Task arrangement execution method, device and equipment of man-machine interaction engine

The task scheduling method for a human-computer interaction engine addresses the inefficiencies in executing AI tasks by analyzing user behavior and system status to enhance intelligent task orchestration and execution.

CN119201372APending Publication Date: 2024-12-27MATTER INNOVATION PTE LTD
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Patent Information

Application Number
CN202410097725.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-01-23
Publication Date
2024-12-27

AI Technical Summary

Technical Problem

Current touch screen operations on mobile devices are inadequate for efficiently executing complex AI tasks due to the lack of global system status perception and user behavior analysis, limiting intelligent task orchestration and execution.

Method used

A task scheduling method for a human-computer interaction engine that includes receiving user requests, analyzing system status and user behavior, determining intentions, and executing tasks in a predefined order using AI models to enhance intelligent task orchestration.

Benefits of technology

Enables intelligent and efficient execution of AI tasks by actively perceiving system status and user behaviors, thereby improving automated task scheduling and execution capabilities.

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Abstract

The invention provides a task arrangement execution method, device and equipment of a man-machine interaction engine, and relates to the technical field of computer task arrangement. The task arrangement execution method of the man-machine interaction engine comprises the following steps: receiving a request of a user; acquiring state information of the system; analyzing and processing previous operation behaviors of the user to obtain common operation behaviors of the user; determining the intention of the user according to the request of the user, the state information of the system and the common operation behavior of the user; arranging at least one task needing to be executed according to the intention of the user to obtain an execution sequence of each task; and executing the corresponding tasks in sequence according to the execution sequence.
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Description

Technical Field

[0001] The present disclosure relates to the technical field of computer task scheduling, and in particular to a task scheduling execution method, device, equipment, computer-readable storage medium and computer program product for a human-computer interaction engine. Background Art

[0002] With the gradual increase in AI (artificial intelligence) applications such as large models, current traditional touch screen operations on mobile phones / tablets can no longer serve the future AI automated task processing well.

[0003] Therefore, how to more intelligently access the automated task orchestration and execution of AI applications is one of the core issues that need to be addressed in the design and development of future AI operating systems (OS). Summary of the invention

[0004] The present disclosure provides a task scheduling execution method for a human-computer interaction engine.

[0005] According to one aspect of the present disclosure, a method for scheduling and executing tasks in a human-computer interaction engine is provided, comprising: receiving a user's request; obtaining system status information; analyzing and processing the user's previous operating behaviors to obtain the user's commonly used operating behaviors; determining the user's intention based on the user's request, the system status information, and the user's commonly used operating behaviors; scheduling and processing at least one task to be executed based on the user's intention to obtain the execution order of each task; and executing the corresponding tasks in sequence according to the execution order.

[0006] According to another aspect of the present disclosure, a task scheduling and execution device of a human-computer interaction engine is provided, including: a first receiving module for receiving a user's request; an acquisition module for acquiring system status information; an analysis module for analyzing and processing the user's previous operation behaviors to obtain the user's commonly used operation behaviors; an artificial intelligence large model module for determining the user's intention based on the user's request, the system's status information and the user's commonly used operation behaviors; an artificial intelligence engine module for scheduling and processing at least one task to be executed according to the user's intention to obtain the execution order of each task; and an execution module for executing corresponding tasks in sequence according to the execution order.

[0007] According to yet another aspect of the present disclosure, a task orchestration execution device of a human-computer interaction engine is provided, wherein the task orchestration execution device is connected to at least one processor and at least one memory, and a computer program is stored in the at least one memory, wherein when the computer program is executed by the at least one processor, the at least one processor executes the task orchestration execution method of the human-computer interaction engine.

[0008] According to yet another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the processor executes a task scheduling execution method of a human-computer interaction engine.

[0009] According to yet another aspect of the present disclosure, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the processor executes a task scheduling execution method of a human-computer interaction engine.

[0010] According to one or more embodiments of the present disclosure, it is possible to actively perceive the system's status information and the user's common operating behaviors, and by analyzing the user's intentions, orchestrate and execute at least one task to be performed, thereby accelerating AI automation in calling the software interface (UI).

[0011] These and other aspects of the disclosure will be apparent from and elucidated with reference to the embodiments described hereinafter. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in accordance with the present disclosure and should not be regarded as limiting the scope of the present disclosure.

[0013] Figure 1 A flowchart illustrating a method for executing task scheduling in a human-computer interaction engine according to an exemplary embodiment;

[0014] Figure 2 To illustrate a method according to an exemplary embodiment Figure 1 A flowchart of some example processes in the method;

[0015] Figure 3 A schematic block diagram illustrating a task scheduling execution device of a human-computer interaction engine according to an exemplary embodiment; and

[0016] Figure 4 A block diagram is shown that illustrates an exemplary computer device that can be used in the exemplary embodiments. DETAILED DESCRIPTION

[0017] In the present disclosure, unless otherwise specified, the use of the terms "first", "second", etc. to describe various elements is not intended to limit the positional relationship, timing relationship, or importance relationship of these elements, and such terms are only used to distinguish one element from another element. In some examples, the first element and the second element may refer to the same instance of the element, and in some cases, based on the description of the context, they may also refer to different instances.

[0018] The terms used in the description of various examples described in this disclosure are only for the purpose of describing specific examples and are not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, the element can be one or more. As used herein, the term "plurality" means two or more, and the term "based on" should be interpreted as "based at least in part on". In addition, the terms "and / or" and "at least one of..." cover any one of the listed items and all possible combinations.

[0019] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0020] Flowcharts are used in this disclosure to illustrate the operations performed by the system according to the embodiments of the present disclosure. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the various steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0021] When the current operating system executes complex AI tasks, the local human-computer interaction engine, after receiving the processing results from the cloud, will use the corresponding software interface operation tools of each platform. For example, the Android operating system can generally use UIautomator to complete the operation of the application software interface, thereby realizing the execution of complex AI tasks.

[0022] However, the APP (application) control and system control in existing operating systems lack the ability to globally perceive the system's status information and analyze users' common operating behaviors. In addition, the control capabilities for traditional applications are single and are not specifically designed to support the execution of AI application tasks.

[0023] In order to enable more intelligent access to automated task scheduling and execution of AI applications, the present disclosure provides a task scheduling and execution method for a human-computer interaction engine.

[0024] Exemplary embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0025] Figure 1 The flowchart is a diagram illustrating a method 100 for executing task orchestration of a human-computer interaction engine according to an exemplary embodiment.

[0026] The task scheduling execution method 100 of the human-computer interaction engine provided in this embodiment can be executed by the task scheduling execution device of the human-computer interaction engine, and the task scheduling execution device of the human-computer interaction engine can be implemented by software and / or hardware. The task scheduling execution device of the human-computer interaction engine can be composed of two or more physical entities, or can be composed of one physical entity. Generally speaking, the task scheduling execution device of the human-computer interaction engine can be a terminal device, such as a mobile phone, a tablet, etc.

[0027] The following description will be made by taking a computer device as the subject of the task scheduling execution method 100 for executing the human-computer interaction engine as an example.

[0028] refer to Figure 1 , method 100 includes steps S110 to S170.

[0029] In step S110, a user's request is received. As an example, receiving the user's request can be performed by automatic speech recognition (ASR), that is, converting the vocabulary content in the user's voice into computer-readable input. For another example, receiving the user's request can also be completed by the user manually typing text, and the present disclosure is not limited to this. In some embodiments, the request may include asking the human-computer interaction engine to send WeChat, schedule a meeting, send an email, etc. For example, a user can say to the human-computer interaction engine, "Please tell my mother that I will not be home for dinner tonight." For another example, a user can say to the human-computer interaction engine, "Please help me book a meeting with Mr. Li on Wednesday afternoon."

[0030] In step S120, the system status information is obtained. In some embodiments, the system status information may include at least one of the focus, position, or size of each active user interface of the application. In some embodiments, the system status information may include the power status or the current mode. For example, after obtaining the current system status information of "low power state and do not disturb mode", when the user says to the human-computer interaction engine "please tell my mother that I will not be home for dinner tonight", the human-computer interaction engine is more inclined to choose to save power and not disturb the user's WeChat or text message method, rather than choosing to consume power and disturb the user's phone call method.

[0031] In step S130, the user's previous operation behavior is analyzed and processed to obtain the user's commonly used operation behavior. In some embodiments, the user's commonly used operation behavior includes at least one of the applications installed by the user, the applications opened, the frequently used applications, and the contacts frequently communicated with. For example, in the case where the human-computer interaction engine described above tends to send WeChat or send text messages, when the human-computer interaction engine obtains that the user's commonly used operation behavior is to use WeChat instead of text messages, then the human-computer interaction engine is more inclined to select the more frequently used application, that is, to send WeChat.

[0032] In step S140, the user's intention is determined based on the user's request, the system's status information, and the user's common operating behaviors. In some embodiments, the human-computer interaction engine includes an artificial intelligence big model, and the determination of the user's intention is achieved through the artificial intelligence big model. According to some embodiments, the artificial intelligence big model can be deployed in the cloud. In some embodiments, the selection of a specific large-scale pre-trained model or a basic model for the artificial intelligence big model can be determined according to actual application requirements or experiments. For example, the artificial intelligence big model can determine that the user's intention is to use WeChat text to send a message to the mother to tell her that she will not be home for dinner at night based on the user's request after automatic voice recognition of "help me tell my mother that I will not be home for dinner at night", the system's "low power state and do not disturb mode" status information, and the user's common communication method with the mother is WeChat text.

[0033] In step S150, at least one task to be executed is arranged according to the user's intention to obtain the execution order of each task. For example, in the case where it is determined that the user's intention is to use WeChat text to send a message to his mother to tell her that he will not be home for dinner at night, it is necessary to arrange and process multiple tasks of opening and editing WeChat to obtain the execution order of each task such as opening WeChat and the chat window of the user's mother, inputting messages, and sending information. In some embodiments, the human-computer interaction engine includes an artificial intelligence engine, and the arrangement and processing of at least one task to be executed to obtain the execution order of each task is achieved by the artificial intelligence engine. In some embodiments, an artificial intelligence engine, such as a neural network-like engine, can realize automatic speech recognition and transmit the recognition results to an artificial intelligence large model, and the artificial intelligence engine can execute specific functions or applications according to the analysis results of the artificial intelligence large model.

[0034] In step S170, the corresponding tasks are executed in sequence according to the execution order.

[0035] Method 100 has the ability to actively perceive the system status information and the user's common operating behaviors, and determines the user's intention through the user's request, the system status information and the user's common operating behaviors, and according to the intention, arranges and processes at least one task to be executed, which is conducive to more intelligent access to the automated task arrangement and execution of AI applications.

[0036] Figure 2 To illustrate a method according to an exemplary embodiment Figure 1 A flowchart of a portion of an exemplary process in method 100. Figure 3As shown, according to some embodiments, the state information of the system may include view tree information of each active user interface of the application. The view tree information includes components of the active user interface and the hierarchical structure of different components. Step S170, executing the corresponding tasks in sequence according to the execution order may include:

[0037] Step S210: adding a mark to the specific view tree information of the application to be executed for subsequent identification; and

[0038] Step S220: Based on the execution order and the mark, locate the components of the active user interface for the required operation and execute the corresponding task.

[0039] According to some embodiments, the component of the active user interface includes at least one of a text box, an edit view, a button, and an image view.

[0040] According to some embodiments, step S210, adding a mark to the specific view tree information of the application to be executed may include: adding metadata (meta) information to the specific view tree information of the application to be executed. In some embodiments, the metadata information includes at least one of a data element, a data attribute, a data structure, or related data. For example, when the execution order of each task such as opening WeChat and the chat window of the user's mother, inputting a message, and sending a message is obtained, the metadata information of the components of the active user interface such as WeChat, the chat window of the user's mother, the message input, and the message sending button can be marked. Therefore, in step S220, there is no need to search for the components of each active user interface one by one in the traditional way, but based on the execution order and the metadata information of the components of each active user interface in the window where the WeChat contact mother is located in step S210, the components of the active user interface for the required operation can be quickly located and the corresponding text message can be sent.

[0041] Reference again Figure 1 Alternatively or additionally, method 100 may further include step S160.

[0042] In step S160, before executing the corresponding tasks in step S170 in sequence according to the execution order, a confirmation operation of the user is received. However, it can be understood that step S160 is not necessary, and the human-computer interaction engine can also determine the user's default operation according to the user's habit of multiple operations, and directly execute the corresponding task in step S170.

[0043] Figure 3 FIG. 1 is a schematic block diagram illustrating a task scheduling execution device 300 of a human-computer interaction engine according to an exemplary embodiment.

[0044] like Figure 3As shown, the task scheduling execution device 300 of the human-computer interaction engine includes: a first receiving module 310, an acquisition module 320, an analysis module 330, an artificial intelligence large model module 340, an artificial intelligence engine module 350 and an execution module 370.

[0045] The first receiving module 310 is configured to receive a user's request.

[0046] The acquisition module 320 is configured to acquire system status information.

[0047] The analysis module 330 is configured to analyze and process the user's previous operation behaviors to obtain the user's commonly used operation behaviors.

[0048] The artificial intelligence big model module 340 is configured to determine the user's intention based on the user's request, the system's status information, and the user's common operating behaviors.

[0049] The artificial intelligence engine module 350 is configured to arrange at least one task to be executed according to the user's intention to obtain the execution order of each task.

[0050] The execution module 370 is configured to execute the corresponding tasks in sequence according to the execution order.

[0051] Reference again Figure 3 Alternatively or additionally, the device 300 may further include a second receiving module 360 ​​.

[0052] The second receiving module 360 ​​is configured to receive the user's confirmation operation before executing the corresponding tasks in sequence according to the execution order.

[0053] It should be understood that Figure 3 The various modules of the apparatus 300 shown in FIG. Figure 1 The steps S110-S170 in the method 100 described above correspond to each other. Therefore, the operations, features and advantages described above for the method 100 are also applicable to the apparatus 300 and the modules included therein. For the sake of brevity, some operations, features and advantages are not described in detail here.

[0054] Although specific functions are discussed above with reference to specific modules, it should be noted that the functions of the various modules discussed herein may be divided into multiple modules, and / or at least some functions of multiple modules may be combined into a single module. The specific module discussed herein performing an action includes the specific module itself performing the action, or alternatively the specific module calling or otherwise accessing another component or module that performs the action (or performs the action in conjunction with the specific module). Therefore, the specific module that performs an action may include the specific module itself that performs the action and / or another module that the specific module calls or otherwise accesses to perform the action.

[0055] It should also be understood that various techniques may be described herein in the general context of software hardware elements or program modules. Figure 3 The various modules described can be implemented in hardware or in hardware in combination with software and / or firmware. For example, these modules can be implemented as computer program codes / instructions, which are configured to be executed in one or more processors and stored in a computer-readable storage medium. Alternatively, these modules can be implemented as hardware logic / circuits. For example, in some embodiments, one or more of the first receiving module 310, the acquisition module 320, the analysis module 330, the artificial intelligence large model module 340, the artificial intelligence engine module 350, the second receiving module 360, and the execution module 370 can be implemented together in a system on chip (System on Chip, SoC). SoC may include an integrated circuit chip (which includes a processor (e.g., a central processing unit (CPU), a microcontroller, a microprocessor, a digital signal processor (DSP), etc.), a memory, one or more communication interfaces, and / or one or more components in other circuits), and may optionally execute the received program code and / or include embedded firmware to perform functions.

[0056] According to one aspect of the present disclosure, a computer device is provided, which includes at least one memory, at least one processor, and a computer program stored in the at least one memory. The at least one processor is configured to execute the computer program to implement the steps of any method embodiment described above. The task scheduling execution device of the human-computer interaction engine may include the computer device.

[0057] According to one aspect of the present disclosure, a task scheduling execution device of a human-computer interaction engine is provided, wherein the task scheduling execution device of the human-computer interaction engine is connected to at least one processor and at least one memory, and a computer program is stored in the at least one memory. The at least one processor is configured to execute the computer program to implement the steps of any method embodiment described above.

[0058] According to one aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any method embodiment described above are implemented.

[0059] According to one aspect of the present disclosure, a computer program product is provided, which includes a computer program. When the computer program is executed by a processor, the steps of any method embodiment described above are implemented.

[0060] In the following, combined Figure 4 Illustrative examples of such a computer device, computer-readable storage medium, and computer program product are described.

[0061] Figure 4 An example configuration of a computer device 400 that can be used to implement the methods described herein is shown. For example, Figure 1 The power management system 100 shown in FIG. 4 may include an architecture similar to the computer device 400. The apparatus 300 may also be implemented in whole or at least in part by the computer device 400 or a similar device or system.

[0062] Computer device 400 may include at least one processor 402, memory 404, communication interface(s) 406, a display device 408, other input / output (I / O) devices 410, and one or more mass storage devices 412, all capable of communicating with one another, such as via a system bus 414 or other appropriate connections.

[0063] Processor 402 may be a single processing unit or multiple processing units, all of which may include a single or multiple computing units or multiple cores. Processor 402 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and / or any device that manipulates signals based on operating instructions. Among other capabilities, processor 402 may be configured to obtain and execute computer-readable instructions stored in memory 404, mass storage device 412, or other computer-readable media, such as program code for operating system 416, program code for application program 418, program code for other programs 420, and the like.

[0064] The memory 404 and the mass storage device 412 are examples of computer-readable storage media for storing instructions that are executed by the processor 402 to implement the various functions described above. For example, the memory 404 may generally include both volatile memory and non-volatile memory (e.g., RAM, ROM, etc.). In addition, the mass storage device 412 may generally include a hard drive, a solid-state drive, a removable medium, including external and removable drives, a memory card, a flash memory, a floppy disk, an optical disk (e.g., a CD, a DVD), a storage array, a network attached storage, a storage area network, etc. The memory 404 and the mass storage device 412 may all be collectively referred to herein as memory or computer-readable storage media, and may be a non-transitory medium capable of storing computer-readable, processor-executable program instructions as computer program code, which may be executed by the processor 402 as a specific machine configured to implement the operations and functions described in the examples herein.

[0065] A number of programs may be stored on mass storage device 412. These programs include operating system 416, one or more application programs 418, other programs 420, and program data 422, and they may be loaded into memory 404 for execution. Examples of such applications or program modules may include, for example, computer program logic (e.g., computer program code or instructions) for implementing the following components / functions: method 200 (including any suitable steps of method 200), and / or additional embodiments described herein.

[0066] Although in Figure 4 4 is illustrated as being stored in the memory 404 of the computer device 400, but the modules 310, 320, 330, 340, 350, 360, and 370, or portions thereof, may be implemented using any form of computer-readable media accessible by the computer device 400. As used herein, "computer-readable media" includes at least two types of computer-readable media, namely, computer-readable storage media and communication media.

[0067] Computer-readable storage media include volatile and non-volatile, removable and non-removable media implemented by any method or technology for storing information, such as computer-readable instructions, data structures, program modules or other data. Computer-readable storage media include but are not limited to RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD), or other optical storage device, magnetic cassette, magnetic tape, magnetic disk storage device or other magnetic storage device, or any other non-transmission medium that can be used to store information for access by a computer device. In contrast, communication media can embody computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transmission mechanism. Computer-readable storage media defined herein do not include communication media.

[0068] One or more communication interfaces 406 are used to exchange data with other devices, such as through a network, direct connection, etc. Such communication interfaces can be one or more of the following: any type of network interface (e.g., a network interface card (NIC)), a wired or wireless (such as IEEE 802.11 wireless LAN (WLAN)) wireless interface, a Worldwide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth™ interface, a Near Field Communication (NFC) interface, etc. The communication interface 406 can facilitate communication within a variety of network and protocol types, including wired networks (e.g., LAN, cable, etc.) and wireless networks (e.g., WLAN, cellular, satellite, etc.), the Internet, etc. The communication interface 406 can also provide communication with external storage devices (not shown) such as storage arrays, network attached storage, storage area networks, etc.

[0069] In some examples, a display device 408 such as a monitor may be included for displaying information and images to the user. Other I / O devices 410 may be devices that receive various inputs from the user and provide various outputs to the user, and may include touch input devices, gesture input devices, cameras, keyboards, remote controls, mice, printers, audio input / output devices, and the like.

[0070] The technology described herein can be supported by these various configurations of the computer device 400, and is not limited to the specific examples of the technology described herein. For example, the functionality can also be implemented in whole or in part on the "cloud" by using a distributed system. The cloud includes and / or represents a platform for resources. The platform abstracts the underlying functions of the hardware (e.g., server) and software resources of the cloud. Resources can include applications and / or data that can be used when performing computing processing on a server away from the computer device 400. Resources can also include services provided over the Internet and / or through a subscriber network such as a cellular or Wi-Fi network. The platform can abstract resources and functions to connect the computer device 400 to other computer devices. Therefore, the implementation of the functions described herein can be distributed throughout the cloud. For example, the functions can be implemented partially on the computer device 600 and partially through a platform that abstracts the functions of the cloud.

[0071] Although the present disclosure has been illustrated and described in detail in the drawings and the foregoing description, such illustration and description should be considered illustrative and exemplary rather than restrictive; the present disclosure is not limited to the disclosed embodiments. By studying the drawings, the disclosure and the appended claims, those skilled in the art will be able to understand and implement variations to the disclosed embodiments when practicing the claimed subject matter. In the claims, the word "comprising" does not exclude other elements or steps that are not listed, and the term "based on" should be interpreted as "based at least in part on". The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

[0072] The above descriptions are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A task scheduling execution method of a human-computer interaction engine, the method comprising: Receive user requests; Get system status information; Analyze and process the user's previous operation behaviors to obtain the user's commonly used operation behaviors; Determining the user's intention according to the user's request, the system's status information, and the user's common operation behavior; Arrange at least one task to be executed according to the user's intention to obtain an execution order of each task; as well as The corresponding tasks are executed in sequence according to the execution order.

2. The method according to claim 1, wherein: The state information of the system includes view tree information of each active user interface of the application, the view tree information includes components of the active user interface and the hierarchical structure of different components, and the corresponding tasks are executed in sequence according to the execution order, including: Adding a tag to the specific view tree information of the application to be executed for subsequent identification; and Based on the execution order and the mark, the components of the active user interface required for the operation are located and the corresponding tasks are executed.

3. The method according to claim 2, wherein: Add tags to the specific view tree information of the application to be executed, including: Metadata information is added to the specific view tree information of the application to be executed.

4. The method according to claim 3, wherein: The metadata information includes at least one of data elements, data attributes, data structures or related data.

5. The method according to claim 2, wherein: The components of the active user interface include at least one of a text box, an edit view, a button, and an image view.

6. The method according to claim 1, wherein: The human-computer interaction engine includes an artificial intelligence big model, and the determination of the user's intention is achieved through the artificial intelligence big model.

7. The method according to claim 1, wherein: The human-computer interaction engine includes an artificial intelligence engine, and arranges and processes at least one task to be executed, and the execution order of each task is obtained by the artificial intelligence engine.

8. The method according to any one of claims 1 to 7, wherein: The user's frequently used operation behaviors include at least one of the following: applications installed by the user, applications opened by the user, applications used frequently, and contacts with whom the user frequently communicates.

9. The method according to any one of claims 1 to 7, wherein: The state information of the system includes at least one of a focus, a position, or a size of each active user interface of the application.

10. The method according to any one of claims 1 to 7, further comprising: Before executing the corresponding tasks in sequence according to the execution order, receiving the user's confirmation operation.

11. A task scheduling execution device of a human-computer interaction engine, comprising: A first receiving module, used to receive a user's request; An acquisition module is used to obtain system status information; An analysis module, used to analyze and process the user's previous operation behaviors to obtain the user's commonly used operation behaviors; An artificial intelligence large model module, used to determine the user's intention based on the user's request, the system's status information, and the user's common operation behavior; An artificial intelligence engine module, used to arrange at least one task to be executed according to the user's intention, and obtain the execution order of each task; as well as The execution module is used to execute the corresponding tasks in sequence according to the execution order.

12. The apparatus according to claim 11, further comprising: The second receiving module is used to receive a confirmation operation of the user before executing the corresponding tasks in sequence according to the execution order.

13. A task scheduling execution device of a human-computer interaction engine, the task scheduling execution device is connected to at least one processor and at least one memory, a computer program is stored in the at least one memory, in, When the computer program is executed by the at least one processor, the at least one processor is caused to perform the method according to any one of claims 1 to 10.

14. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor is caused to execute the method according to any one of claims 1 to 10.

15. A computer program product, comprising a computer program, which, when executed by a processor, causes the processor to perform the method according to any one of claims 1 to 10.

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