Abstract: To provide an action evaluation system capable of more efficiently planning a new action based on an execution result of a test for limited action conditions. A condition change tracking unit determines, based on execution result information obtained by executing a test related to an action for an action target having a predetermined action condition, a condition change which is a change in the action condition before and after the test. A result verification unit calculates, based on the execution result information, an evaluation value obtained by evaluating an effect of the action. A reward distribution unit calculates a change contribution degree which is a degree of contribution of the condition change to the evaluation value.

Abstract: A computer system accurately selects learning data for improving a prediction accuracy of a predictor, and is connected to a database that stores a plurality of pieces of learning data and information for managing a plurality of predictors generated under different learning conditions. A target predictor is selected, an influence degree representing strength of an influence of the learning data on a prediction accuracy of the target predictor for test data is calculated for each of a plurality of pieces of test data, an influence score of the learning data is calculated for the plurality of predictors based on a plurality of influence degrees of the learning data associated with the predictors, and the learning data to be used is selected from the plurality of pieces of learning data on the basis of a plurality of the influence scores of each of the plurality of pieces of learning data.

Abstract: There is provided is a computer system that outputs a predicted value of data to be evaluated using a predictor generated using learning data. The computer system includes the predictor; an index calculation unit that calculates an interpretation index of the data to be evaluated; and an extraction unit that selects the learning data useful for a user to interpret the predicted value of the data to be evaluated, wherein index management information for managing an interpretation index of the learning data is stored, the index calculation unit calculates the interpretation index of the data to be evaluated, and the extraction unit calculates a selection index based on the interpretation index of the data to be evaluated and the interpretation index of the learning data, selects the learning data based on the selection index, and outputs display information for presenting information indicating a processing result.

Abstract: Provided is a computer system to present information useful for achieving purposes related to an object by utilizing AI prediction. The computer system manages a prediction model for predicting an object event based on evaluation data and feature profiling database that defines a change rule of each of the plurality of feature values included in the evaluation data, generates change policy data by changing the plurality of feature values included in the evaluation data based on the feature profiling database, calculates an evaluation value indicating effectiveness of the change policy data, and generates display data for presenting the change policy data and the evaluation value as information useful for achieving purposes related to the object.

Abstract: A computer has: a testing unit obtaining attribute values of attributes from an object to which a measure is implemented and an object to which the measure is not implemented, and calculating a change amount of the attribute values of the attributes due to the implementation of the measure and a test indicator for determining a significant difference of the change amount of the attribute values of the attributes due to the implementation of the measure; an experimental rule updating unit calculating a cumulative change amount indicating a temporal change amount of the attribute values of the attributes and a cumulative test indicator indicating a temporal test indicator of the attributes on the basis of a test result output from the testing unit, and accumulating data in which the identification information of the measure and the cumulative change amount and the cumulative test indicator are associated; and a display unit.

Abstract: A management computer for managing a system that makes an inference using a training model has a processor for performing a process in cooperation with a memory, and the processor executes: a generation process for generating an accuracy improvement prediction model for predicting the accuracy of a retrained model when retraining is executed using retraining data including new collected data collected from the system after the start of the operation of the system based on a correlation between the Feature of training data used for training of the training model and the accuracy of the training model; a prediction process for predicting the accuracy of the retrained model from the accuracy improvement prediction model and the Feature of the retraining data; and a determination process for determining whether or not the execution of the retraining is necessary based on the predicted accuracy of the retrained model.

Abstract: Provided is a technique for reducing the calculation load in navigation management of a moving body within a freely navigable space. The system has a storage unit 21 for storing movement locus data showing a plurality of movement loci in which a moving body is moved in a two-dimensional or three-dimensional space in which free movement is possible; a network model management unit 11 for integrating sections approximated by the plurality of movement loci on the basis of the movement locus data, and generating a network model showing a route within the space; a navigation schedule calculation unit 13 for calculating a navigation schedule when a plurality of moving bodies planning to pass within the space navigate within that space according to the network model route; and a display processing unit 15 for outputting the calculated navigation schedule to a display apparatus.

Abstract: Provided is a computer system to present information useful for achieving purposes related to an object by utilizing AI prediction. The computer system manages a prediction model for predicting an object event based on evaluation data and feature profiling database that defines a change rule of each of the plurality of feature values included in the evaluation data, generates change policy data by changing the plurality of feature values included in the evaluation data based on the feature profiling database, calculates an evaluation value indicating effectiveness of the change policy data, and generates display data for presenting the change policy data and the evaluation value as information useful for achieving purposes related to the object.

Abstract: There is provided is a computer system that outputs a predicted value of data to be evaluated using a predictor generated using learning data. The computer system includes the predictor; an index calculation unit that calculates an interpretation index of the data to be evaluated; and an extraction unit that selects the learning data useful for a user to interpret the predicted value of the data to be evaluated, wherein index management information for managing an interpretation index of the learning data is stored, the index calculation unit calculates the interpretation index of the data to be evaluated, and the extraction unit calculates a selection index based on the interpretation index of the data to be evaluated and the interpretation index of the learning data, selects the learning data based on the selection index, and outputs display information for presenting information indicating a processing result.

Abstract: Provided is a technique for reducing the calculation load in navigation management of a moving body within a freely navigable space. The system has a storage unit 21 for storing movement locus data showing a plurality of movement loci in which a moving body is moved in a two-dimensional or three-dimensional space in which free movement is possible; a network model management unit 11 for integrating sections approximated by the plurality of movement loci on the basis of the movement locus data, and generating a network model showing a route within the space; a navigation schedule calculation unit 13 for calculating a navigation schedule when a plurality of moving bodies planning to pass within the space navigate within that space according to the network model route; and a display processing unit 15 for outputting the calculated navigation schedule to a display apparatus.

Abstract: A traffic control assisting system (“assisting system”) stores action data on an action of a moving object, geographic data in which geographic attribute information, which is information on a reference of movement of the moving object, is imparted to individual segments that are meshes into which a map is divided, and responsiveness data on the moving object's responsiveness to an instruction. The assisting system estimates an ideal action of the moving object based on the responsiveness data; calculates a difference between the estimated action and an action in the action data; updates the responsiveness data based on a result of the calculation; estimates probability of presence of the moving object at certain coordinates at each time point based on the action data, the geographic data, and the responsiveness data and generates a geographic E map; and predicts future coordinates of the moving object based on the geographic E map.

Abstract: A toilet seat lifter is arranged for pivotally moving a toilet seat with respect to a toilet bowl. The toilet seat lifter includes an actuator having a coupling portion adapted for outwardly extending from an outer peripheral edge of the toilet seat and a hand gripping portion extending from the coupling portion at a position away from a peripheral edge of the toilet seat. The hand gripping portion of the actuator is adapted for being held to pivotally lift up the toilet seat from the toilet bowl at an upright unfolded position and to pivotally drop down to the toilet bowl at a lay flat folded position without directly contacting with the toilet seat by a hand of a user for sanitary purpose.