detecting an updated observation associated with one or more of the other vehicles, identifying the other vehicles to be updated as the current opponent vehicle, and updating a root node of the search tree based on the current opponent vehicle.

There is provided an information processing apparatus and an information processing method that can provide more useful information for an action plan of an autonomous mobile body, the information processing apparatus including an action recommendation unit configured to present a recommended action recommended to an autonomous mobile body, to the autonomous mobile body that performs an action plan based on situation estimation. The action recommendation unit determines the recommended action on the basis of an action history collected from a plurality of the autonomous mobile bodies, and on the basis of a situation summary received from a target autonomous mobile body that is a target of recommendation. The information processing method includes presenting, by a processor, a recommended action recommended to an autonomous mobile body, to the autonomous mobile body that performs an action plan based on situation estimation.

There is provided an information processing apparatus and an information processing method that can provide more useful information for an action plan of an autonomous mobile body, the information processing apparatus including an action recommendation unit configured to present a recommended action recommended to an autonomous mobile body, to the autonomous mobile body that performs an action plan based on situation estimation. The action recommendation unit determines the recommended action on the basis of an action history collected from a plurality of the autonomous mobile bodies, and on the basis of a situation summary received from a target autonomous mobile body that is a target of recommendation. The information processing method includes presenting, by a processor, a recommended action recommended to an autonomous mobile body, to the autonomous mobile body that performs an action plan based on situation estimation.

The present invention provides a safe path planning method including a process of using a grid map and a congestion map, and a process of planning a path of a mobile robot using a cost function.

An electronic device is provided. The electronic device comprises: a storage for storing interaction setting information and behavior setting information; an interaction interface; and a processor electrically connected to the storage and the interaction interface. When the processor receives a behavior-driving command from the interaction interface, the processor is configured to select the behavior setting information and the interaction setting information according to the behavior-driving command. The processor is configured to perform a behavior according to the behavior setting information. The processor is further configured to perform an interaction operation based on the behavior according to the behavior setting information and the interaction setting information when the behavior is had. A control method and a non-transitory computer readable storage medium are also provided.

Methods and devices are disclosed for monitoring environmental conditions in one or more environments. In one embodiment, the method includes maintaining a plurality of environmental-condition thresholds, each of which corresponds to an environmental condition and is predetermined based on data corresponding to the environmental condition that is received from a plurality of robots. The method further includes receiving from a first robot first data corresponding to a first environmental condition in a first environment. The method may still further include making a first comparison of the first data and a first environmental-condition threshold corresponding to the first environmental condition and, based on the first comparison, triggering a notification. Triggering the notification may comprise transmitting to the robot instructions to transmit the notification to at least one of a call center and a remote device.