JP-7854893-B2 - Computer system

Inventors

• 松下 康平
• 間瀬 正啓
• 森 靖英

Assignees

• 株式会社日立製作所

Dates

Publication Date

20260507

Application Date

20220802

Claims (7)

1. A computer system, The computing unit and Includes a storage device, The aforementioned storage device stores a model that outputs value-based predictive behavior for input data, The aforementioned computing device is To explain the first prediction process by the model that outputs a first predicted action from the first input data, we obtain explanatory data that includes the values of multiple explanatory elements, Determine the contribution of each of the aforementioned multiple explanatory elements to the value and the uncertainty of the value in the first prediction process. Based on the contribution values, the risk elements in the first prediction process are detected in the plurality of explanatory elements. The information on the aforementioned risk factors is presented, The data to be explained above is the first predicted behavior, The computing device is a computer system that searches for and presents action improvement proposals for the first predicted action that improve the value and the uncertainty of the value by changing the values of some elements in the first predicted action .
2. A computer system according to claim 1, The computing device is a computer system that detects, as risk elements, explanatory elements that contribute to worsening both the value and the uncertainty of the value.
3. A computer system according to claim 1, The aforementioned elements include the aforementioned risk element, the computer system.
4. A computer system according to claim 1, A computer system in which some of the aforementioned elements are specified by the user.
5. A computer system according to claim 1, The aforementioned computing device is The first predicted behavior and the proposed behavior improvement are evaluated by simulation. A computer system that presents the results of the aforementioned evaluation.
6. A computer system according to claim 1, The uncertainty of the aforementioned value is the Aleatoric uncertainty of the aforementioned value, The computing device is a computer system that searches for proposed improvements to the action in an action where the epithemic uncertainty of the value is below a threshold.
7. The way the system executes, The system stores a model that outputs value-based predictive behavior for input data, The aforementioned method, The system acquires explanatory data, which includes the values of multiple explanatory elements, for explaining the first prediction process by the model that outputs a first predicted action from the first input data. The system determines the contribution of each of the plurality of explanatory elements to the value and the uncertainty of the value in the first prediction process, The system detects risk elements in the first prediction process based on the contribution values in the plurality of explanatory elements. The system presents information on the risk elements, The data to be explained above is the first predicted behavior, The method described above is a method in which the system searches for and presents action improvement proposals that improve the value and the uncertainty of the value for the first predicted action by changing the values of some elements in the first predicted action.

Description

This disclosure relates to a computer system, for example, a computer system that assists user decision-making. As background technology to this disclosure, for example, International Publication No. 2022/024559 (Patent Document 1) is known. Patent Document 1 discloses a medical support system that assists physicians in performing medical procedures. For example, it discloses that "the medical support system comprises a control unit, a recognition unit that recognizes the surgical field environment, and a machine learning model that estimates the actions to be performed by the medical support system based on the recognition results of the recognition unit. The control unit outputs judgment basis information regarding the actions estimated by the machine learning model to an information display unit. The control unit further comprises a calculation unit that calculates the confidence level regarding the estimation results of the machine learning model, and outputs the confidence level to the information display unit." (See abstract, for example). International Publication No. 2022/024559 This figure shows an example of the hardware configuration of a computer system, including a decision support system according to one embodiment of this specification.This figure shows an example of a computer system's software configuration.This shows an example of the structure of information included in the status transmitted from the operational management system to the decision support system.This shows an example of the information structure included in the predicted behavior by the behavior prediction unit.This shows an example of the information structure included in the behavioral value and the uncertainty of the behavioral value, as predicted by the behavioral value prediction unit.This shows an example of the information structure included in the contribution values of elements to behavioral value and uncertainty, as determined by the XAI execution unit.This shows an example of the information structure included in behavior improvement proposals, as developed by the Behavior Improvement Proposal Exploration Department.This shows an example of the information structure included in the evaluation values of the original behavior and improved behavior by the behavior evaluation unit.This flowchart shows an embodiment of the processing procedure when a reinforcement learning model, specifically a Q-learning model, is applied to the operation and management of power.A flowchart illustrating an example of a method for extracting high-risk factors in step S13 is shown.A flowchart illustrating another example of a method for extracting high-risk factors in step S13 is shown.An example of the XAI settings screen is shown.An example of a screen displaying risk factors is shown.An example of a behavior improvement suggestion screen generated by the behavior improvement suggestion suggestion unit is shown.An example of the behavioral assessment results screen is shown. The embodiments of the present invention will be described in detail below with reference to the drawings. Where necessary for convenience, the description will be divided into multiple sections or embodiments. Unless otherwise specified, these are not unrelated; one may be a modification, detail, or supplementary explanation of part or all of the other. Furthermore, when referring to the number of elements (including quantity, numerical value, amount, range, etc.), unless otherwise specified or clearly limited to a specific number in principle, the number is not limited to that specific number and may be greater than or less than that number. The system in one embodiment of this specification may be a physical computer system (one or more physical computers) or a system built on a cloud infrastructure or other computing resource group (multiple computing resources). The computer system or computing resource group may include one or more interface devices (e.g., including communication devices and input/output devices), one or more storage devices (e.g., including memory (main memory) and auxiliary storage devices), and one or more arithmetic units. When a program containing instruction codes is executed by an arithmetic unit (AGS) to realize its functionality, the defined processing is carried out using memory devices and/or interface devices as appropriate; therefore, the functionality may be at least a part of the AGS. The processing described with functionality as the subject may be processing performed by the AGS or a system having that AGS. The program may also be installed from the program source. The program source may be, for example, a program distribution computer or a computer-readable storage medium (e.g., a computer-readable non-transient storage medium). The descriptions of each function are examples; multiple functions may be combined into one, or one function may be divided into multiple functions. Figure 1 shows an example of the hardware confi