Game character control optimization method, device, electronic device and medium

Abstract

The present application discloses a game character control optimization method, device, electronic device and medium, which are applied to the field of game technology. The game character control optimization method comprises: obtaining first game character information of a first game character and second game character information corresponding to a second game character, wherein the first game character is controlled by a user and the second game character is controlled by the human-computer interaction system; based on the first game character information and the second game character information, performing a behavior decision analysis on the second game character to obtain control action information corresponding to the second game character; based on the control action information, generating game control signal data; and based on the game control signal data, controlling the second game character. The present application solves the technical problem of low accuracy of human-computer interaction.

Description

Technical Field

[0001] The present application relates to the field of game technology, and in particular to a method, device, electronic device and medium for optimizing game character control. Background Art

[0002] With the rapid development of science and technology, game technology has become more and more mature. Due to the rapid update of MOBA (Multiplayer Online Battle Arena) games, users need to improve their gaming skills through human-computer training mode. At present, the second game character in the game determines the game control behavior through the decision tree method, and the control behavior determined by the decision tree method is fixed and single, and cannot provide effective feedback on the user's control behavior, resulting in low accuracy of human-computer interaction. Summary of the invention

[0003] The main purpose of this application is to provide a game character control optimization method, device, electronic device and medium, aiming to solve the technical problem of low accuracy of human-computer interaction in the prior art.

[0004] To achieve the above-mentioned purpose, the present application provides a game character control optimization method, which is applied to a game character control optimization device, and the game character control optimization method comprises:

[0005] Acquire first game character information of a first game character and second game character information corresponding to a second game character, wherein the first game character is controlled by a user and the second game character is controlled by the human-computer interaction system;

[0006] According to the first game character information and the second game character information, a behavior decision analysis is performed on the second game character to obtain control action information corresponding to the second game character;

[0007] generating game control signal data according to the control action information;

[0008] The second game character is controlled according to the game control signal data.

[0009] To achieve the above-mentioned purpose, the present application further provides a game character control optimization device, which is applied to a game character control optimization device, and the game character control optimization device comprises:

[0010] An acquisition module, used to acquire first game character information of a first game character and second game character information corresponding to a second game character, wherein the first game character is controlled by a user and the second game character is controlled by the human-computer interaction system;

[0011] An analysis module, configured to perform a behavior decision analysis on the second game character based on the first game character information and the second game character information, and obtain control action information corresponding to the second game character;

[0012] A generating module, used for generating game control signal data according to the control action information;

[0013] The control module is used to control the second game character according to the game control signal data.

[0014] The present application also provides an electronic device, comprising: a memory, a processor, and a program of the game character control optimization method stored in the memory and executable on the processor. When the program of the game character control optimization method is executed by the processor, the steps of the game character control optimization method as described above can be implemented.

[0015] The present application also provides a computer-readable storage medium, on which is stored a program for implementing a game character control optimization method. When the program for the game character control optimization method is executed by a processor, the steps of the game character control optimization method as described above are implemented.

[0016] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned game character control optimization method when executed by a processor.

[0017] The present application provides a game character control optimization method, device, electronic device and medium. Compared with determining the game control behavior of the second game character through a decision tree method, the present application obtains first game character information of the first game character and second game character information corresponding to the second game character, wherein the first game character is controlled by the user and the second game character is controlled by the human-computer interaction system; based on the first game character information and the second game character information, a behavior decision analysis is performed on the second game character to obtain control action information corresponding to the second game character; based on the control action information, game control signal data is generated; based on the game control signal data, the second game character is controlled, thereby achieving matching the control behavior of the second game character according to the user's game character type, avoiding the technical defect of low accuracy of human-computer interaction caused by the fixed and single control behavior determined by the decision tree method, and failing to provide effective feedback on the user's control behavior, thereby improving the accuracy of human-computer interaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0020] Figure 1 This is a flow chart of the first embodiment of the game character control optimization method of the present application;

[0021] Figure 2 This is a flow chart of the second embodiment of the game character control optimization method of the present application;

[0022] Figure 3 This is a schematic diagram of the device structure of the hardware operating environment involved in the game character control optimization method in the embodiment of the present application.

[0023] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0024] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of this application.

[0025] Embodiment 1

[0026] The present application embodiment provides a game character control optimization method. In the first embodiment of the game character control optimization method of the present application, refer to Figure 1 , the game character control optimization method comprises:

[0027] Step S10, obtaining first game character information of a first game character and second game character information corresponding to a second game character, wherein the first game character is controlled by a user and the second game character is controlled by the human-computer interaction system;

[0028] In the present embodiment, it should be noted that the human-computer interaction system is a system for controlling a game character that interacts with a user. The second game character may be an invulnerable object, an attackable object, or a game character in the opposite camp to the user. When the second game character is the game character in the opposite camp to the user, usually only based on the character state of the second game character (for example, the blood volume of the second game character), a fixed attack or evasion action is performed, that is, when the blood volume of the second game character is low, an evasion action is performed, and when the blood volume of the second game character is not low, an attack action is performed. When the character state of the first game character changes, control behavior is still performed only based on the character state of the second game character, which may easily lead to a situation where effective feedback on the user's control behavior cannot be given. Therefore, it is necessary to comprehensively determine the control behavior of the second game character by combining the first game character information and the second game character information of the second game character.

[0029] Exemplarily, step S10 includes: obtaining first character attributes and first character status corresponding to the first game character to obtain first game character information of the first game character, and obtaining second character attributes and second character status corresponding to the second game character to obtain second game character information of the second game character.

[0030] Step S20, performing a behavior decision analysis on the second game character according to the first game character information and the second game character information, and obtaining control action information corresponding to the second game character;

[0031] In this embodiment, it should be noted that the control action information is information about the control action on the second game character, wherein the control action information is information about the selection and parameters of the control action, and one of the control actions controls the second game character to perform an action. For example, the first control action can control the second game character to perform an attack action, the second control action can control the second game character to perform an evasive action, and the third control action can control the second game character to perform a gain action (for example, increasing the health and / or mana of the second game character through game equipment and / or game environment gain). In addition, a function to be achieved by controlling the second game character may correspond to one or more control actions. For example, when the health of the second game character is high and it attacks the first game character, the control process to be achieved by the first control action is to control the second game character to chase the first game character, and the control process to be achieved by the third control action is to increase the health and / or mana of the second game character through game equipment, so that the second game character can provide accurate feedback to the first game character.

[0032] Exemplarily, step S20 includes: concatenating the first game character information and the second game character information to obtain behavior decision input information, performing feature extraction on the behavior decision input information to extract feature information in the behavior decision input information that contributes greatly to decision analysis, and obtaining a feature extraction matrix, and then fully connecting the feature extraction matrix to make a control decision to obtain control action information corresponding to the second game character, wherein the decision input information can be a matrix.

[0033] Step S30, generating game control signal data according to the control action information;

[0034] Step S40: controlling the second game character according to the game control signal data.

[0035] Exemplarily, steps S30 to S40 include: selecting a corresponding control action module based on each control action label in the control action information, and initializing the corresponding control action modules based on each control action score in the control information, and then inputting the control input information of the second game character into the corresponding initialized control action module to generate game control signal data; and controlling the second game character based on the game control signal data.

[0036] Wherein, in step S20, the step of performing a behavior decision analysis on the second game character based on the first game character information and the second game character information to obtain the control action information corresponding to the second game character includes:

[0037] Step S21, predicting the control effect of the second game character according to the first game character information, the second game character information and a preset game control effect prediction model, to obtain a control effect prediction result, wherein the control effect prediction result includes each control effect and a control effect score corresponding to each control effect;

[0038] Step S22, selecting a target control action score greater than or equal to a preset control action score threshold from each of the control action scores;

[0039] Step S23: generating the control action information according to the target control action corresponding to the target control action score.

[0040] In this embodiment, it should be noted that the preset game control effect prediction model is a reinforcement learning model. The preset control effect score threshold is a preset critical value of the control effect score for determining that the control effect of this control decision is relatively strong.

[0041] Exemplarily, steps S21 to S23 include: mapping the feature extraction matrix into a game control effect prediction vector, and using the game control effect prediction vector as a game control effect prediction result, wherein the control effect prediction vector includes a control effect label and a control effect score, the control effect label is an identifier of the type of control effect, and the control effect score indicates the probability that the control effect corresponding to the control effect label is the control effect of this control decision; judging whether there is a target control effect score greater than or equal to a preset control effect score threshold in each of the control effect scores, if there is a target control effect score greater than or equal to the preset control effect score threshold in each of the control effect scores, then generating the control effect information based on the target control effect corresponding to the target control effect score, for example, when the control effect prediction vector is (1, 0, 2, 0.5), it means that the control effect score of the first control effect is 0, and the control effect score of the second control effect is 0.5.

[0042] The embodiment of the present application provides a game character control optimization method. Compared with determining the game control behavior of the second game character through a decision tree method, the embodiment of the present application obtains first game character information of the first game character and second game character information corresponding to the second game character, wherein the first game character is controlled by the user and the second game character is controlled by the human-computer interaction system; based on the first game character information and the second game character information, a behavior decision analysis is performed on the second game character to obtain control action information corresponding to the second game character; based on the control action information, game control signal data is generated; based on the game control signal data, the second game character is controlled, thereby achieving matching the control behavior of the second game character according to the game character type of the user, avoiding the technical defect of low accuracy of human-computer interaction caused by the fixed and single control behavior determined by the decision tree method, and failing to provide effective feedback on the user's control behavior, thereby improving the accuracy of human-computer interaction.

[0043] Embodiment 2

[0044] Further, refer to Figure 2 Based on the first embodiment of the present application, in another embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above description and will not be described in detail later. On this basis, in step S20, the step of performing a behavior decision analysis on the second game character based on the first game character information and the second game character information to obtain the control action information corresponding to the second game character also includes:

[0045] Step A10, predicting the game character behavior of the first game character at the next time step based on the first game character information, the second game character information and a preset game character behavior prediction model, to obtain a first game character behavior prediction result;

[0046] Step A20, generating the control action information according to the game character behavior prediction result and the second game character information.

[0047] Exemplarily, steps A10 to A20 include: inputting a game feature vector jointly constructed by the first game character information and the second game character information into a preset game character behavior prediction model, predicting the game character behavior of the first game character in the next time step, and obtaining a first game character behavior prediction result; and generating the control action information based on the game character behavior prediction result and the second game character information.

[0048] Wherein, in step A10, the step of predicting the game character behavior of the first game character at the next time step based on the first game character information, the second game character information and a preset game character behavior prediction model to obtain the first game character behavior prediction result includes:

[0049] Step A11, constructing a game feature vector of the first game character according to the first game feature information in the first game character information and the second game feature information in the second game character information;

[0050] Step A12: Mapping the game feature vector to the game character behavior of the first game character in the next time step through the preset game character behavior prediction model.

[0051] Exemplarily, step A12 includes: mapping the game feature vector into the game character behavior of the first game character at the next time step by inputting the game feature vector into the preset game character behavior prediction model.

[0052] Wherein, before step S20, before the step of performing a behavior decision analysis on the second game character based on the first game character information and the second game character information to obtain the control action information corresponding to the second game character, the method further includes:

[0053] Step B10, acquiring a first character type corresponding to the first game character, first position information of the first game character, first movement information of the first game character, and first character state information corresponding to the first game character, to obtain the first game character information;

[0054] Step B20, obtaining the second character type corresponding to the second game character, the second position information of the second game character, the second movement information of the second game character and the second character state information corresponding to the second game character to obtain the second game character information.

[0055] Exemplarily, steps B10 to B20 include: obtaining a first image including the first game character, determining a first character type corresponding to the first game character based on the character features of the first game character in the first image, determining first position information corresponding to the first game character based on the first image, obtaining a previous frame of the first image, obtaining a second image, determining motion information corresponding to the first game character based on the second position information of the first game character corresponding to the second image and the first position information, obtaining game equipment, character health and character mana of the game user character, obtaining first character status information corresponding to the game character, and obtaining the first game character information. The specific steps for obtaining the second game character information refer to the above-mentioned content of obtaining the first game character information, which will not be repeated here.

[0056] Among them, in step A11, the step of constructing a game feature vector of the first game character according to the first game feature information in the first game character information and the second game feature information in the second game character information includes:

[0057] Step C10, determining a first role type label corresponding to the first game role based on the first role type, and determining a second role type label corresponding to the second game role based on the second role type;

[0058] Step C20, concatenating the first character type label, the first position information, the first motion information, the first character status information, the second character type label, the second position information, the second motion information and the second character status information into the game feature vector.

[0059] In this embodiment, it should be noted that the character type label is determined by the character features of the game character, and the character type label can be used to characterize the positioning of the game character. For example, the character type can include auxiliary characters and core characters.

[0060] Exemplarily, steps C10 to C20 include: generating a first role type label corresponding to the first game role based on the first role type, and generating a second role type label corresponding to the second game role based on the second role type; splicing the first role type label, the first position information, the first motion information, the first role state information, the second role type label, the second position information, the second motion information, and the second role state information into the game feature vector or the game feature matrix. Wherein, the columns of the game feature matrix correspond to time points, the rows of the matrix correspond to the first game role information and the second game role information, and the values ​​in the matrix are the first role type label, the first position information, the first motion information, the first role state information, the second role type label, the second position information, the second motion information, and the second role state information arranged according to time, wherein the motion information includes at least one of the speed corresponding to the game role and the acceleration corresponding to the game role, and the role state information includes at least one of the health corresponding to the game role, the mana corresponding to the game role, and the equipment corresponding to the game role.

[0061] Since the game character behavior of the first game character in the next time step is affected by multiple factors, the embodiment of the present application matches the game feature vector corresponding to the first game character according to the first character type of the first game character, the first position information of the first game character, the first motion information of the first game character, the first character state of the first game character, the second character type of the second game character, the second position information of the second game character, the second motion information of the second game character and the second character state of the second game character, and fully considers the impact of various factors on the game character behavior. The game feature vector is an input value for predicting the game character behavior, so it provides more decision-making basis for predicting the game character behavior of the first game character in the next time step, and improves the accuracy of game character behavior prediction. The control behavior of the second game character is affected by the game character behavior, thereby further improving the accuracy of human-computer interaction.

[0062] Wherein, in step A12, the game behavior prediction result includes attack behavior information and avoidance behavior information, the control effect information includes avoidance control information and attack control information, and the step of generating the control effect information according to the game character behavior prediction result and the second game character information includes:

[0063] Step D10, when the game character behavior prediction result is the attack behavior information, generating avoidance control information corresponding to the second game character according to the attack behavior information and the second game character information;

[0064] Step D20, when the game character behavior prediction result is the avoidance behavior information, generating attack control information corresponding to the second game character according to the avoidance behavior information and the second game character information.

[0065] Exemplarily, steps D10 to D20 include: when the game character behavior prediction result is the attack behavior information, determining the avoidance control parameters and corresponding gain parameters corresponding to the second game character based on the attack behavior information and the second game character information, and generating the avoidance control information corresponding to the second game character based on the avoidance control parameters and the gain parameters; when the game character behavior prediction result is the avoidance behavior information, determining the attack control parameters and corresponding gain parameters corresponding to the second game character based on the avoidance behavior information and the second game character information, and generating the attack control information corresponding to the second game character based on the attack control parameters and the gain parameters, wherein the avoidance control parameters include avoidance game skills, avoidance position information and avoidance motion information, the attack control parameters include attack game skills, attack position information and attack motion information, and the gain parameters include gain behavior types and gain behavior parameters.

[0066] The embodiment of the present application provides a game character control optimization method. Compared with determining the game control behavior of the second game character through a decision tree method, the embodiment of the present application obtains first game character information of the first game character and second game character information corresponding to the second game character, wherein the first game character is controlled by the user and the second game character is controlled by the human-computer interaction system; based on the first game character information and the second game character information, a behavior decision analysis is performed on the second game character to obtain control action information corresponding to the second game character; based on the control action information, game control signal data is generated; based on the game control signal data, the second game character is controlled, thereby achieving matching the control behavior of the second game character according to the game character type of the user, avoiding the technical defect of low accuracy of human-computer interaction caused by the fixed and single control behavior determined by the decision tree method, and failing to provide effective feedback on the user's control behavior, thereby improving the accuracy of human-computer interaction.

[0067] Embodiment 3

[0068] The embodiment of the present application also provides a game character control optimization device, which is applied to a game character control optimization device, and the game character control optimization device includes:

[0069] An acquisition module, used to acquire first game character information of a first game character and second game character information corresponding to a second game character, wherein the first game character is controlled by a user and the second game character is controlled by the human-computer interaction system;

[0070] An analysis module, configured to perform a behavior decision analysis on the second game character based on the first game character information and the second game character information, and obtain control action information corresponding to the second game character;

[0071] A generating module, used for generating game control signal data according to the control action information;

[0072] The control module is used to control the second game character according to the game control signal data.

[0073] Optionally, the analysis module is further used for:

[0074] According to the first game character information, the second game character information and a preset game control effect prediction model, a control effect prediction is performed on the second game character to obtain a control effect prediction result, wherein the control effect prediction result includes each control effect and a control effect score corresponding to each control effect;

[0075] Selecting a target control action score greater than or equal to a preset control action score threshold from among the control action scores;

[0076] The control action information is generated according to the target control action corresponding to the target control action score.

[0077] Optionally, the analysis module is further used for:

[0078] Predicting the game character behavior of the first game character at the next time step based on the first game character information, the second game character information and a preset game character behavior prediction model to obtain a first game character behavior prediction result;

[0079] The control action information is generated according to the game character behavior prediction result and the second game character information.

[0080] Optionally, the analysis module is further used for:

[0081] constructing a game feature vector of the first game character according to the first game feature information in the first game character information and the second game feature information in the second game character information;

[0082] The game feature vector is mapped to the game character behavior of the first game character in the next time step through the preset game character behavior prediction model.

[0083] Optionally, the game character control optimization device is also used for:

[0084] Acquire a first character type corresponding to the first game character, first position information of the first game character, first movement information of the first game character, and first character state information corresponding to the first game character to obtain the first game character information;

[0085] The second character type corresponding to the second game character, the second position information of the second game character, the second movement information of the second game character, and the second character state information corresponding to the second game character are obtained to obtain the second game character information.

[0086] Optionally, the game character control optimization device is also used for:

[0087] Determining a first role type tag corresponding to the first game role based on the first role type, and determining a second role type tag corresponding to the second game role based on the second role type;

[0088] The first character type label, the first position information, the first motion information, the first character status information, the second character type label, the second position information, the second motion information and the second character status information are concatenated into the game feature vector.

[0089] Optionally, the game behavior prediction result includes attack behavior information and avoidance behavior information, the control action information includes avoidance control information and attack control information, and the generation module is further used to:

[0090] When the game character behavior prediction result is the attack behavior information, generating avoidance control information corresponding to the second game character according to the attack behavior information and the second game character information;

[0091] When the game character behavior prediction result is the avoidance behavior information, attack control information corresponding to the second game character is generated according to the avoidance behavior information and the second game character information.

[0092] The game character control optimization device provided by the present application adopts the game character control optimization method in the above embodiment to solve the technical problem of low accuracy of human-computer interaction. Compared with the prior art, the beneficial effects of the game character control optimization device provided by the embodiment of the present application are the same as the beneficial effects of the game character control optimization method provided by the above embodiment, and the other technical features in the game character control optimization device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0093] Embodiment 4

[0094] An embodiment of the present application provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the game character control optimization method in the above-mentioned embodiment.

[0095] Reference below Figure 3 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present disclosure. The electronic device in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0096] like Figure 3 As shown, the electronic device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage device into a random access memory (RAM). In the RAM, various programs and data required for the operation of the electronic device are also stored. The processing device, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0097] Typically, the following systems can be connected to the I / O interface: input devices including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices including, for example, a magnetic tape, a hard disk, etc.; and communication devices. The communication device can allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows an electronic device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0098] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processing device, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0099] The electronic device provided by the present application adopts the game character control optimization method in the above embodiment to solve the technical problem of low accuracy of human-computer interaction. Compared with the prior art, the beneficial effects of the electronic device provided by the embodiment of the present application are the same as the beneficial effects of the game character control optimization method provided by the above embodiment, and other technical features in the electronic device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0100] It should be understood that the various parts of the present disclosure can be implemented with hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0101] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0102] Embodiment 5

[0103] This embodiment provides a computer-readable storage medium having computer-readable program instructions stored thereon, and the computer-readable program instructions are used to execute the method of the game character control optimization method in the above embodiment.

[0104] The computer-readable storage medium provided in the embodiment of the present application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present embodiment, the computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, a system or a device or used in combination with it. The program code contained on the computer-readable storage medium can be transmitted with any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0105] The computer-readable storage medium may be included in the electronic device, or may exist independently without being installed in the electronic device.

[0106] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by an electronic device, the electronic device: obtains first game character information of a first game character and second game character information corresponding to a second game character, wherein the first game character is controlled by a user and the second game character is controlled by the human-computer interaction system; performs a behavior decision analysis on the second game character based on the first game character information and the second game character information to obtain control action information corresponding to the second game character; generates game control signal data based on the control action information; and controls the second game character based on the game control signal data.

[0107] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0108] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0109] The modules involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of the module does not limit the unit itself in some cases.

[0110] The computer-readable storage medium provided in the present application stores computer-readable program instructions for executing the above-mentioned game character control optimization method, which solves the technical problem of low accuracy of human-computer interaction.

[0111] Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the embodiment of the present application are the same as the beneficial effects of the game character control optimization method provided in the above-mentioned implementation, and will not be elaborated here.

[0112] Embodiment 6

[0113] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned game character control optimization method when executed by a processor.

[0114] The computer program product provided by the present application solves the technical problem of low accuracy of human-computer interaction. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the present application are the same as the beneficial effects of the game character control optimization method provided by the above embodiment, which will not be repeated here.

[0115] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent processing scope of the present application.

Claims

1. A method for optimizing game character control, characterized in that: Applied to a human-computer interaction system, the game character control optimization method includes: Acquire first game character information of a first game character and second game character information corresponding to a second game character, wherein the first game character is controlled by a user and the second game character is controlled by the human-computer interaction system, wherein the first game character is controlled by the user and the second game character is controlled by the human-computer interaction system; According to the first game character information and the second game character information, a behavior decision analysis is performed on the second game character to obtain control action information corresponding to the second game character; generating game control signal data according to the control action information; Controlling the second game character according to the game control signal data; Wherein, the step of performing a behavior decision analysis on the second game character based on the first game character information and the second game character information to obtain the control action information corresponding to the second game character further includes: Predicting the game character behavior of the first game character at the next time step based on the first game character information, the second game character information and a preset game character behavior prediction model to obtain a first game character behavior prediction result; generating the control action information according to the game character behavior prediction result and the second game character information; The game behavior prediction result includes attack behavior information and avoidance behavior information, the control effect information includes avoidance control information and attack control information, and the step of generating the control effect information based on the game character behavior prediction result and the second game character information includes: When the game character behavior prediction result is the attack behavior information, generating avoidance control information corresponding to the second game character according to the attack behavior information and the second game character information; When the game character behavior prediction result is the avoidance behavior information, attack control information corresponding to the second game character is generated according to the avoidance behavior information and the second game character information.

2. The game character control optimization method according to claim 1, characterized in that: The step of performing a behavior decision analysis on the second game character based on the first game character information and the second game character information to obtain control action information corresponding to the second game character comprises: According to the first game character information, the second game character information and a preset game control effect prediction model, a control effect prediction is performed on the second game character to obtain a control effect prediction result, wherein the control effect prediction result includes each control effect and a control effect score corresponding to each control effect; Selecting a target control action score greater than or equal to a preset control action score threshold from among the control action scores; The control action information is generated according to the target control action corresponding to the target control action score.

3. The game character control optimization method according to claim 1, characterized in that: The step of predicting the game character behavior of the first game character at the next time step based on the first game character information, the second game character information and a preset game character behavior prediction model to obtain the first game character behavior prediction result comprises: constructing a game feature vector of the first game character according to the first game feature information in the first game character information and the second game feature information in the second game character information; The game feature vector is mapped to the game character behavior of the first game character in the next time step through the preset game character behavior prediction model.

4. The game character control optimization method according to claim 1, characterized in that: Before the step of performing a behavior decision analysis on the second game character based on the first game character information and the second game character information to obtain the control action information corresponding to the second game character, the method further includes: Acquire a first character type corresponding to the first game character, first position information of the first game character, first movement information of the first game character, and first character state information corresponding to the first game character to obtain the first game character information; The second character type corresponding to the second game character, the second position information of the second game character, the second movement information of the second game character, and the second character state information corresponding to the second game character are obtained to obtain the second game character information.

5. The game character control optimization method according to claim 4, characterized in that: The step of constructing a game feature vector of the first game character according to the first game feature information in the first game character information and the second game feature information in the second game character information comprises: Determining a first role type tag corresponding to the first game role based on the first role type, and determining a second role type tag corresponding to the second game role based on the second role type; The first character type label, the first position information, the first motion information, the first character status information, the second character type label, the second position information, the second motion information and the second character status information are concatenated into the game feature vector.

6. A game character control optimization device, characterized in that: The game character control optimization device comprises: An acquisition module, used to acquire first game character information of a first game character and second game character information corresponding to a second game character, wherein the first game character is controlled by a user and the second game character is controlled by the human-computer interaction system; An analysis module, configured to perform a behavior decision analysis on the second game character based on the first game character information and the second game character information, and obtain control action information corresponding to the second game character; A generating module, used for generating game control signal data according to the control action information; A control module, used for controlling the second game character according to the game control signal data; Wherein, the analysis module is also used for: Predicting the game character behavior of the first game character at the next time step based on the first game character information, the second game character information and a preset game character behavior prediction model to obtain a first game character behavior prediction result; generating the control action information according to the game character behavior prediction result and the second game character information; The game behavior prediction result includes attack behavior information and avoidance behavior information, the control action information includes avoidance control information and attack control information, and the analysis module is further used for: When the game character behavior prediction result is the attack behavior information, generating avoidance control information corresponding to the second game character according to the attack behavior information and the second game character information; When the game character behavior prediction result is the avoidance behavior information, attack control information corresponding to the second game character is generated according to the avoidance behavior information and the second game character information.

7. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the game character control optimization method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program for implementing a method for optimizing control of a game character, and the program for implementing a method for optimizing control of a game character is executed by a processor to implement the steps of the method for optimizing control of a game character as described in any one of claims 1 to 5.

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