Many-to-many game task resource allocation method and device, equipment, medium and product
By adopting a two-way breadth search algorithm and priority sorting mechanism in game path search, the problem of game resources and path conflicts in high-speed aircraft confrontation simulation is solved, the resource allocation efficiency is improved and the task starvation is avoided.
Patent Information
- Application Number
- CN202411686322.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-25
- Publication Date
- 2025-03-14
AI Technical Summary
In the process of high-speed aircraft confrontation simulation game, as the complexity of the game tasks increases, the possibility of conflict between game resources and paths continues to increase, resulting in inefficiency of existing game path search algorithms.
A two-way breadth search algorithm is used to match game resources for each game task in the game sequence, and the game sequence is updated to avoid hunger based on the priority and starvation time flag of the game task.
It improves the efficiency of resource allocation of game tasks, ensures that game tasks with high priority can obtain resources first, and reduces the risk of low priority tasks starving to death due to long waiting time.
Smart Images
Figure CN119621315A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of game task resource allocation, and in particular to a many-to-many game task resource allocation method, device, equipment, medium and product. Background Art
[0002] In the high-speed aircraft confrontation simulation game process, game path search refers to finding the optimal game path from several game resource ports and game task (game object) port pairs in the game resource matching matrix in the cascade matrix association commonly used in the current game system. In actual game tasks, there are usually many accessible paths in the association matrix, and as the game tasks become more and more complex, the possibility of conflicts between game resources and paths is also increasing. Therefore, it is necessary to design an efficient and feasible game path search algorithm. Summary of the invention
[0003] The purpose of this application is to provide a many-to-many game task resource allocation method, device, equipment, medium and product, which can improve the efficiency of game task resource allocation.
[0004] To achieve the above objectives, this application provides the following solutions:
[0005] In a first aspect, the present application provides a method for allocating many-to-many game task resources, comprising:
[0006] Establishing an association matrix according to the game task set and the game resource set; the association matrix is used to describe the path relationship between each game task in the game task set and each game resource in the game resource set;
[0007] Determining a game sequence according to the priority of each game task in the game task set;
[0008] A bidirectional breadth search algorithm is used to match game resources for each game task in a game sequence. During the search process of the bidirectional breadth search algorithm, it is determined whether there is a hungry game task according to the hunger time flag of each game task. If so, the game sequence is updated.
[0009] Optionally, each element value in the association matrix represents a path relationship between a game task port of a game task and a game resource port of a game resource, and if there is a reachable path between the game task port of the game task and the game resource port of the game resource, the element value is the path length of the reachable path, otherwise the element value is 0;
[0010] The condition for the existence of a reachable path includes that the interface type of the game task port matches the interface type of the game resource port.
[0011] Optionally, a bidirectional breadth search algorithm is used to match game resources for each game task in the game sequence. During the search process of the bidirectional breadth search algorithm, it is determined whether there is a hungry game task according to the starvation time flag of each game task. If so, the game sequence is updated, which specifically includes:
[0012] Determine whether there is a hungry game task in the current game sequence, and if so, update the current game sequence;
[0013] Take the starting game task and the ending game task of the current game sequence, and determine the starting port pair of the starting game task and the ending port pair of the ending game task; both the starting port pair and the ending port pair include the game task port and the corresponding game resource port;
[0014] Find the adjacent elements of the game task port and the adjacent elements of the game resource port in the starting port pair to obtain a first search port pair set; and simultaneously find the adjacent elements of the game task port and the adjacent elements of the game resource port in the end port pair to obtain a second search port pair set;
[0015] Determine whether there is a port pair of a reachable path in the first search port pair set according to the association matrix, and if so, store the searched port pair in the path set and update the game task in the searched port pair as the starting game task;
[0016] Determine whether there is a port pair of a reachable path in the second search port pair set according to the association matrix, and if so, store the searched port pair in the path set and update the game task in the searched port pair to the end point game task;
[0017] Determine whether the starting game task is the same as the ending game task. If they are the same, the search ends and the current path set is output; otherwise, return to the step of determining whether there is a hungry game task in the current game sequence. If so, update the current game sequence.
[0018] Optionally, it is determined whether there is a hungry game task in the current game sequence, and if so, the current game sequence is updated, specifically including:
[0019] Determine whether there is a hungry game task in the current game sequence. If so, use the bubbling method to put the hungry game task at the front of the current game sequence.
[0020] Optionally, otherwise, returning to determine whether there is a hungry game task in the current game sequence, and if so, updating the current game sequence, specifically includes:
[0021] If there is no port pair with a reachable path in the first search port pair set, or there is no port pair with a reachable path in the second search port pair set, determine whether the search time has timed out. If so, determine that the search has failed. If not, return to determine whether there is a hungry game task in the current game sequence. If so, update the step of the current game sequence.
[0022] Optionally, the game task in the game task set is a high-speed aircraft confrontation simulation.
[0023] In a second aspect, the present application provides a many-to-many game task resource allocation device, comprising:
[0024] An association matrix establishment module is used to establish an association matrix according to a game task set and a game resource set; the association matrix is used to describe the path relationship between each game task in the game task set and each game resource in the game resource set;
[0025] A game sequence determination module, used to determine the game sequence according to the priority of each game task in the game task set;
[0026] The task resource matching module is used to match game resources for each game task in the game sequence using a bidirectional breadth search algorithm. During the search process of the bidirectional breadth search algorithm, it is determined whether there is a hungry game task based on the starvation time flag of each game task. If so, the game sequence is updated.
[0027] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any one of the many-to-many game task resource allocation methods described above.
[0028] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the many-to-many game task resource allocation methods described above.
[0029] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any one of the many-to-many game task resource allocation methods described above.
[0030] According to the specific embodiments provided in this application, this application discloses the following technical effects:
[0031] The present application provides a many-to-many game task resource allocation method, device, equipment, medium and product, which improves the resource allocation speed through two-way breadth search, and sets a starvation time flag by combining priorities to ensure that game tasks with higher priorities are allocated game resources first. At the same time, it can reduce the problem of game tasks with lower priorities starving to death due to long waiting time, thereby improving the efficiency of game task resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS
[0032] 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 will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0033] Figure 1 A flowchart of a method for allocating resources for many-to-many game tasks provided in one embodiment of the present application;
[0034] Figure 2 A complete flowchart of a method for allocating resources for many-to-many game tasks provided in one embodiment of the present application;
[0035] Figure 3 A schematic diagram of functional modules of a multi-to-multi game task resource allocation device provided in one embodiment of the present application;
[0036] Figure 4 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION
[0037] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions 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 are within the scope of protection of this application.
[0038] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.
[0039] This application provides a method for allocating many-to-many game task resources. Figure 1 As shown, a many-to-many game task resource allocation method includes:
[0040] Step 101: Establish an association matrix according to a game task set and a game resource set; the association matrix is used to describe the path relationship between each game task in the game task set and each game resource in the game resource set.
[0041] Step 102: Determine a game sequence according to the priority of each game task in the game task set.
[0042] Step 103: Use a bidirectional breadth search algorithm to match game resources for each game task in the game sequence. During the search process of the bidirectional breadth search algorithm, determine whether there is a hungry game task based on the starvation time flag of each game task. If so, update the game sequence.
[0043] This application improves the resource allocation speed through bidirectional breadth search, and sets the starvation time flag by combining priorities to ensure that game tasks with higher priorities are allocated game resources first. At the same time, it can reduce the problem of game tasks with lower priorities starving to death due to long waiting time, thereby improving the efficiency of game task resource allocation.
[0044] The problem of resource allocation for game tasks in this application is a game path search problem. The goal of game path search is to achieve the optimal game path allocation for a number of game resource ports and game task ports. Therefore, when establishing a mathematical model describing the game path, i.e., the association matrix, it is necessary to consider the availability, conflict constraints, accessibility, and optimality of the game path.
[0045] (1) Availability: The premise of game path search is that the interface types of the game resource port and the game task port match and can realize the corresponding physical connection and data exchange. The resource-task pair is determined by the resource matching process. Before executing the game path search process, it is necessary to first check whether the connection relationship between the corresponding game resource port and the game task port is available.
[0046] For the interface type matching of the gaming resource port and the gaming task port, for example, the function of the gaming resource port is to measure voltage, and the requirement of the gaming task port is also to measure voltage, then the interface types of the two match.
[0047] (2) Conflict constraints: As game tasks become increasingly complex, game resources are repeatedly called during the entire game task execution process. It is necessary not only to check whether the game resources are occupied, but also to check whether the game resource ports are available. There are certain conflicts and constraints between different game tasks during the game path search process, which is more obvious in the dynamic scheduling system. Therefore, on the premise of confirming that the resource-task port pair is available, it is necessary to further determine whether there is a conflict constraint, sort them according to priority, and remove the constraint relationship.
[0048] (3) Accessibility: After confirming that the game resource port and the game task port can be physically connected and eliminating the corresponding conflict constraints, it is necessary to further consider the accessibility of the port pair. Theoretically, when a single game task is executed and the performance of the association matrix is intact, there must be a reachable link between the port pairs. However, in actual game tasks, due to the multiple module reuse of the association matrix and its actual health status, a reachability check is required.
[0049] (4) Optimality: In the process of searching for game paths, the shortest game path is generally selected under the premise of meeting the game requirements. The length of the path is related to the control action and cumulative reliability of the association matrix. The shorter the game path, the simpler the control action and the higher the cumulative reliability. Therefore, after determining the availability between the game resource port and the game task port and resolving the constraint conflict, when performing the path search process, it is necessary to consider the optimal performance of the path.
[0050] Through the above analysis, the graph theory method is used to establish the association matrix, and the ports in the association matrix are defined as the vertices V in the graph, and are distinguished by subscripts V|=n; if there is availability and reachability between vertex i and vertex j in the association circuit, then the edge E is recorded i,j = m, then m is the path length between vertex i and vertex j. If m = 0, the vertices are not connected. If m ≠ 0, they are connected, and the path length is m, which is used as the basis for optimality judgment. It should be noted here that the value of m is generally not unique and defaults to its minimum value.
[0051] Each element value in the association matrix represents the path relationship between a game task port of a game task and a game resource port of a game resource. If there is a reachable path between the game task port of the game task and the game resource port of the game resource, the element value is the path length of the reachable path; otherwise, the element value is 0.
[0052] In an exemplary embodiment, the path length of the reachable path is 1 by default, and the condition for the existence of the reachable path includes that the interface type of the game task port matches the interface type of the game resource port.
[0053] In an exemplary embodiment, a matrix of the association of three task capabilities corresponding to a certain resource is described as follows:
[0054]
[0055] Among them, G is the matrix description of association (association matrix), defining resource node as 1, task vertices as 2, 3 and 4 respectively. The relationship between accessibility and optimality can be clearly obtained from the matrix description. By analyzing various associations and association matrices in the game system, its matrix description relationship can be obtained, which is also the basis and prerequisite for the execution of the game path search algorithm. The key to solving the conflict constraint relationship lies in solving the matrix description of the game task.
[0056] The implementation process of the bidirectional breadth search algorithm is: start breadth-first search from the root node and the target node at the same time, and stop searching when they meet at a certain node in the middle. The bidirectional breadth search algorithm solves the natural contradiction between depth and breadth in the search algorithm to a certain extent, effectively improves the search efficiency, and is a good search method.
[0057] This application adds a collaborative sorting method based on the two-way breadth search algorithm. The main implementation idea is to increase the priority sorting of game tasks. On the basis of the two-way breadth search, the game paths are allocated to the top-ranked game tasks first, and a starvation time flag is added to prevent certain types of tasks from "starving to death" due to long waiting times due to low priority. By setting the game task priority and the starvation time flag, the collaborative sorting of game tasks is achieved, and the optimization search task of the game path is completed by combining the two-way breadth search method.
[0058] Wherein, step 103 specifically includes:
[0059] Determine whether there is a hungry game task in the current game sequence, and if so, update the current game sequence.
[0060] Take the starting game task and the ending game task of the current game sequence, and determine the starting port pair of the starting game task and the ending port pair of the ending game task; both the starting port pair and the ending port pair include the game task port and the corresponding game resource port.
[0061] Find the adjacent elements of the game task port and the adjacent elements of the game resource port in the starting port pair to obtain a first search port pair set; at the same time, find the adjacent elements of the game task port and the adjacent elements of the game resource port in the end port pair to obtain a second search port pair set.
[0062] It is determined whether there is a port pair of a reachable path in the first search port pair set according to the association matrix. If so, the searched port pair is stored in the path set and the game task in the searched port pair is updated as the starting game task.
[0063] It is determined whether there is a port pair of a reachable path in the second search port pair set according to the association matrix. If so, the searched port pair is stored in the path set and the game task in the searched port pair is updated to the end game task.
[0064] Determine whether the starting game task is the same as the ending game task. If they are the same, the search ends and the current path set is output; otherwise, return to the step of determining whether there is a hungry game task in the current game sequence. If so, update the current game sequence.
[0065] Otherwise, the process returns to determine whether there is a hungry game task in the current game sequence, and if so, the step of updating the current game sequence specifically includes: if there is no port pair with a reachable path in the first search port pair set, or there is no port pair with a reachable path in the second search port pair set, then determining whether the search time has timed out, if so, determining that the search has failed, and if not, returning to determine whether there is a hungry game task in the current game sequence, and if so, updating the step of updating the current game sequence.
[0066] Among them, it is judged whether there is a hungry game task in the current game sequence, and if so, the current game sequence is updated, which specifically includes: judging whether there is a hungry game task in the current game sequence, and if so, the bubbling method is used to put the hungry game task at the front of the current game sequence.
[0067] The path set is used to store the game resources allocated to each game task.
[0068] The game tasks in the game task set are high-speed aircraft confrontation simulations, such as simulation of a new type of high-speed aircraft confrontation process based on simulation software.
[0069] The game task set is a set of many-to-many game tasks. In the application scenario of the high-speed aircraft confrontation simulation of this application, the two parties in the game are defined as the red party and the blue party. The game task set is the game task set of the red party, and the game resource set is the game resource set of the red party. The many-to-many game task resource allocation process is the process of allocating the game resource set to each game task. Many-to-many game tasks refer to the existence of multiple game objects on both sides.
[0070] In an exemplary embodiment, Figure 2 As shown, a more complete method for allocating resources of many-to-many game tasks includes:
[0071] S1: The matrix description of the initial association model is established by the game task set and the game resource set, where E i,j =m, m takes the minimum value under ideal conditions.
[0072] S2: Update the game sequence according to the priority, let s i=n, t i =T, where n is the sequence number of the signal in the game sequence, and t is the waiting time of the signal.
[0073] S3: Determine whether t exists i ≥T max If yes, use the bubble method to make s1=s i 、s j+1 =s j .
[0074] S4: According to the current game sequence execution status, take out the current game resource-task port pair
[0075] S5: Set the two starting points of the bidirectional breadth search to and to start your search.
[0076] S6: Find The corresponding adjacent elements of and The corresponding adjacent elements of .
[0077] S7: During the search process, update the and .
[0078] S8: For each direction in the bidirectional search, determine whether there is E i,j =1, if it exists, randomly select one path in its path, store it in the path set V(t), and go to step S3; otherwise, go to step S9.
[0079] S9: Determine whether the total search time exceeds the response time. If so, go to step S10; otherwise, return to step S2.
[0080] S10: No resource path is available, and the path search failed.
[0081] S11: Enter the waiting loop and go to step S1 when there is a new task.
[0082] The design idea of the resource allocation method for many-to-many game tasks in this application belongs to the greedy algorithm, which always solves the optimal value of the current sequence. Since the balanced load of each game resource has been considered in the resource matching process, there is no need to consider the global optimality here. In addition, by combining the two-way breadth search algorithm, the coordination of the search speed and accuracy of the method is guaranteed, and the priority sorting of game tasks and the starvation time flag are added, which is adapted to the application characteristics of many-to-many game tasks, realizes the design idea of "cooperative sorting", and also lays the foundation for the subsequent upgrade and development of software functions to adapt to more complex systems.
[0083] Based on the same inventive concept, the embodiment of the present application also provides a multi-to-multi game task resource allocation device for implementing the multi-to-multi game task resource allocation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the one or more game task resource allocation device embodiments provided below can refer to the limitations of the multi-to-multi game task resource allocation method above, and will not be repeated here.
[0084] In an exemplary embodiment, Figure 3 As shown, a many-to-many game task resource allocation device is provided, comprising:
[0085] The association matrix establishment module 201 is used to establish an association matrix according to the game task set and the game resource set; the association matrix is used to describe the path relationship between each game task in the game task set and each game resource in the game resource set.
[0086] The game sequence determination module 202 is used to determine the game sequence according to the priority of each game task in the game task set.
[0087] The task resource matching module 203 is used to match game resources for each game task in the game sequence using a bidirectional breadth search algorithm. During the search process of the bidirectional breadth search algorithm, it is determined whether there is a hungry game task based on the starvation time flag of each game task. If so, the game sequence is updated.
[0088] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store multi-to-multi game task resource allocation data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a multi-to-multi game task resource allocation method is implemented.
[0089] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.
[0090] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.
[0091] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.
[0092] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.
[0093] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).
[0094] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a data processing logic of a programmable logic device, etc., but is not limited thereto.
[0095] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0096] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.
Claims
1. A method for allocating many-to-many game task resources, characterized in that: The many-to-many game task resource allocation method comprises: Establishing an association matrix according to the game task set and the game resource set; the association matrix is used to describe the path relationship between each game task in the game task set and each game resource in the game resource set; Determining a game sequence according to the priority of each game task in the game task set; A bidirectional breadth search algorithm is used to match game resources for each game task in a game sequence. During the search process of the bidirectional breadth search algorithm, it is determined whether there is a hungry game task according to the hunger time flag of each game task. If so, the game sequence is updated.
2. The method for allocating many-to-many game task resources according to claim 1, characterized in that: Each element value in the association matrix represents the path relationship between a game task port of a game task and a game resource port of a game resource. If there is a reachable path between the game task port of the game task and the game resource port of the game resource, the element value is the path length of the reachable path, otherwise the element value is 0; The condition for the existence of a reachable path includes that the interface type of the game task port matches the interface type of the game resource port.
3. The method for allocating many-to-many game task resources according to claim 2, characterized in that: A two-way breadth search algorithm is used to match game resources for each game task in the game sequence. During the search process of the two-way breadth search algorithm, it is determined whether there is a hungry game task according to the starvation time flag of each game task. If so, the game sequence is updated, which specifically includes: Determine whether there is a hungry game task in the current game sequence, and if so, update the current game sequence; Take the starting game task and the ending game task of the current game sequence, and determine the starting port pair of the starting game task and the ending port pair of the ending game task; both the starting port pair and the ending port pair include the game task port and the corresponding game resource port; Find the adjacent elements of the game task port and the adjacent elements of the game resource port in the starting port pair to obtain a first search port pair set; and simultaneously find the adjacent elements of the game task port and the adjacent elements of the game resource port in the end port pair to obtain a second search port pair set; Determine whether there is a port pair of a reachable path in the first search port pair set according to the association matrix, and if so, store the searched port pair in the path set and update the game task in the searched port pair as the starting point game task; Determine whether there is a port pair of a reachable path in the second search port pair set according to the association matrix, and if so, store the searched port pair in the path set and update the game task in the searched port pair to the end point game task; Determine whether the starting game task is the same as the ending game task. If they are the same, the search ends and the current path set is output; otherwise, return to the step of determining whether there is a hungry game task in the current game sequence. If so, update the current game sequence.
4. The method for allocating many-to-many game task resources according to claim 2, characterized in that: Determine whether there is a hungry game task in the current game sequence. If so, update the current game sequence, including: Determine whether there is a hungry game task in the current game sequence. If so, use the bubbling method to put the hungry game task at the front of the current game sequence.
5. The method for allocating many-to-many game task resources according to claim 3, characterized in that: Otherwise, return to determine whether there is a hungry game task in the current game sequence. If so, update the current game sequence, including: If there is no port pair with a reachable path in the first search port pair set, or there is no port pair with a reachable path in the second search port pair set, determine whether the search time has timed out. If so, determine that the search has failed. If not, return to determine whether there is a hungry game task in the current game sequence. If so, update the step of the current game sequence.
6. The method for allocating many-to-many game task resources according to claim 1, characterized in that: The game task in the game task set is high-speed aircraft confrontation simulation.
7. A multi-to-multi game task resource allocation device, characterized in that: The many-to-many game task resource allocation device comprises: An association matrix establishment module is used to establish an association matrix according to a game task set and a game resource set; the association matrix is used to describe the path relationship between each game task in the game task set and each game resource in the game resource set; A game sequence determination module, used to determine the game sequence according to the priority of each game task in the game task set; The task resource matching module is used to match game resources for each game task in the game sequence using a bidirectional breadth search algorithm. During the search process of the bidirectional breadth search algorithm, it is determined whether there is a hungry game task based on the starvation time flag of each game task. If so, the game sequence is updated.
8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the many-to-many game task resource allocation method described in any one of claims 1-6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for allocating resources for many-to-many game tasks described in any one of claims 1 to 6 is implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for allocating resources for many-to-many game tasks described in any one of claims 1 to 6 is implemented.