CN118121936A - Data processing method and system for game real-time interaction - Google Patents

Data processing method and system for game real-time interaction Download PDF

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CN118121936A
CN118121936A CN202410562281.3A CN202410562281A CN118121936A CN 118121936 A CN118121936 A CN 118121936A CN 202410562281 A CN202410562281 A CN 202410562281A CN 118121936 A CN118121936 A CN 118121936A
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game
player
historical
behavior
data
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CN118121936B (en
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林镇松
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Guiyang Yiyi Technology Co ltd
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Guiyang Yiyi Technology Co ltd
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Abstract

The invention discloses a data processing method and a system for real-time interaction of games, and relates to the technical field of data processing, wherein the method comprises the steps of collecting historical game behavior data of all players entering the same game through a game server; preprocessing the historical game behavior data to obtain preprocessed historical game behavior data; analyzing player gaming behavior threat values and player gaming behavior capability values based on the historical gaming behavior data; obtaining game level of a player and game difficulty; the game map is used for carrying out birth point distribution on all players entering the same game. The invention can increase the interest of the game when the player plays the game, and avoid the two parties losing the most important experience of 'average force and enemy' in the game because of the large difference in the aspects of the game grade, the game style, the capability and the like of the allocated player when the player interacts with the players at the similar positions.

Description

Data processing method and system for game real-time interaction
Technical Field
The invention relates to the technical field of data processing, in particular to a data processing method and system for game real-time interaction.
Background
With the continuous development of the game market, more and more excellent game works are sequentially marketed and widely loved by a plurality of game lovers; while the experience of a game is critical to the player, in a competitive game, the player group plays into the game and is randomly assigned to the birth points in different areas of the game map; however, this random allocation has a problem in that if the game ability of another player allocated in the vicinity of the player is too strong, the player is eliminated too long, and thus the game experience of the player is affected, and the game's level of sophistication is also affected; therefore, how to reasonably distribute the birth points, and avoid the players from losing the experience of the games too early, is a technical problem which needs attention at present.
For example, chinese patent publication No. CN202620680U discloses a MEMS-based motion sensing game handle, which includes a micro sensor device, a data processing device, and a wireless communication device; the micro sensor device comprises a triaxial micro accelerometer which is arranged at the foot part of the human body and is used for acquiring two-dimensional direction information, a triaxial gyroscope which is arranged at the head part of the human body and is used for acquiring visual angle information, and a triaxial micro accelerometer which is arranged at the hand part of the human body and is used for acquiring action information; the output ends of the triaxial micro accelerometer arranged on the foot, the triaxial micro accelerometer arranged on the hand and the triaxial gyroscope are connected with the input end of the upper computer through the data processing device and the wireless communication device in sequence. The intelligent game device can improve the interestingness of a game and the happy feeling of a player, and can acquire the motion information of the limbs in real time through the miniature sensor devices arranged on each part of the limbs, so that synchronous interaction between the game player and a game role is realized, and the player can obtain ideal game experience and has a good body-building effect.
The patent with publication number CN110308787A discloses an AR interactive system and method combining multidimensional interactive recognition and chess and card games, wherein the AR interactive system comprises a server, a host, a display unit group, human body 3D bone data acquisition and a face recognition data acquisition group, wherein the host is electrically and bidirectionally connected with the server, the host is electrically and output connected with the display unit group, and the host is electrically and input connected with the human body bone data acquisition group. The human body skeleton data acquisition group is used for acquiring the body state of a player and generating a 3D skeleton model of the player, and meanwhile, the human body skeleton data acquisition group is used for acquiring actions of selecting chess and card elements by the player, and virtual chess and card elements are selected in a virtual scene by the 3D skeleton model of the player through data processing, so that the problems that the interactivity and game immersion feeling of the player are poor due to the fact that the existing chess and card element games mostly adopt mice and keyboards to operate are avoided.
The problems presented in the background art exist in the above patents: in the prior art, when a player performs real-time interaction of a game, and does not perform birth point distribution for the player just entering the game, the player is distributed to a player with a potential enemy in an adjacent area, so that the player is eliminated too early, and the experience of the game is lost; in order to solve the problems, the invention provides a data processing method and a data processing system for game real-time interaction.
Disclosure of Invention
Aiming at the defects of the prior art, the main purpose of the invention is to provide a data processing method and a system for real-time interaction of games, which can effectively solve the problems in the background art. The specific technical scheme of the invention is as follows:
the data processing method for the real-time interaction of the game comprises the following specific steps:
S1, collecting historical game behavior data of all players entering the same game through a game server;
S2, preprocessing the historical game behavior data to obtain preprocessed historical game behavior data;
S3, substituting the historical game behavior data into a game behavior threat value calculation strategy and a game behavior capacity value calculation strategy of the player to calculate a game behavior threat value and a game behavior capacity value of the player respectively;
S4, obtaining game difficulty and game grades of players;
S5, substituting the game action threat value of the player, the game action capability value of the player, the game difficulty and the game grade of the player into a game matching score calculation strategy of the player to calculate the game matching score of the player, and establishing a birth point distribution sequence for storing all players entering the same game according to the game matching score ascending sequence of the player, and performing birth point distribution on the players in the birth point distribution sequence in a game map through a distance formula.
Specifically, the historical game behavior data includes: historical mouse input data, historical keyboard input data and historical game data; the historical mouse input data comprises the number of mouse clicks of a player in each game, the success rate of clicking on a target object in the game and the average value of time intervals between all adjacent two mouse clicks in each game; the historical keyboard input data comprises the number of keys required by a player in each game, the number of times each key is pressed and the average time interval of each key being continuously pressed; the historical game data includes the completion time of each game of the player, the game difficulty of each game, the number of games that earn winnings, the number of games that the player exits halfway, the map area of each game, the length of the player's movement path in each game, and the average movement speed.
Specifically, the preprocessing in S2 includes: deleting the missing value and the repeated value in the data, and carrying out normalization processing on the deleted data.
Specifically, the calculating strategy of the threat value of the game behavior of the player in S3 includes:
s31, before the player plays the game, extracting historical mouse input data and historical keyboard input data of n times of games of the player in history and the number of times of games of the player in the historical game data to exit halfway;
S32, substituting the historical mouse input data and the historical keyboard input data of the n-time games and the number of times of midway exiting the game of the player into a game behavior threat value calculation formula of the player to calculate a game behavior threat value of the player
S33, the player game behavior threat value calculation formula is as followsWhere m is the number of keys a player needs in each game,/>For the number of mouse clicks of the player in the ith game,/>For the success rate of the player clicking on the target object in the game in the ith game, and the number of games that A is the player to exit halfway,/>For the number of times a player has been pressed for the jth key position in the ith game,/>For the average time interval in which the jth key position is continuously pressed in the ith game by the player, i is any one of 1 to n, j is any one of 1 to m.
Specifically, the player game behavior ability value calculation strategy in S3 includes:
S34, before the player plays the game, extracting historical keyboard input data and historical game data of n times of games of the player historically;
S35, substituting the historical keyboard input data of the n games and the historical game data into a player game behavior capability value calculation formula to calculate the player game behavior capability value
S36, the player game behavior ability value calculation formula is as followsWherein S is the area of the game map of the field, and m is the number of keys required by the player in each game,/>Game difficulty for the ith game,/>For player movement path length in the ith game,/>For average moving speed of player in ith game,/>Completion time for the ith game of player,/>For the number of times a player has been pressed for the jth key position in the ith game,/>Average time interval for a player to be continuously pressed for a jth key position in an ith game,/>For the i-th game map area, num is the number of winning games, i is any one of 1 to n, j is any one of 1 to m.
Specifically, the S4 specifically includes: the game level of the player, the game level of the player's own game, and the game level of the player are obtained.
Specifically, the S5 specifically includes:
S51, setting Q players in the game field, and obtaining the game level minimum value of the players in the Q players Game level maximum value of player/>; Obtaining minimum value/>, of threat values of game behaviors of players in Q playersAnd player game threat value maximum/>And player game performance capability value minimum/>And player game performance capability value maximum/>; Substituting the game difficulty of the game played by the player, the game level of the player, the game behavior threat value of the player and the game behavior capability value of the player into a game matching score calculation strategy to calculate the game matching score of each player;
S52, the local game matching score calculation strategy comprises the following steps: obtaining maximum game difficulty in n-time game of the qth player in history Computing a game match score for the q-th playerWhereinThe game difficulty influence coefficient, the player game level influence coefficient, the player game behavior threat value influence coefficient and the player game behavior capacity value influence coefficient are respectively; d is the game difficulty of the game of the field,/>Game level for the q-th player,/>Player gaming behavior threat value for the qth player,/>Player gaming behavior capability values for the qth player.
Specifically, the step S5 specifically further includes:
S53, uniformly dividing the game map into Q areas, acquiring game matching scores of Q players in the game, arranging in ascending order, and storing the players corresponding to the game matching scores after the ascending order into a birth point distribution sequence; the first element in the birth point distribution sequence is a player with the minimum matching score of the game, and the Q element is a player with the maximum matching score of the game; let q=1, allocate the player corresponding to the first element in the birth point allocation sequence to the center point of any area on the game map;
S54, calculating the distance between the qth player and the center point of the adjacent area by using a distance formula, taking the center point of the adjacent area with the smallest distance as the next allocation position, letting q=q+1, and Q=Q-1, and allocating the player corresponding to the qth element in the birth point allocation sequence to the next allocation position;
s55, repeating S54 until q=q, and completing the birth point allocation of all players.
Specifically, the data processing system for real-time game interaction is realized based on the data processing method for real-time game interaction, and the system comprises the following modules:
The data acquisition module is used for acquiring historical game behavior data of all players entering the same game through the game server, and acquiring game difficulty and game grades of the players; preprocessing the historical game behavior data to obtain preprocessed historical game behavior data;
The data analysis module is used for substituting the historical game behavior data into a game behavior threat value calculation strategy of the player and calculating the game behavior threat value and the game behavior capacity value of the player respectively;
The game matching score calculation module is used for calculating the game matching score of the player by substituting the game action threat value of the player, the game action capacity value of the player, the game difficulty and the game grade of the player into the game matching score calculation strategy, establishing a game point distribution sequence, and storing all players entering the same game according to the game matching score ascending sequence of the player, and carrying out game point distribution on the players in the game point distribution sequence in a game map through a distance formula;
and the control module is used for controlling the operation of each module.
Compared with the prior art, the invention has the following beneficial effects:
The invention collects the historical game behavior data of all players entering the same game through the game server; preprocessing the historical game behavior data to obtain preprocessed historical game behavior data; analyzing player gaming behavior threat values and player gaming behavior capability values based on the historical gaming behavior data; obtaining game level of a player and game difficulty; the game map is used for carrying out birth point distribution on all players entering the same game. The invention can increase the interest of the game when the player plays the game, and avoid the two parties losing the most important experience of 'average force and enemy' in the game because of the large difference in the aspects of the game grade, the game style, the capability and the like of the allocated player when the player interacts with the players at the similar positions.
Drawings
FIG. 1 is a workflow diagram of a data processing method for game real-time interaction of the present invention;
FIG. 2 is a block diagram of a data processing system for real-time game interaction according to the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Example 1
The embodiment provides a data processing method for real-time interaction of a game, and the specific scheme is that, as shown in fig. 1, the data processing method for real-time interaction of the game comprises the following specific steps:
S1, collecting historical game behavior data of all players entering the same game through a game server;
S2, preprocessing the historical game behavior data to obtain preprocessed historical game behavior data;
S3, substituting the historical game behavior data into a game behavior threat value calculation strategy and a game behavior capacity value calculation strategy of the player to calculate a game behavior threat value and a game behavior capacity value of the player respectively;
S4, obtaining game difficulty and game grades of players;
S5, substituting the game action threat value of the player, the game action capability value of the player, the game difficulty and the game grade of the player into a game matching score calculation strategy of the player to calculate the game matching score of the player, and establishing a birth point distribution sequence for storing all players entering the same game according to the game matching score ascending sequence of the player, and performing birth point distribution on the players in the birth point distribution sequence in a game map through a distance formula.
In this embodiment, the historical game behavior data includes: historical mouse input data, historical keyboard input data and historical game data; the historical mouse input data comprises the number of mouse clicks of a player in each game, the success rate of clicking on a target object in the game and the average value of time intervals between all adjacent two mouse clicks in each game; the historical keyboard input data comprises the number of keys required by a player in each game, the number of times each key is pressed and the average time interval of each key being continuously pressed; the historical game data includes the completion time of each game of the player, the game difficulty of each game, the number of games that earn winnings, the number of games that the player exits halfway, the map area of each game, the length of the player's movement path in each game, and the average movement speed.
In this embodiment, the preprocessing in S2 includes: deleting the missing value and the repeated value in the data, and carrying out normalization processing on the deleted data.
In this embodiment, the player game action threat value calculation strategy in S3 includes:
s31, before the player plays the game, extracting historical mouse input data and historical keyboard input data of n times of games of the player in history and the number of times of games of the player in the historical game data to exit halfway;
S32, substituting the historical mouse input data and the historical keyboard input data of the n-time games and the number of times of midway exiting the game of the player into a game behavior threat value calculation formula of the player to calculate a game behavior threat value of the player
S33, the player game behavior threat value calculation formula is as followsWhere m is the number of keys a player needs in each game,/>For the number of mouse clicks of the player in the ith game,/>For the success rate of the player clicking on the target object in the game in the ith game, and the number of games that A is the player to exit halfway,/>For the number of times a player has been pressed for the jth key position in the ith game,/>For the average time interval in which the jth key position is continuously pressed in the ith game by the player, i is any one of 1 to n, j is any one of 1 to m.
In this embodiment, the player game performance value calculation strategy in S3 includes:
S34, before the player plays the game, extracting historical keyboard input data and historical game data of n times of games of the player historically;
S35, substituting the historical keyboard input data of the n games and the historical game data into a player game behavior capability value calculation formula to calculate the player game behavior capability value
S36, the player game behavior ability value calculation formula is as followsWherein S is the area of the game map of the field, and m is the number of keys required by the player in each game,/>Game difficulty for the ith game,/>For player movement path length in the ith game,/>For average moving speed of player in ith game,/>Completion time for the ith game of player,/>For the number of times a player has been pressed for the jth key position in the ith game,/>Average time interval for a player to be continuously pressed for a jth key position in an ith game,/>For the i-th game map area, num is the number of winning games, i is any one of 1 to n, j is any one of 1 to m.
In this embodiment, the S4 specifically includes: the game level of the player, the game level of the player's own game, and the game level of the player are obtained.
In this embodiment, the S5 specifically includes:
S51, setting Q players in the game field, and obtaining the game level minimum value of the players in the Q players Game level maximum value of player/>; Obtaining minimum value/>, of threat values of game behaviors of players in Q playersAnd player game threat value maximum/>And player game performance capability value minimum/>And player game performance capability value maximum/>; Substituting the game difficulty of the game played by the player, the game level of the player, the game behavior threat value of the player and the game behavior capability value of the player into a game matching score calculation strategy to calculate the game matching score of each player;
S52, the local game matching score calculation strategy comprises the following steps: obtaining maximum game difficulty in n-time game of the qth player in history Computing a game match score for the q-th playerWhereinThe game difficulty influence coefficient, the player game grade influence coefficient, the player game behavior threat value influence coefficient and the player game behavior capacity value influence coefficient are respectively described, and the game difficulty influence coefficient, the player game grade influence coefficient, the player game behavior threat value influence coefficient and the player game behavior capacity value influence coefficient need to be determined by a person skilled in the art according to specific application requirements and actual conditions; d is the game difficulty of the game of the field,/>Game level for the q-th player,/>Player gaming behavior threat value for the qth player,/>Player gaming behavior capability values for the qth player.
In this embodiment, the step S5 specifically further includes:
S53, uniformly dividing the game map into Q areas, acquiring game matching scores of Q players in the game, arranging in ascending order, and storing the players corresponding to the game matching scores after the ascending order into a birth point distribution sequence; the first element in the birth point distribution sequence is a player with the minimum matching score of the game, and the Q element is a player with the maximum matching score of the game; let q=1, allocate the player corresponding to the first element in the birth point allocation sequence to the center point of any area on the game map;
S54, calculating the distance between the qth player and the center point of the adjacent area by using a distance formula, taking the center point of the adjacent area with the smallest distance as the next allocation position, letting q=q+1, and Q=Q-1, and allocating the player corresponding to the qth element in the birth point allocation sequence to the next allocation position;
s55, repeating S54 until q=q, and completing the birth point allocation of all players.
Example 2
The embodiment provides a data processing system for real-time game interaction, specifically, as shown in fig. 2, the data processing system for real-time game interaction is implemented based on the data processing method for real-time game interaction described in embodiment 1, and the system includes the following modules:
The data acquisition module is used for acquiring historical game behavior data of all players entering the same game through the game server, and acquiring game difficulty and game grades of the players; preprocessing the historical game behavior data to obtain preprocessed historical game behavior data;
The data analysis module is used for substituting the historical game behavior data into a game behavior threat value calculation strategy of the player and calculating the game behavior threat value and the game behavior capacity value of the player respectively;
The game matching score calculation module is used for calculating the game matching score of the player by substituting the game action threat value of the player, the game action capacity value of the player, the game difficulty and the game grade of the player into the game matching score calculation strategy, establishing a game point distribution sequence, and storing all players entering the same game according to the game matching score ascending sequence of the player, and carrying out game point distribution on the players in the game point distribution sequence in a game map through a distance formula;
and the control module is used for controlling the operation of each module.
The foregoing has shown and described the basic principles and main features of the present invention and the advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (9)

1. The data processing method for game real-time interaction is characterized by comprising the following steps of: the method comprises the following specific steps:
S1, collecting historical game behavior data of all players entering the same game through a game server;
S2, preprocessing the historical game behavior data to obtain preprocessed historical game behavior data;
S3, substituting the historical game behavior data into a game behavior threat value calculation strategy and a game behavior capacity value calculation strategy of the player to calculate a game behavior threat value and a game behavior capacity value of the player respectively;
S4, obtaining game difficulty and game grades of players;
S5, substituting the game action threat value of the player, the game action capability value of the player, the game difficulty and the game grade of the player into a game matching score calculation strategy of the player to calculate the game matching score of the player, and establishing a birth point distribution sequence for storing all players entering the same game according to the game matching score ascending sequence of the player, and performing birth point distribution on the players in the birth point distribution sequence in a game map through a distance formula.
2. The data processing method for game real-time interaction according to claim 1, wherein: the historical game behavior data includes: historical mouse input data, historical keyboard input data and historical game data; the historical mouse input data comprises the number of mouse clicks of a player in each game, the success rate of clicking on a target object in the game and the average value of time intervals between all adjacent two mouse clicks in each game; the historical keyboard input data comprises the number of keys required by a player in each game, the number of times each key is pressed and the average time interval of each key being continuously pressed; the historical game data includes the completion time of each game of the player, the game difficulty of each game, the number of games that earn winnings, the number of games that the player exits halfway, the map area of each game, the length of the player's movement path in each game, and the average movement speed.
3. The data processing method for game real-time interaction according to claim 2, wherein: the preprocessing in S2 includes: deleting the missing value and the repeated value in the data, and carrying out normalization processing on the deleted data.
4. A data processing method for real-time interaction of a game according to claim 3, wherein: the player game action threat value calculation strategy in the S3 comprises the following steps:
s31, before the player plays the game, extracting historical mouse input data and historical keyboard input data of n times of games of the player in history and the number of times of games of the player in the historical game data to exit halfway;
S32, substituting the historical mouse input data and the historical keyboard input data of the n-time games and the number of times of midway exiting the game of the player into a game behavior threat value calculation formula of the player to calculate a game behavior threat value of the player
S33, the player game behavior threat value calculation formula is as followsWhere m is the number of keys a player needs in each game,/>For the number of mouse clicks of the player in the ith game,/>For the success rate of the player clicking on the target object in the game in the ith game, and the number of games that A is the player to exit halfway,/>For the number of times a player has been pressed for the jth key position in the ith game,/>For the average time interval in which the jth key position is continuously pressed in the ith game by the player, i is any one of 1 to n, j is any one of 1 to m.
5. The data processing method for game real-time interaction according to claim 4, wherein: the player game behavior ability value calculation strategy in the S3 comprises the following steps:
S34, before the player plays the game, extracting historical keyboard input data and historical game data of n times of games of the player historically;
S35, substituting the historical keyboard input data of the n games and the historical game data into a player game behavior capability value calculation formula to calculate the player game behavior capability value
S36, the player game behavior ability value calculation formula is as followsWherein S is the area of the game map of the field, and m is the number of keys required by the player in each game,/>Game difficulty for the ith game,/>For player movement path length in the ith game,/>For average moving speed of player in ith game,/>Completion time for the ith game of player,/>For the number of times a player has been pressed for the jth key position in the ith game,/>Average time interval for a player to be continuously pressed for a jth key position in an ith game,/>For the i-th game map area, num is the number of winning games, i is any one of 1 to n, j is any one of 1 to m.
6. The data processing method for game real-time interaction according to claim 5, wherein: the step S4 specifically comprises the following steps: the game level of the player, the game level of the player's own game, and the game level of the player are obtained.
7. The data processing method for game real-time interaction according to claim 6, wherein: the step S5 specifically comprises the following steps:
S51, setting Q players in the game field, and obtaining the game level minimum value of the players in the Q players Game level maximum value of player/>; Obtaining minimum value/>, of threat values of game behaviors of players in Q playersAnd player game threat value maximum/>And player game performance capability value minimum/>And player game performance capability value maximum; Substituting the game difficulty of the game played by the player, the game level of the player, the game behavior threat value of the player and the game behavior capability value of the player into a game matching score calculation strategy to calculate the game matching score of each player;
S52, the local game matching score calculation strategy comprises the following steps: obtaining maximum game difficulty in n-time game of the qth player in history Computing a game match score for the q-th playerWhereinThe game difficulty influence coefficient, the player game level influence coefficient, the player game behavior threat value influence coefficient and the player game behavior capacity value influence coefficient are respectively; d is the game difficulty of the game of the field,/>Game level for the q-th player,/>Player gaming behavior threat value for the qth player,/>Player gaming behavior capability values for the qth player.
8. The data processing method for game real-time interaction according to claim 7, wherein: the step S5 specifically further comprises:
S53, uniformly dividing the game map into Q areas, acquiring game matching scores of Q players in the game, arranging in ascending order, and storing the players corresponding to the game matching scores after the ascending order into a birth point distribution sequence; the first element in the birth point distribution sequence is a player with the minimum matching score of the game, and the Q element is a player with the maximum matching score of the game; let q=1, allocate the player corresponding to the first element in the birth point allocation sequence to the center point of any area on the game map;
S54, calculating the distance between the qth player and the center point of the adjacent area by using a distance formula, taking the center point of the adjacent area with the smallest distance as the next allocation position, letting q=q+1, and Q=Q-1, and allocating the player corresponding to the qth element in the birth point allocation sequence to the next allocation position;
s55, repeating S54 until q=q, and completing the birth point allocation of all players.
9. Data processing system for game real-time interaction, realized on the basis of the data processing method for game real-time interaction according to any one of claims 1-8, characterized in that: the system comprises the following modules:
The data acquisition module is used for acquiring historical game behavior data of all players entering the same game through the game server, and acquiring game difficulty and game grades of the players; preprocessing the historical game behavior data to obtain preprocessed historical game behavior data;
The data analysis module is used for substituting the historical game behavior data into a game behavior threat value calculation strategy of the player and calculating the game behavior threat value and the game behavior capacity value of the player respectively;
The game matching score calculation module is used for calculating the game matching score of the player by substituting the game action threat value of the player, the game action capacity value of the player, the game difficulty and the game grade of the player into the game matching score calculation strategy, establishing a game point distribution sequence, and storing all players entering the same game according to the game matching score ascending sequence of the player, and carrying out game point distribution on the players in the game point distribution sequence in a game map through a distance formula;
and the control module is used for controlling the operation of each module.
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