Game task data personalized distribution method and terminal
By setting up multiple game-style task templates in large-scale online games and assigning tasks in a personalized manner based on player behavior data, the server pressure caused by player aggregation was resolved, and the game's smoothness and playability were improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- FUJIAN TQ DIGITAL
- Filing Date
- 2024-10-09
- Publication Date
- 2026-04-10
AI Technical Summary
In existing large-scale online games, the consistency of game tasks leads to player aggregation, increases the pressure on server data processing, and affects the smoothness and playability of the game.
Multiple task templates with different game styles are preset. By analyzing the behavior data of players' virtual characters, personalized game tasks are matched to avoid player aggregation. The task content is adjusted based on player feedback.
Improve game playability, reduce server data processing pressure, enhance game smoothness, and improve player interaction and task suitability.
Smart Images
Figure CN121819338A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data processing technology, and in particular to a method and terminal for personalized allocation of game task data. Background Technology
[0002] Nowadays, many large-scale online games require players to control a virtual character to move around the map and complete various game tasks. These tasks are generally assigned by NPCs. Because the process of game tasks is consistent, large numbers of players often gather at certain scenes or entrances to dungeons. The more players gather, the more NPC characters are matched, the more data the server has to process, and the more likely it is to cause frame drops or stuttering in the game. To alleviate the data processing pressure, the server may also guide players to queue to enter dungeons, further impacting the player experience.
[0003] Furthermore, repetitive game missions can easily bore players, making them unwilling to explore new characters or start a second playthrough, thus affecting the game's playability. Summary of the Invention
[0004] The technical problem to be solved by the present invention is to provide a method and terminal for personalized allocation of game task data, thereby reducing the data processing pressure on the server and improving the playability of the game.
[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:
[0006] A method for personalized allocation of game task data includes the following steps:
[0007] S1. Pre-set at least two task templates representing different game styles, wherein the task templates have corresponding game levels of the same game style in the game;
[0008] S2. During the game process, acquire the behavior data of the target virtual character controlled by the target player, analyze the game style of the target player based on the behavior data of the target virtual character, and match the corresponding task template based on the game style of the target player;
[0009] S3. Generate a game task based on the matched task template and the character information of the target virtual character, and assign the game task to the target player after receiving the task request from the target player.
[0010] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows:
[0011] A method for personalized allocation of game task data includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it performs the following steps:
[0012] S1. Pre-set at least two task templates representing different game styles, wherein the task templates have corresponding game levels of the same game style in the game;
[0013] S2. During the game process, acquire the behavior data of the target virtual character controlled by the target player, analyze the game style of the target player based on the behavior data of the target virtual character, and match the corresponding task template based on the game style of the target player;
[0014] S3. Generate a game task based on the matched task template and the character information of the target virtual character, and assign the game task to the target player after receiving the task request from the target player.
[0015] The beneficial effects of this invention are as follows: It provides a method and terminal for personalized allocation of game task data, which pre-sets multiple task templates with different game styles. Each task template has game levels corresponding to its game style. Before allocating game tasks, the game style of the target player is determined based on the behavior data of the target virtual character controlled by the target player, and then corresponding game tasks are assigned to them. Different game tasks are assigned to different players according to their preferences, which improves the playability of the game. At the same time, compared with all players having the same tasks, it can avoid the situation of a large number of players gathering in the game, reduce the data processing pressure on the server for the same game scene, and improve the smoothness of the game. Attached Figure Description
[0016] Figure 1 This is a schematic diagram illustrating the steps of a personalized game task data allocation method according to the present invention;
[0017] Figure 2 This is a system block diagram of a personalized game task data allocation terminal according to the present invention.
[0018] Label Explanation:
[0019] 1. A terminal for personalized allocation of game task data; 2. Memory; 3. Processor. Detailed Implementation
[0020] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.
[0021] Please refer to Figure 1 A method for personalized allocation of game task data includes the following steps:
[0022] S1. Pre-set at least two task templates representing different game styles, wherein the task templates have corresponding game levels of the same game style in the game;
[0023] S2. During the game process, acquire the behavior data of the target virtual character controlled by the target player, analyze the game style of the target player based on the behavior data of the target virtual character, and match the corresponding task template based on the game style of the target player;
[0024] S3. Generate a game task based on the matched task template and the character information of the target virtual character, and assign the game task to the target player after receiving the task request from the target player.
[0025] As can be seen from the above description, the beneficial effects of the present invention are as follows: multiple task templates with different game styles are pre-set, and each task template has game levels with a corresponding game style. Before assigning game tasks, the game style of the target player is determined based on the behavior data of the target virtual character controlled by the target player, and then corresponding game tasks are assigned to them. Different game tasks are assigned to different players according to their preferences, which improves the playability of the game. At the same time, compared with all players having the same tasks, it can avoid the situation of a large number of players gathering in the game, reduce the data processing pressure on the server for the same game scene, and improve the smoothness of the game.
[0026] Furthermore, the procedure before step S2 includes:
[0027] In the game activity area corresponding to the early stage of the game, set up at least two special interactive elements with different game styles;
[0028] The acquisition of behavioral data of the target virtual character controlled by the target player includes:
[0029] Acquire the target virtual character's movement trajectory and combat data within the game activity area, as well as the target virtual character's interaction data with all the special interactive elements.
[0030] As described above, special interactive elements with different game styles are set up in the game activity area. At the same time, the movement trajectory, combat data, and interaction data of the target virtual character in the game activity area are collected to comprehensively judge the player's game style and improve the accuracy of the judgment.
[0031] Furthermore, the procedure before step S3 includes:
[0032] Pre-set NPCs that correspond one-to-one with the task templates, and set dialogue and interaction rules on the NPCs that are the same as the game style of the corresponding task templates;
[0033] The system receives the target player's quest request through an NPC and assigns the game quest to the target player.
[0034] As can be seen from the above description, when a task in the game is received from an NPC, some dialogue and interaction rules for the NPC are set according to the game style of the task template used in the game, so that the target player has a better interactive experience and enhances the fun of the game.
[0035] Furthermore, it also includes:
[0036] S4. After the target player completes the current game task, determine whether the time difference between the current time and the time node when the target player's game style was previously determined is greater than the preset time. If so, repeat step S2.
[0037] As described above, as the game progresses, players' preferred game styles may change accordingly. Therefore, a time condition with a preset duration is set. After a certain game task is completed, the target player's behavior data is retrieved again to re-evaluate the target player's game style, so as to prepare for subsequent task allocation, dynamically adjust, and improve the player's game experience.
[0038] Furthermore, it also includes:
[0039] S5. Obtain and adjust the content of the next game task for the target player based on the feedback from the target player regarding the current game task.
[0040] As can be seen from the above description, in addition to generating game tasks based on the game style, adjustments should also be made based on player feedback. For example, if players feel that the difficulty of the current game task is too high, the difficulty of the task will be adjusted accordingly when generating the next game task to improve the suitability of the task to the player's level or needs.
[0041] Please refer to Figure 2 A personalized game task data allocation terminal 1 includes a memory 2, a processor 3, and a computer program stored on the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, it performs the following steps:
[0042] S1. Pre-set at least two task templates representing different game styles, wherein the task templates have corresponding game levels of the same game style in the game;
[0043] S2. During the game process, acquire the behavior data of the target virtual character controlled by the target player, analyze the game style of the target player based on the behavior data of the target virtual character, and match the corresponding task template based on the game style of the target player;
[0044] S3. Generate a game task based on the matched task template and the character information of the target virtual character, and assign the game task to the target player after receiving the task request from the target player.
[0045] As can be seen from the above description, the beneficial effects of the present invention are as follows: multiple task templates with different game styles are pre-set, and each task template has game levels with a corresponding game style. Before assigning game tasks, the game style of the target player is determined based on the behavior data of the target virtual character controlled by the target player, and then corresponding game tasks are assigned to them. Different game tasks are assigned to different players according to their preferences, which improves the playability of the game. At the same time, compared with all players having the same tasks, it can avoid the situation of a large number of players gathering in the game, reduce the data processing pressure on the server for the same game scene, and improve the smoothness of the game.
[0046] Furthermore, the procedure before step S2 includes:
[0047] In the game activity area corresponding to the early stage of the game, set up at least two special interactive elements with different game styles;
[0048] The acquisition of behavioral data of the target virtual character controlled by the target player includes:
[0049] Acquire the target virtual character's movement trajectory and combat data within the game activity area, as well as the target virtual character's interaction data with all the special interactive elements.
[0050] As described above, special interactive elements with different game styles are set up in the game activity area. At the same time, the movement trajectory, combat data, and interaction data of the target virtual character in the game activity area are collected to comprehensively judge the player's game style and improve the accuracy of the judgment.
[0051] Furthermore, the procedure before step S3 includes:
[0052] Pre-set NPCs that correspond one-to-one with the task templates, and set dialogue and interaction rules on the NPCs that are the same as the game style of the corresponding task templates;
[0053] The system receives the target player's quest request through an NPC and assigns the game quest to the target player.
[0054] As can be seen from the above description, when a task in the game is received from an NPC, some dialogue and interaction rules for the NPC are set according to the game style of the task template used in the game, so that the target player has a better interactive experience and enhances the fun of the game.
[0055] Furthermore, it also includes:
[0056] S4. After the target player completes the current game task, determine whether the time difference between the current time and the time node when the target player's game style was previously determined is greater than the preset time. If so, repeat step S2.
[0057] As described above, as the game progresses, players' preferred game styles may change accordingly. Therefore, a time condition with a preset duration is set. After a certain game task is completed, the target player's behavior data is retrieved again to re-evaluate the target player's game style, so as to prepare for subsequent task allocation, dynamically adjust, and improve the player's game experience.
[0058] Furthermore, it also includes:
[0059] S5. Obtain and adjust the content of the next game task for the target player based on the feedback from the target player regarding the current game task.
[0060] As can be seen from the above description, in addition to generating game tasks based on the game style, adjustments should also be made based on player feedback. For example, if players feel that the difficulty of the current game task is too high, the difficulty of the task will be adjusted accordingly when generating the next game task to improve the suitability of the task to the player's level or needs.
[0061] Please refer to Figure 1 Embodiment 1 of the present invention is as follows:
[0062] A method for personalized allocation of game task data includes the following steps:
[0063] S1. Pre-set at least two task templates that represent different game styles. Each task template has corresponding game levels with the same game style in the game.
[0064] In this embodiment, different game styles include, but are not limited to, aggressive combat and exploration / puzzle-solving. This embodiment only uses these two as examples for illustration.
[0065] 1. Aggressive combat type
[0066] Players enjoy combat and high-difficulty challenges when controlling virtual characters in the game. Therefore, corresponding mission templates and game levels can be designed as combat challenges, such as intense faction battles where two powerful factions engage in large-scale warfare in a specific battlefield area, requiring players to choose one side and fight for them; or powerful boss battles, such as a boss with multiple powerful skills and high health appearing in a dangerous dungeon for players to challenge. Specifically, the game engine's scene management and scripting systems are used to create combat scenes. For example, in Unity, scripts can be used to generate different factions and monsters, setting their attributes and behaviors. A random number generator is used to determine the specific content and difficulty of the mission.
[0067] Furthermore, the descriptive language in the mission templates can be optimized, such as "Two forces clash fiercely in the Dark Canyon; your strength will determine the outcome of this battle. Join the fight and fight for glory!" or "The terrifying Dragon King has appeared in the Flame Mountains; only the bravest warriors can challenge it. Are you ready?" etc., to provide players with a better gaming experience.
[0068] 2. Exploration and Decryption Type
[0069] Players enjoy exploring areas and solving puzzles while controlling a virtual character. Therefore, corresponding mission templates and game levels can be designed with hidden locations and puzzles, such as "The Secret of an Ancient Castle," which could be designed as an abandoned ancient castle hidden deep in a mysterious forest, with various mechanisms and puzzles waiting for players to solve. Alternatively, there could be "Mysterious Cave Exploration," a cave filled with unknown dangers and mysterious clues waiting to be explored. In implementation, the game engine's scene generation and puzzle design features are used to create exploration scenes. For example, in Unity, terrain tools can be used to create forest and cave scenes, and scripts can be used to set the logic of mechanisms and puzzles. A random number generator is used to determine the location of hidden locations and the difficulty of puzzles.
[0070] Additionally, the descriptive language in the task template can be optimized, such as: "In that forgotten ghost castle, some ancient magical secrets seem to be hidden, waiting for brave explorers to uncover the mystery." or "In the mysterious dark cave, a mysterious light flickers faintly; there must be an unknown secret hidden there. Go and explore!"
[0071] Furthermore, clustering algorithms from machine learning can be used to categorize players based on their answers to questions and their behavior data from the early stages of the game. For example, Player A, who explicitly stated a preference for intense combat when creating their character and actively attacks monsters early in the game, can be classified as an aggressive combat player. Player B, who showed a high interest in exploration-related questions when creating their character and explored the map extensively after the game started, can be classified as an exploration / puzzle player. In implementation, machine learning frameworks such as TensorFlow or Scikit-learn can be used to preprocess the collected player data, extract feature vectors, and then apply clustering algorithms for classification. The classification results are stored in a database for later retrieval during task assignment. Machine learning algorithms can be run periodically on the game server to update player classifications.
[0072] S2. During the game, acquire the behavior data of the target virtual character controlled by the target player, analyze the game style of the target player based on the behavior data of the target virtual character, and match the corresponding task template according to the game style of the target player.
[0073] In this embodiment, at least two special interactive elements with different gameplay styles are set up within the game activity area corresponding to the initial stage of the game. Obtaining the behavioral data of the target virtual character controlled by the target player includes: acquiring the target virtual character's movement trajectory within the game activity area, combat data, and interaction data between the target virtual character and all special interactive elements. Optionally, the game engine's event system and logging function are used to record player behavior. For example, in Unity, custom events can be triggered during key events in combat and exploration, and then scripts can record the event occurrence time, player combat data, and other information to a log file.
[0074] Regarding special interactive elements, one approach could be to set a uniform method for obtaining rewards during the first few minutes after players enter the game. For example, rewards could be placed in a specific area, and players could obtain these rewards through two challenge paths: high-skill combat or puzzle-solving exploration.
[0075] For the challenging combat paths, powerful monsters are introduced, requiring players to actively engage in intense battles and demonstrate high skill levels to earn rewards. For example, these monsters possess high attack and defense, demanding players skillfully utilize abilities and strategies to defeat them. Conversely, for the puzzle-solving exploration paths, hidden clues and puzzles are set up within the area. Players must carefully observe the environment, search for clues, and solve the puzzles to obtain rewards. For instance, mysterious symbols or mechanisms hidden in a corner require players to use reasoning and exploration to discover and activate them.
[0076] Furthermore, the observation points are simultaneously presented with interactive, even somewhat hidden, content, such as hidden treasure chests, mysterious runes, or interaction mechanics with specific objects. Players are observed to determine whether they attempt to find and interact with these interactive elements, thus increasing the accuracy of their playstyle assessment. Players who actively seek out and interact with these hidden elements are more likely to exhibit an exploration and puzzle-solving style. Conversely, players who pay little attention to these interactive elements and instead actively seek out monsters for combat are more likely to be identified as having a combat-oriented playstyle.
[0077] Regarding special interactive elements, triggers can also be set up in the game scene to record events when a player enters a specific area or interacts with a specific object. For example, a collision trigger can be set up around a monster; when a player enters the trigger's range and attacks the monster, it can be recorded as a combat action. Similarly, observation points can be set up at key locations on the map; when a player stays at an observation point for a certain period, it can be recorded as an exploration action. These functionalities can be implemented using the game engine's physics and event systems, such as Unity's Physics and Event systems.
[0078] In this embodiment, NPCs are pre-set to correspond one-to-one with the task templates, and dialogue and interaction rules with the same game style as the corresponding task templates are set on the NPCs; the NPCs receive task requests from target players and assign game tasks to target players.
[0079] The dialogue interaction rules can be as follows: tasks are assigned to players through dialogue or task prompt windows. When a player interacts with a specific NPC, the NPC will say lines corresponding to the game's style. For example, for an aggressive combatant, the dialogue could be: "Warrior, I see the fighting spirit within you. Two forces are locked in a fierce battle in Dark Canyon, and you are exactly the strength we need. Join the battle!" Alternatively, when a player enters a specific area, a task prompt window will pop up, displaying a task description and an accept button. Task assignment is implemented using the game engine's NPC interaction system and UI system. When a player interacts with a specific NPC, a dialogue event is triggered, and the NPC's dialogue and task assignment logic are controlled by scripts. When a player enters a specific area, a trigger is used to detect the player's location, and then a task prompt window pops up. This task prompt window can be created using Unity's UI system, and its display and interaction can be controlled by scripts.
[0080] S3. Generate game tasks based on the matched task template and the target virtual character's character information, and assign the game tasks to the target player after receiving the target player's task request.
[0081] In this embodiment, the game levels of the task template are set in different map areas to separate players at the same time or stage of the game, avoid a large number of players gathering at the task pick-up point or task execution point, and reduce the data processing pressure on the server.
[0082] When generating game quests, the acquired character information includes, but is not limited to, the target virtual character's level, attributes, class, etc., and then the variable parameters such as the monster level involved in the game template are adjusted to obtain game quests that are adapted to the target virtual character in terms of difficulty, rewards, etc.
[0083] S4. After the target player completes the current game task, determine whether the time difference between the current time and the time point when the target player's game style was determined last time is greater than the preset time. If so, repeat step S2.
[0084] In this embodiment, when step S2 is re-executed, i.e., the target player's game style is redefined, the incremental learning function of a machine learning algorithm can be used. When new player behavior data appears, the player's feature vector is updated, and the player is reclassified. For example, an online learning algorithm, such as stochastic gradient descent, can be used to continuously adjust the model parameters based on new data. On the game server side, a scheduled task can be set to trigger the dynamic adjustment process, ensuring that the player's classification and task assignment always match their behavior.
[0085] S5. Obtain and adjust the content of the next game task for the target player based on their feedback on the current game task.
[0086] In this embodiment, after a player completes a task, a feedback window pops up, allowing the player to rate the task's difficulty, enjoyment, and other aspects, and to provide text feedback. Optionally, the feedback window can be created using the game engine's UI system, and its display and interaction can be controlled by scripts. When a player completes a task, a feedback event is triggered, and a window pops up for the player to provide feedback. The player's feedback data is stored in a database for subsequent adjustments to the content of the next game task for the target player.
[0087] For example, if many players report that a certain combat mission is too difficult, the system can appropriately reduce the difficulty of that mission; if players report that the clues in a certain exploration mission are not clear enough, more obvious clues can be added. Optionally, data analysis tools can be used to analyze player feedback data to identify the characteristics of problematic missions and directions for improvement. Based on the analysis results, the parameters and logic of mission generation can be adjusted. For example, if the difficulty of a certain combat mission is reported to be too high, the monster's health or attack power can be reduced; if the clues in a certain exploration mission are not clear enough, more clue items or NPC dialogue hints can be added. On the game server side, missions can be optimized regularly based on feedback data to ensure mission quality and player satisfaction.
[0088] Please refer to Figure 2 Embodiment two of the present invention is as follows:
[0089] A personalized game task data allocation terminal 1 includes a memory 2, a processor 3, and a computer program stored on the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, it implements a personalized game task data allocation method according to Embodiment 1.
[0090] In summary, the present invention provides a method and terminal for personalized allocation of game task data. Multiple task templates with different game styles are pre-set, each with corresponding game levels. Before allocating game tasks, the game style of the target player is determined based on the behavioral data of the target virtual character controlled by the target player, and then corresponding game tasks are assigned. This approach caters to different players' preferences, enhancing game playability. Furthermore, compared to all players having the same tasks, it avoids large player gatherings within the game, reduces server data processing pressure on the same game scene, and improves game smoothness. During the game, the determination of the player's game style is updated based on the player's behavioral data, ensuring that subsequent tasks match the player. Additionally, feedback can be incorporated to adjust task content and optimize the game experience.
[0091] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.
Claims
1. A method for personalized allocation of game task data, characterized in that, Includes the following steps: S1. Pre-set at least two task templates representing different game styles, wherein the task templates have corresponding game levels of the same game style in the game; S2. During the game process, acquire the behavior data of the target virtual character controlled by the target player, analyze the game style of the target player based on the behavior data of the target virtual character, and match the corresponding task template based on the game style of the target player; S3. Generate a game task based on the matched task template and the character information of the target virtual character, and assign the game task to the target player after receiving the task request from the target player.
2. The method for personalized allocation of game task data according to claim 1, characterized in that, The procedure preceding step S2 also includes: In the game activity area corresponding to the early stage of the game, set up at least two special interactive elements with different game styles; The acquisition of behavioral data of the target virtual character controlled by the target player includes: Acquire the target virtual character's movement trajectory and combat data within the game activity area, as well as the target virtual character's interaction data with all the special interactive elements.
3. The method for personalized allocation of game task data according to claim 1, characterized in that, Before step S3, the following also includes: Pre-set NPCs that correspond one-to-one with the task templates, and set dialogue and interaction rules on the NPCs that are the same as the game style of the corresponding task templates; The system receives the target player's quest request through an NPC and assigns the game quest to the target player.
4. The method for personalized allocation of game task data according to claim 1, characterized in that, Also includes: S4. After the target player completes the current game task, determine whether the time difference between the current time and the time node when the target player's game style was previously determined is greater than the preset time. If so, repeat step S2.
5. The method for personalized allocation of game task data according to claim 1, characterized in that, Also includes: S5. Obtain and adjust the content of the next game task for the target player based on the feedback from the target player regarding the current game task.
6. A personalized game task data allocation terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it performs the following steps: S1. Pre-set at least two task templates representing different game styles, wherein the task templates have corresponding game levels of the same game style in the game; S2. During the game process, acquire the behavior data of the target virtual character controlled by the target player, analyze the game style of the target player based on the behavior data of the target virtual character, and match the corresponding task template based on the game style of the target player; S3. Generate a game task based on the matched task template and the character information of the target virtual character, and assign the game task to the target player after receiving the task request from the target player.
7. A personalized game task data allocation terminal according to claim 6, characterized in that, The procedure preceding step S2 also includes: In the game activity area corresponding to the early stage of the game, set up at least two special interactive elements with different game styles; The acquisition of behavioral data of the target virtual character controlled by the target player includes: Acquire the target virtual character's movement trajectory and combat data within the game activity area, as well as the target virtual character's interaction data with all the special interactive elements.
8. A personalized game task data allocation terminal according to claim 6, characterized in that, Before step S3, the following also includes: Pre-set NPCs that correspond one-to-one with the task templates, and set dialogue and interaction rules on the NPCs that are the same as the game style of the corresponding task templates; The system receives the target player's quest request through an NPC and assigns the game quest to the target player.
9. A personalized game task data allocation terminal according to claim 6, characterized in that, Also includes: S4. After the target player completes the current game task, determine whether the time difference between the current time and the time node when the target player's game style was previously determined is greater than the preset time. If so, repeat step S2.
10. A personalized game task data allocation terminal according to claim 6, characterized in that, Also includes: S5. Obtain and adjust the content of the next game task for the target player based on the feedback from the target player regarding the current game task.