A method and device for distributing random map exploration rewards in a 2D game

Abstract

This invention provides a method and apparatus for randomly distributing map exploration rewards in a 2D game. The method includes: generating potential reward trigger points based on the current game task completion status and the game character's position on the game map; setting trigger conditions for each potential reward trigger point; if the game character arrives at a potential reward trigger point and the game character's interaction behavior meets the trigger conditions, then matching the target reward pool based on the interaction behavior completed by the game character; determining the exploration reward category based on the game character's current game character level and current game progress; determining the exploration reward item and reward item level based on the game character's current game character attributes, cumulative in-game time, and game world state; and drawing the final exploration reward from the target reward pool based on the exploration reward category, exploration reward item, and reward item level, and distributing it to the game character. This invention improves player engagement in the game.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method and apparatus for distributing rewards for random map exploration in 2D games. Background Technology

[0002] In existing 2D games, the methods for distributing rewards for random map exploration are usually quite simple and direct. For example, when a player enters a specific area of ​​the map or completes a specific exploration action (such as opening a treasure chest or defeating a specific monster), the game system directly distributes rewards according to preset fixed rules. However, existing methods for distributing rewards for random map exploration lack sufficient fun and player engagement. Because the reward distribution rules are fixed, players easily become bored with the reward pattern after multiple explorations, lacking a sense of novelty and surprise in exploration, reducing the game's long-term appeal, and consequently reducing player stickiness. Summary of the Invention

[0003] This invention provides a method and apparatus for distributing random map exploration rewards in 2D games, in order to increase player engagement.

[0004] In a first aspect, the present invention provides a method for distributing random map exploration rewards in a 2D game, comprising:

[0005] Based on the real-time acquisition of the game character's current game task completion status and game position on the game map during the 2D game operation, potential reward trigger points are generated.

[0006] Set trigger conditions for each potential reward trigger point; the trigger conditions include completing at least two different interactive behaviors, including triggering hidden mechanisms, completing a specific path, having a conversation with a specific character in a specific order, and using a specific item to perform an operation at a specific location;

[0007] During the game character's exploration of the game map, if the game character arrives at a potential reward trigger point and the game character's interaction behavior meets the triggering conditions, then the target reward pool is matched in the reward pool set according to the combination of the game character's completed interaction behaviors; the reward pool set is updated according to the game version.

[0008] The exploration reward category is determined based on the game character's current level and current game progress, and the exploration reward item and reward item level are determined based on the game character's current attributes, cumulative in-game time, and game world status.

[0009] Based on the exploration reward category, the exploration reward item, and the reward item level, the final exploration reward is drawn from the target reward pool and displayed at the potential reward trigger point.

[0010] According to an embodiment of the present invention, a method for distributing random map exploration rewards in a 2D game includes generating potential reward trigger points based on the completion status of the game character's current game tasks and the game character's position on the game map, which are obtained in real time during the operation of the 2D game.

[0011] A correlation strength analysis was performed on the current game task completion status of the game character and the game position of the game character on the game map to obtain the correlation coefficient between task progress and game position;

[0012] The location difficulty is determined based on the terrain and virtual monster distribution in each area of ​​the game map, and a matching analysis is performed based on the task difficulty level and location difficulty of the current game task to obtain the difficulty matching coefficient.

[0013] Based on the correlation coefficient, the difficulty matching coefficient, and the location heatmap of the game map, the potential reward trigger points are generated; the location heatmap represents the popularity of each area and is constructed based on the frequency of game characters appearing in different game locations.

[0014] According to an embodiment of the present invention, a method for distributing random exploration rewards in a 2D game map includes generating potential reward trigger points based on the correlation coefficient, the difficulty matching coefficient, and the location heatmap of the game map, comprising:

[0015] Based on the correlation coefficient, the difficulty matching coefficient, and the location heatmap of the game map, the initial probability of each location in the game map becoming a reward trigger point is obtained.

[0016] The probability of each location becoming a reward trigger point is adjusted based on the current game time and in-game activity frequency of the game character to obtain the final probability of each location becoming a reward trigger point.

[0017] Iterate through the final probability of each position becoming a reward trigger point, and determine the reward trigger points whose final probability is greater than or equal to a preset probability threshold as the potential reward trigger points.

[0018] According to an embodiment of the present invention, a method for distributing random map exploration rewards in a 2D game includes matching a target reward pool from a reward pool set based on the combination of interactive behaviors performed by the game character.

[0019] Based on the behavioral characteristics of the game character when completing each target interactive behavior in the combination of interactive behaviors, the behavioral characteristic value of each target interactive behavior is determined.

[0020] The behavior combination complexity of the interaction behavior combination is calculated based on the time interval between the target interaction behaviors in the interaction behavior combination and the behavior feature value of each target interaction behavior.

[0021] Based on the combined complexity of the behaviors, a matching process is performed in the reward pool set to obtain a candidate set for the reward pool.

[0022] Based on the correlation analysis of the candidate set of the reward pool and the game context when the interaction behavior combination occurs, the target reward pool of the interaction behavior combination is obtained.

[0023] According to an embodiment of the present invention, a method for distributing random map exploration rewards in a 2D game includes, in which the step of performing correlation analysis based on the candidate set of the reward pool and the game context in which the interaction behavior combination occurs to obtain the target reward pool for the interaction behavior combination includes:

[0024] Based on the current stage of the game, the attribute state of the player character, and the environmental state of the game world when the interaction behavior combination occurs, the correlation between the interaction behavior combination and the game context is determined.

[0025] Based on the correlation, the candidate set of the reward pool is matched to obtain the final reward pool set;

[0026] Based on the frequency of occurrence of the interaction behavior combination in the game history and the latest rewards obtained by the game character, the compatibility between the interaction behavior combination and each reward pool in the final reward pool set is determined.

[0027] Iterate through the fit of each reward pool and determine the reward pool with the largest fit in the final reward pool set as the target reward pool.

[0028] According to an embodiment of the present invention, a method for distributing random exploration rewards in a 2D game map includes determining the exploration reward category based on the current game character level and current game progress, comprising:

[0029] Map the current game character level and the current game progress to obtain the level mapping result and the progress stage division result;

[0030] Based on the level mapping results and the progress stage division results, a cross-influence analysis is performed to obtain the cross-influence value between game character level and game progress.

[0031] The characteristics of the explored areas are determined based on the degree of danger and the abundance of resources in the areas explored by the game characters during the exploration of the game map;

[0032] The exploration reward category is determined based on the cross-influence value, the characteristics of the exploration area, and the character's career orientation characteristics.

[0033] According to an embodiment of the present invention, a method for distributing random exploration rewards in a 2D game map includes determining the exploration reward items and their levels based on the game character's current attributes, cumulative in-game time, and game world status.

[0034] The cumulative time in the game is broken down according to different game behaviors, and the time factor of the game time for each game behavior on the exploration reward is obtained.

[0035] Based on the current game character attributes, the time factor of exploration rewards for each game action, and the topological structure of the game world state, the initial exploration reward potential of the game character in the current state is determined; the topological structure is constructed with each region in the game world as a node and the connection relationship between regions as node edges.

[0036] The initial exploration reward potential is adjusted based on dynamic events occurring in the game world in real time, resulting in the adjusted reward potential value of the game character in the current state. Based on the adjusted reward potential value, item mapping is performed to obtain the exploration reward item and the level of the reward item.

[0037] In a second aspect, the present invention also provides a device for distributing random map exploration rewards in a 2D game, applied to the method for distributing random map exploration rewards in a 2D game as described in the first aspect, comprising:

[0038] The trigger point generation module is used to generate potential reward trigger points based on the completion status of the game character's current game task and the game character's position on the game map, which are obtained in real time during the operation of the 2D game.

[0039] The settings module is used to set trigger conditions for each potential reward trigger point;

[0040] The reward pool matching module is used to match the target reward pool in the reward pool set according to the combination of interactive behaviors completed by the game character in the game character's exploration of the game map if the game character arrives at a potential reward trigger point and the game character's interactive behavior meets the trigger conditions.

[0041] The reward information generation module is used to determine the exploration reward category based on the game character's current game character level and current game progress, and to determine the exploration reward items and reward item levels based on the game character's current game character attributes, cumulative in-game time, and game world status;

[0042] The reward distribution module is used to extract the final exploration reward from the target reward pool based on the exploration reward category, the exploration reward item, and the reward item level, and to display the final exploration reward at the potential reward trigger point.

[0043] Thirdly, the present invention also provides an electronic device, comprising: a memory for storing computer software programs; and a processor for reading and executing the computer software programs, thereby implementing the method for distributing random map exploration rewards in any of the above-described 2D games.

[0044] Fourthly, the present invention also provides a non-transitory computer-readable storage medium storing a computer software program, which, when executed by a processor, implements the map random exploration reward distribution method in any of the above-described 2D game methods.

[0045] Fifthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements a method for distributing random map exploration rewards in any of the above-described 2D games.

[0046] The method for randomly distributing map exploration rewards in 2D games provided by this invention sets trigger conditions including multiple interaction modes for each potential reward trigger point, greatly enriching the ways players interact with the map and increasing the fun of exploration. On the other hand, the multiple interaction modes and complex judgment mechanism mean that different interactive behaviors may trigger different rewards each time a player explores, making it difficult to predict how rewards will be obtained. This effectively solves the problem of player boredom caused by fixed reward patterns in existing methods, enhancing the game's fun and player engagement. Therefore, this invention improves player stickiness to the game. Attached Figure Description

[0047] Figure 1 This is a flowchart illustrating the method for distributing random map exploration rewards in a 2D game, as provided in an embodiment of the present invention.

[0048] Figure 2 This is a schematic diagram of the structure of the 2D game map random exploration reward distribution device provided in an embodiment of the present invention;

[0049] Figure 3 An embodiment diagram of the electronic device provided in this invention;

[0050] Figure 4 An embodiment diagram of a computer-readable storage medium provided in accordance with the present invention. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0053] In the description of this invention, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed herein.

[0054] See Figure 1 As shown, Figure 1 This is a flowchart illustrating the method for distributing random map exploration rewards in a 2D game provided by the present invention. In this embodiment of the invention, the executing entity of the method for distributing random map exploration rewards in a 2D game is a game control device. Therefore, the method for distributing random map exploration rewards in a 2D game includes:

[0055] Step 10: Based on the real-time completion status of the game character's current game task and the game character's position on the game map obtained during the 2D game operation, generate potential reward trigger points.

[0056] Optionally, players can launch the 2D game by clicking the game app provided on the game control device's interface. After the 2D game is launched, the game control device monitors the game's operation in real time, such as the current game task being performed by the player's character, the completion status of the current game task (i.e., task completion stage), the game character's position on the game map, the current game character's attributes, the cumulative time in the game, the environmental state of the game world, the state of the game world, the current game character's level, the current game progress, and the game character's attribute status (intelligence, health, attack power, etc.).

[0057] Therefore, the game control device obtains the current game task completion status and the game position of the game character controlled by the player during the 2D game operation. Based on the current game task completion status and the game position of the game character on the game map, it generates potential reward trigger points on the game map, as described in steps 101 to 103.

[0058] Step 20: Set trigger conditions for each potential reward trigger point.

[0059] Furthermore, the game control device sets trigger conditions for each potential reward trigger point. The trigger conditions include completing at least two different interactive behaviors, such as triggering a hidden mechanism, completing a specific path, talking to a specific character in a specific order, and using a specific item to perform an operation at a specific location. That is, the trigger conditions are any two or more of the following: triggering a hidden mechanism, completing a specific path, talking to a specific character in a specific order, and using a specific item to perform an operation at a specific location.

[0060] Step 30: During the game character's exploration of the game map, if the game character arrives at a potential reward trigger point and the game character's interaction behavior meets the trigger conditions, then the target reward pool is matched in the reward pool set according to the combination of interaction behaviors completed by the game character.

[0061] Optionally, in this embodiment of the invention, the reward pool set of the 2D game is updated according to the game version; that is, when the 2D game is updated, the reward pool set of the 2D game is also updated.

[0062] Furthermore, the game control device monitors the game character's position during exploration of the game map. When it is determined that the game character's position on the game map is within the range of a potential reward trigger point (i.e., the game character has arrived at the potential reward trigger point), the game control device monitors the game character's interactive behavior. If it is determined that the game character has completed at least two interactive behaviors (i.e., the game character's interactive behaviors meet the trigger conditions), the interactive behaviors completed by the game character are integrated to obtain the combination of interactive behaviors completed by the game character.

[0063] Furthermore, the game control device matches the combination of interactive behaviors completed by the game character in the reward pool set to obtain the target reward pool for the distribution of exploration rewards, as detailed in steps 301 to 304.

[0064] Step 40: Determine the exploration reward category based on the game character's current game character level and current game progress, and determine the exploration reward items and reward item levels based on the game character's current game character attributes, cumulative in-game time, and game world status.

[0065] Furthermore, the game control device determines the exploration reward category based on the game character's current level and current game progress, as described in steps 401 to 404. Furthermore, the game control device determines the exploration reward item and its level based on the game character's current attributes, cumulative in-game time, and game world state, as described in steps 405 to 408.

[0066] Step 50: Based on the exploration reward category, exploration reward item, and reward item level, extract the final exploration reward from the target reward pool and display the final exploration reward at the potential reward trigger point.

[0067] Furthermore, the game control device extracts the corresponding final exploration reward from the target reward pool based on the exploration reward category, exploration reward item, and reward item level, and displays the final exploration reward at the potential reward trigger point. In other words, the final exploration reward is sent to the potential reward trigger point, and the game player can control the game character to pick up the final exploration reward at the potential reward trigger point.

[0068] This invention sets trigger conditions with multiple interaction modes for each potential reward trigger point, greatly enriching the ways players interact with the map and increasing the fun of exploration. On the other hand, the multiple interaction modes and complex judgment mechanism mean that different interactive behaviors may trigger different rewards each time a player explores, making it difficult to predict how to obtain rewards, thus increasing the fun of the game and player participation, and therefore increasing player stickiness.

[0069] In one embodiment, steps 101 to 103 are described as follows:

[0070] Step 101: Perform a correlation strength analysis on the completion status of the current game task of the game character and the game position of the game character on the game map to obtain the correlation coefficient between task progress and game position.

[0071] Optionally, the game control device performs a correlation strength analysis between the completion status of the game character's current game task and the game character's current game position. This involves analyzing the probability of different task stages appearing in different areas of the map to obtain the correlation coefficient between task progress and game position. In one embodiment, the total number of stages in the current game task is N. G The current game task completion status is stage G. T The current game mission's median stage is G. median The game character's position on the game map is L. T Therefore, the correlation coefficient C between task progress and game position is... TL Therefore, the correlation coefficient C TLThe specific calculation formula is as follows:

[0072] C TL =[(G T / N G )*cos(Hash(L T )π)] / (1+|G T -G median |).

[0073] Step 102: Determine the location difficulty based on the terrain and virtual monster distribution of each area of ​​the game map, and perform a matching analysis based on the task difficulty level and location difficulty of the current game task to obtain the difficulty matching coefficient.

[0074] Furthermore, the game control device acquires the terrain and virtual monster distribution of each area in the game map, divides the terrain of each area in the game map into different terrain types, divides the map area with a preset grid size, and counts the number of monsters in each grid. Among them, different terrain types include plains, mountains, rivers, forests, etc., and the preset grid size is such as 3*3, 5*5, etc.

[0075] It should be noted that each terrain type has a pre-set complexity value. For example, plains have a low complexity value of 1; mountains have a complexity value of 3 due to their undulating terrain and difficult passage; rivers have a complexity value of 2 if they require special passage methods; and forests may have issues such as obstructed views, so their complexity value is 2.

[0076] Furthermore, the game control device determines the terrain complexity of each region based on the proportion of different terrain types and their corresponding complexity values. In one embodiment, region R... i Medium terrain type O j The area ratio is S ij Terrain type O j The complexity is C. j Then region R i Terrain complexity TC i for:

[0077] Where, N O This indicates the total number of terrain types.

[0078] Furthermore, the game control device calculates the average monster distribution density based on the number of monsters in all grids within each area. In one embodiment, area R... i It contains N R The m-th grid R The number of monsters in each grid is N. im The grid area is A m Then region R i The monster distribution density is:

[0079]

[0080] Furthermore, the game controls determine the location difficulty (DL) of each area based on its terrain complexity and average monster density. i Specifically, DL i =α*TC i +(1-α)*MD i , where α represents the preset weight coefficient, and the location difficulty of the game position is determined by the area to which the game character's position in the game map belongs.

[0081] Furthermore, the game control device can obtain the difficulty level of the current game task, which can be obtained based on the version number of the current game task.

[0082] Furthermore, the game control device performs a matching analysis based on the task difficulty level and location difficulty of the current game mission to obtain a difficulty matching coefficient. In one embodiment, the task difficulty level is D. T The location difficulty is DL, and the difficulty matching coefficient is M. TL The specific formula is:

[0083] M TL ={cos[(D T / Max D Max D This indicates the highest level of task difficulty.

[0084] Step 103: Based on the correlation coefficient, difficulty matching coefficient, and location heatmap of the game map, generate potential reward trigger points.

[0085] Optionally, the location heatmap in this embodiment of the invention represents the heat of each region and is constructed based on the frequency of game characters appearing in different game locations. In the location heatmap, the heat value of each game location L is H(L), and the number of times game location L appears in historical data is N. L The total number of records is N total The distance from the game position L to the center of the game map is dis. L Then the heat value H(L) can be expressed as:

[0086] H(L)=(N L / N total )*[1 / (1+(dis L ) 2 )).

[0087] Furthermore, the game control device generates potential reward trigger points based on the correlation coefficient, difficulty matching coefficient, and location heatmap of the game map, as described in steps 1031 to 1033.

[0088] According to the embodiments of the present invention, potential reward trigger points are randomly generated based on the completion status of the current game task of the game character and the game position of the game character in the game map. This greatly enriches the way players interact with the map, increases the fun of exploration, and further improves the stickiness of game players.

[0089] In one embodiment, steps 1031 to 1033 are described as follows:

[0090] Step 1031: Based on the correlation coefficient, difficulty matching coefficient and the location heatmap of the game map, predict the initial probability of each location in the game map becoming a reward trigger point.

[0091] Optionally, the game control device determines the heat value H(L) corresponding to each location in the game map based on the location heatmap, and predicts the initial probability of each location in the game map becoming a reward trigger point based on the correlation coefficient, difficulty matching coefficient, and the heat value H(L) corresponding to each location. The formula is as follows: Where ω1, ω2, and ω3 represent preset coefficients, and ω1 + ω2 + ω3 = 1.

[0092] Step 1032: Adjust the probability of each position becoming a reward trigger point based on the current game time and in-game activity frequency of the game character to obtain the final probability of each position becoming a reward trigger point.

[0093] Furthermore, the game control device analyzes the current game time and overall game rhythm (i.e., the frequency of in-game activities) of the game character. Different game times and game rhythms have different impacts on the probability of reward trigger points. For example, in the early stages of the game, there may be a greater emphasis on simple reward triggers to guide the player, while in the later stages, there may be a greater emphasis on high-difficulty challenge rewards. The trigger point adjustment coefficient is calculated based on the current game time and the frequency of in-game activities of the game character. In one embodiment, the current game time is t, and the estimated total game duration is T. total The frequency of in-game activities is R. f The trigger point adjustment coefficient of position L under the influence of game time and game rhythm is A. L A L ={sin[(t / T)} total +R f )*π]} / 2+0.5.

[0094] Furthermore, the game control device adjusts the probability of each position becoming a reward trigger point based on the trigger point adjustment coefficient influenced by game time and game rhythm, thus obtaining the final probability P of each position becoming a reward trigger point. L ,

[0095] Step 1033: Iterate through the final probability of each position becoming a reward trigger point, and determine the reward trigger points with a final probability greater than or equal to a preset probability threshold as potential reward trigger points.

[0096] Furthermore, the game control device iterates through the final probability of each location becoming a reward trigger point, and determines the reward trigger points with a final probability greater than or equal to a preset probability threshold as potential reward trigger points.

[0097] This invention generates potential reward trigger points randomly based on correlation coefficients, difficulty matching coefficients, and location heatmaps of the game map. This greatly enriches the ways players interact with the map, increases the fun of exploration, and further enhances player engagement.

[0098] In one embodiment, steps 301 to 304 are described as follows:

[0099] Step 301: Based on the behavioral characteristics of the game character when completing each target interactive behavior in the combination of interactive behaviors, determine the behavioral characteristic value of each target interactive behavior.

[0100] Optionally, the game control device extracts behavioral features when each target interaction behavior in the combination of interactive behaviors is completed. For example, when the target interaction behavior triggers a hidden mechanism, the behavioral features are the location of the mechanism and the complexity of the triggering condition; when the target interaction behavior is to walk a specific path, the behavioral features are the path length, the number of turns, and the rarity of the area traversed by the path; when the target interaction behavior is to talk to a specific character in a specific order, the behavioral features are the number of characters in the dialogue and the logic of the dialogue order; when the target interaction behavior is to use a specific item to operate in a specific location, the behavioral features are the rarity of the item and the specialness of the operation location.

[0101] Furthermore, the game control device determines the behavioral characteristic value of each target interactive behavior based on the behavioral characteristics of the character when completing each target interactive behavior in the combination of interactive behaviors.

[0102] For the target interaction behavior A1 that triggers the hidden mechanism, its behavioral characteristic value F(A1) = L location *C location , where L location The coordinate complexity value representing the location of the mechanism (calculated based on the game map coordinate system), C locationThis represents the complexity score of the triggering condition. For the target interaction behavior A2 that completes walking along a specific path, its behavioral feature value F(A2) = L path *N turn *R area , where L path N represents the path length. turn R represents the number of turns. area This represents the rarity value of the area traversed by the path.

[0103] For target interaction behavior A3 involving dialogue with a specific character in a specific order, its behavioral characteristic value is... Where, N character S represents the number of characters in the dialogue. order (i, i+1) represents the logical score of the order of the i-th and i+1-th dialogue characters. For the target interaction behavior A4, which uses a specific prop and operates at a specific location, its behavior feature value F(A4) = R item *S location , where R item S indicates the rarity of the item. location The score indicates the specificity of the operation location.

[0104] Step 302: Calculate the behavior combination complexity of the interaction behavior combination based on the time interval between the occurrence of the target interaction behaviors in the interaction behavior combination and the behavior feature value of each target interaction behavior.

[0105] Furthermore, the game control device acquires the time interval between the occurrences of target interactive behaviors in the interactive behavior combination, and calculates the behavior combination complexity of the interactive behavior combination based on the time interval between the occurrences of target interactive behaviors in the interactive behavior combination and the behavior feature value of each target interactive behavior. In one embodiment, for the interactive behavior combination Q... A The number of interactive behaviors is N. Q Target interaction behavior A i Interaction behavior with target A i+1 The time interval between the actions is T(A) i A i+1 Therefore, the interaction behavior combination Q A Combinatorial complexity (Q) A )for:

[0106]

[0107] Step 303: Match the reward pool set based on the behavior combination complexity to obtain the reward pool candidate set.

[0108] Furthermore, the game control device matches the reward pool set with the pre-set reward pool and the behavior combination features based on the behavior combination complexity, and generates a reward pool candidate set. The higher the combination complexity, the higher the potential reward value of the reward pool in the candidate set.

[0109] In one embodiment, the reward pool set is U = {u1, u2, ..., u}. h The reward pool value sequence corresponding to the reward pool set is V={v1,v2,...,v}. h The complexity threshold sequence corresponding to the reward pool value sequence is X = {x1, x2, ..., x}. h If Complexity(Q) A )≥x k And Complexity(Q) A ) <x k+1 Then the candidate set for the reward pool is Candidate = {u i |i≥k}.

[0110] Step 304: Based on the candidate set of the reward pool and the game context when the combination of interactive behaviors occurs, perform correlation analysis to obtain the target reward pool for the combination of interactive behaviors.

[0111] Furthermore, the game control device acquires the game context when the combination of interactive behaviors occurs. The game context includes the current stage of the game, the attribute status of the player character, and the environmental status of the game world, such as the level of danger and the abundance of resources.

[0112] Furthermore, the game control device performs correlation analysis based on the candidate set of the reward pool and the game context when the combination of interactive behaviors occurs, to obtain the target reward pool for the combination of interactive behaviors, as described in steps 3041 to 3044.

[0113] In this embodiment of the invention, the game character's interactive behavior is combined with the target reward pool in the reward pool set, so that the final game reward is consistent with the player's efforts in the game. At the same time, the multiple interaction modes and complex judgment mechanism mean that different rewards may be triggered by different interactive behaviors each time the player explores, making it difficult to predict how to obtain rewards, which enhances the fun of the game and the player's participation, and further improves the player's stickiness to the game.

[0114] In one embodiment, steps 3041 to 3044 are described as follows:

[0115] Step 3041: Determine the correlation between the interaction behavior combination and the game context based on the current stage of the game, the attribute state of the player character, and the environmental state of the game world when the interaction behavior combination occurs.

[0116] Optionally, the game control device analyzes the correlation between the game context and the combination of interactive behaviors, that is, the correlation between the current stage of the game, the attribute state of the player character, and the environmental state of the game world when the combination of interactive behaviors occurs, and the combination of interactive behaviors.

[0117] In one embodiment, the game context vector is G = {g1, g2, ..., g...} s The correlation between the combination of interactive behaviors and the game context is: Among them, F(Q) A R represents the behavioral combination feature in the interaction behavior combination. factor (F(Q A ),g t The denoted is a correlation measurement function between behavioral combination features and game context factors, which can be measured by calculating the reciprocal of the distance between the behavioral combination feature values ​​and the game context factor values ​​in a specific space.

[0118] Step 3042: Match the candidate set of the reward pool based on the correlation to obtain the final reward pool set.

[0119] Furthermore, the game control device matches the reward pool candidate set based on the relevance to obtain the final reward pool set. In one embodiment, for each reward pool u in the reward pool candidate set... i The corresponding correlation threshold is Thershold. i If Relevance(Q) A ,G) <Thershold i Then the reward pool u i The final reward pool set is obtained by removing from the candidate reward pool set.

[0120] Step 3043: Based on the frequency of occurrence of the interaction behavior combination in the game history and the latest rewards obtained by the game character, determine the fit between the interaction behavior combination and each reward pool in the final reward pool set.

[0121] Furthermore, the game control device acquires the frequency of occurrence of the interaction behavior combination in the game history and the latest rewards obtained by the game character. Further, based on the frequency of occurrence of the interaction behavior combination in the game history and the latest rewards obtained by the game character, the game control device determines the fit between the interaction behavior combination and each reward pool in the final reward pool set.

[0122] In one embodiment, the interaction behavior combination Q A The frequency of occurrence is Frequency(Q) A The latest reward value sequence obtained by the game character controlled by the player is R. recnt={r1,r2,...,r q For each reward pool u in the final reward pool set i Its fitness (u) is well-suited to the combination of interactive behaviors. i )for.

[0123] Wherein, V(u) i ) represents the reward pool u i The value measure.

[0124] Step 3044: Iterate through the fit of each reward pool and determine the reward pool with the largest fit in the final reward pool set as the target reward pool.

[0125] Furthermore, the game control device iterates through the fit of each reward pool and determines the reward pool with the highest fit in the final reward pool set as the target reward pool.

[0126] The embodiments of the present invention, through multiple interaction modes and complex judgment mechanisms, enable players to trigger different rewards each time they explore due to different interactive behaviors, making it difficult to predict how to obtain rewards, thereby enhancing the fun of the game and the participation of players, and further increasing the stickiness of players to the game.

[0127] In one embodiment, steps 401 to 404 are described as follows:

[0128] Step 401: Map the current game character level and the current game progress to obtain the level mapping result and the progress stage division result.

[0129] Optionally, the game control device divides the game character's level into different level ranges, resulting in a level mapping result. Each range corresponds to a different exploration reward preference; for example, lower level ranges may emphasize basic resource rewards, while higher level ranges may emphasize rare items or special skill rewards. Simultaneously, the game control device divides the current game progress into different stages, resulting in a progress stage classification result, such as the beginner stage, growth stage, advanced stage, and mastery stage. Different stages will have different emphasis on exploration rewards; the beginner stage may focus on introductory rewards, while the mastery stage may offer more challenging and advanced rewards.

[0130] Step 402: Based on the level mapping results and progress stage division results, perform cross-influence analysis to obtain the cross-influence value between game character level and game progress.

[0131] Furthermore, considering the interplay between level and progress, different levels may exhibit different biases towards reward categories at different progress stages. For example, high-level players may receive rewards that help them progress quickly in the beginner stage, while low-level players may receive rewards that help them improve their strength in the mastery stage. Therefore, the game control device performs a cross-influence analysis based on the level mapping results and the progress stage division results to obtain the cross-influence value between the game character level and the game progress. This value is obtained through analysis of the mapping matrix in the database, where the mapping matrix is ​​constructed based on the cross-influence value between level interval i and progress stage j.

[0132] Step 404: Determine the characteristics of the exploration area based on the danger level and resource abundance of the area explored by the game character during the exploration of the game map.

[0133] Furthermore, the game control device acquires the danger level and resource abundance of the area explored by the game character during the exploration of the game map, and determines the characteristics of the exploration area based on the danger level and resource abundance. In one embodiment, the danger level of the exploration area is D. d The resource abundance is D. r Explore the regional features as Feature(D) d D r )=β1D r +β2D d , where β1 and β2 are preset coefficients.

[0134] Step 404: Determine the exploration reward category based on cross-influence values, exploration area characteristics, and the character's career orientation characteristics.

[0135] Furthermore, the game control device acquires the character's class preference characteristics. For example, a warrior class may prefer combat-related rewards such as weapons and armor, while a mage class may need magic-related rewards such as spellbooks and magic crystals.

[0136] Furthermore, the game control device uses cross-influence values, exploration area features, and the character's career orientation features as matching features, and performs mapping matching in the reward category library through specific mapping relationships to obtain the final exploration reward category.

[0137] The embodiments of the present invention can accurately determine the exploration reward category based on the current game character level and current game progress, so that the final game reward issued is consistent with the player's progress in the game, which increases the exploration experience and further improves the player's stickiness to the game.

[0138] In one embodiment, steps 405 to 408 are described as follows:

[0139] Step 405: Decompose the cumulative time in the game according to different game behaviors to obtain the time factor of the game time for each game behavior on the exploration reward.

[0140] Optionally, the game control device decomposes the cumulative time in the game according to different game behaviors, analyzes the impact of the time of each game behavior on the exploration rewards, and obtains the time factor of the game time of each game behavior on the exploration rewards, where game behaviors include combat behavior, gathering behavior, exploration behavior, etc.

[0141] In one embodiment, the cumulative time in the game is T. G The combat time percentage is p b The percentage of collection time is p c The exploration time accounted for p e , and p b +p c +p e =1. Time decomposition impact factor I T for:

[0142]

[0143] Step 406: Based on the current game character attributes, the time factor of exploration rewards for each game action, and the topological structure of the game world state, determine the initial exploration reward potential of the game character in the current state.

[0144] Optionally, the game control device of this embodiment pre-constructs a topological structure of the game world state. This topological structure is constructed using regions within the game world as nodes, and the connections between regions (such as path length and difficulty) as node edges. Therefore, the game control device extracts the attribute features F of the current game character's attributes. G Based on the attribute characteristics of the current game character, the time factor of the game time for each game action on the exploration reward, and the topological structure of the game world state, determine the initial exploration reward potential E of the game character in the current state. w Among them, the initial exploration reward potential E w The calculation formula is Where, N C w represents the number of regions in the game world. ij d represents the node edge from region i to region j. lk Let d represent the shortest path length from node l to node k. When l = k, d lk =1.

[0145] Step 407: Adjust the initial exploration reward potential based on the dynamic events that occur in the game world in real time, and obtain the adjusted reward potential value of the game character in the current state.

[0146] Furthermore, the game control device acquires dynamic events that occur in the game world in real time, such as sudden monster attacks and time-limited treasure appearances.

[0147] Furthermore, the game control device matches the dynamic events that occur in real time with the dynamic event in a preset mapping matching table to obtain the dynamic event influence coefficient. The preset mapping matching table is a correlation table constructed based on the dynamic event and its corresponding influence coefficient.

[0148] Furthermore, the game control device adjusts the initial exploration reward potential based on the dynamic event influence coefficient, resulting in the adjusted reward potential value E of the game character in the current state. f Among them, the revised reward potential value E f The calculation formula is: E f =E w *(1+E k *rand(0,1)), where E k This represents the influence coefficient of a dynamic event, and rand(0,1) represents a random number between 0 and 1.

[0149] Step 408: Map items based on the corrected reward potential value to obtain exploration reward items and reward item levels.

[0150] Furthermore, the game control device maps items based on the corrected reward potential value, analyzes the item characteristic range within which the corrected reward potential value falls. For example, if the corrected reward potential value falls within the first item characteristic range, the exploration reward item is determined to be an exploration reward item that restores health; if it falls within the second item characteristic range, it is determined to be an exploration reward item that enhances attack power; and if it falls within the third item characteristic range, it is determined to be an exploration reward item that enhances defense power. The device also calculates the reward item level R based on the corrected reward potential value. L Among them, the reward item level R L The calculation formula is: This indicates rounding down to the nearest integer.

[0151] This invention accurately determines the exploration reward items and their levels based on the game character's current attributes, cumulative in-game time, and game world status. This ensures that the final game rewards are aligned with the player's progress, enhancing the exploration experience and further increasing player engagement.

[0152] Furthermore, the following describes the 2D game map random exploration reward distribution system provided by the present invention. The 2D game map random exploration reward distribution system described below can be referred to in correspondence with the 2D game map random exploration reward distribution method described above. Optionally, refer to... Figure 2 , Figure 2 This is a schematic diagram of the structure of the 2D game map random exploration reward distribution device provided by the present invention. The 2D game map random exploration reward distribution device includes:

[0153] The trigger point generation module 210 is used to generate potential reward trigger points based on the completion status of the current game task of the game character and the game position of the game character in the game map, which are obtained in real time during the operation of the 2D game.

[0154] Setting module 220 is used to set trigger conditions for each potential reward trigger point;

[0155] The reward pool matching module 230 is used to match the target reward pool in the reward pool set according to the combination of interactive behaviors completed by the game character in the game character's exploration of the game map if the game character arrives at a potential reward trigger point and the game character's interactive behavior meets the trigger conditions.

[0156] The reward information generation module 240 is used to determine the exploration reward category based on the game character's current game character level and current game progress, and to determine the exploration reward items and reward item levels based on the game character's current game character attributes, cumulative in-game time, and game world status.

[0157] The reward distribution module 250 is used to extract the final exploration reward from the target reward pool based on the exploration reward category, exploration reward item, and reward item level, and display the final exploration reward at the potential reward trigger point.

[0158] This invention sets trigger conditions including multiple interaction modes for each potential reward trigger point, greatly enriching the ways players interact with the map and increasing the fun of exploration. On the other hand, the multiple interaction modes and complex judgment mechanism mean that different rewards may be triggered by different interactive behaviors each time a player explores, making it difficult to predict how to obtain rewards, thus increasing the fun of the game and player participation, and therefore increasing player stickiness to the game.

[0159] Please see Figure 3 , Figure 3 An embodiment diagram of an electronic device provided in accordance with the present invention. For example... Figure 3As shown, this embodiment of the invention provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 311, it performs the following steps:

[0160] Based on the real-time acquisition of the game character's current game task completion status and game position on the game map during the 2D game operation, potential reward trigger points are generated.

[0161] Set trigger conditions for each potential reward trigger point; the trigger conditions include completing at least two different interactive behaviors, such as triggering hidden mechanisms, completing a specific path, talking to a specific character in a specific order, and using a specific item to perform an operation at a specific location.

[0162] During the game character's exploration of the game map, if the game character arrives at a potential reward trigger point and the game character's interaction behavior meets the trigger conditions, then the target reward pool will be matched from the reward pool set based on the combination of the game character's completed interaction behaviors; the reward pool set is updated according to the game version.

[0163] The exploration reward category is determined based on the game character's current level and current game progress, and the exploration reward item and reward item level are determined based on the game character's current attributes, cumulative in-game time, and game world status.

[0164] The final exploration reward is drawn from the target reward pool based on the exploration reward category, exploration reward item, and reward item level, and then displayed at the potential reward trigger point.

[0165] Please see Figure 4 , Figure 4 An embodiment diagram of a computer-readable storage medium provided in accordance with an embodiment of the present invention is shown. Figure 4 As shown, this embodiment provides a computer-readable storage medium 400 on which a computer program 311 is stored. When the computer program 311 is executed by a processor, it performs the following steps:

[0166] Based on the real-time acquisition of the game character's current game task completion status and game position on the game map during the 2D game operation, potential reward trigger points are generated.

[0167] Set trigger conditions for each potential reward trigger point; the trigger conditions include completing at least two different interactive behaviors, such as triggering hidden mechanisms, completing a specific path, talking to a specific character in a specific order, and using a specific item to perform an operation at a specific location.

[0168] During the game character's exploration of the game map, if the game character arrives at a potential reward trigger point and the game character's interaction behavior meets the trigger conditions, then the target reward pool will be matched from the reward pool set based on the combination of the game character's completed interaction behaviors; the reward pool set is updated according to the game version.

[0169] The exploration reward category is determined based on the game character's current level and current game progress, and the exploration reward item and reward item level are determined based on the game character's current attributes, cumulative in-game time, and game world status.

[0170] The final exploration reward is drawn from the target reward pool based on the exploration reward category, exploration reward item, and reward item level, and then displayed at the potential reward trigger point.

[0171] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the method for distributing random map exploration rewards in a 2D game provided by the above methods, the method including:

[0172] Based on the real-time acquisition of the game character's current game task completion status and game position on the game map during the 2D game operation, potential reward trigger points are generated.

[0173] Set trigger conditions for each potential reward trigger point; the trigger conditions include completing at least two different interactive behaviors, such as triggering hidden mechanisms, completing a specific path, talking to a specific character in a specific order, and using a specific item to perform an operation at a specific location.

[0174] During the game character's exploration of the game map, if the game character arrives at a potential reward trigger point and the game character's interaction behavior meets the trigger conditions, then the target reward pool will be matched from the reward pool set based on the combination of the game character's completed interaction behaviors; the reward pool set is updated according to the game version.

[0175] The exploration reward category is determined based on the game character's current level and current game progress, and the exploration reward item and reward item level are determined based on the game character's current attributes, cumulative in-game time, and game world status.

[0176] The final exploration reward is drawn from the target reward pool based on the exploration reward category, exploration reward item, and reward item level, and then displayed at the potential reward trigger point.

[0177] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0178] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0179] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for distributing rewards for random map exploration in a 2D game, characterized in that, include: Based on the real-time acquisition of the game character's current game task completion status and game position on the game map during the 2D game operation, potential reward trigger points are generated. Set trigger conditions for each potential reward trigger point; the trigger conditions include completing at least two different interactive behaviors, including triggering hidden mechanisms, completing a specific path, having a conversation with a specific character in a specific order, and using a specific item to perform an operation at a specific location; During the game character's exploration of the game map, if the game character arrives at a potential reward trigger point and the game character's interaction behavior meets the triggering conditions, then the target reward pool is matched in the reward pool set according to the combination of the game character's completed interaction behaviors; the reward pool set is updated according to the game version. The exploration reward category is determined based on the game character's current level and current game progress, and the exploration reward item and reward item level are determined based on the game character's current attributes, cumulative in-game time, and game world status. Based on the exploration reward category, the exploration reward item, and the reward item level, the final exploration reward is drawn from the target reward pool and displayed at the potential reward trigger point; The step of matching the target reward pool from the reward pool set based on the combination of interactive behaviors performed by the game character includes: Based on the behavioral characteristics of the game character when completing each target interactive behavior in the combination of interactive behaviors, the behavioral characteristic value of each target interactive behavior is determined. The behavior combination complexity of the interaction behavior combination is calculated based on the time interval between the target interaction behaviors in the interaction behavior combination and the behavior feature value of each target interaction behavior. Based on the combined complexity of the behaviors, a matching process is performed in the reward pool set to obtain a candidate set for the reward pool. Based on the correlation analysis of the candidate set of the reward pool and the game context when the combination of interactive behaviors occurs, the target reward pool of the combination of interactive behaviors is obtained. The step of performing correlation analysis based on the candidate set of the reward pool and the game context in which the interaction behavior combination occurs to obtain the target reward pool for the interaction behavior combination includes: Based on the current stage of the game, the attribute state of the player character, and the environmental state of the game world when the interaction behavior combination occurs, the correlation between the interaction behavior combination and the game context is determined. Based on the correlation, the candidate set of the reward pool is matched to obtain the final reward pool set; Based on the frequency of occurrence of the interaction behavior combination in the game history and the latest rewards obtained by the game character, the compatibility between the interaction behavior combination and each reward pool in the final reward pool set is determined. Iterate through the fit of each reward pool and determine the reward pool with the largest fit in the final reward pool set as the target reward pool.

2. The method for distributing random map exploration rewards in a 2D game according to claim 1, characterized in that, The process of generating potential reward trigger points based on the real-time acquisition of the game character's current game task completion status and game position on the game map during 2D game operation includes: A correlation strength analysis was performed on the current game task completion status of the game character and the game position of the game character on the game map to obtain the correlation coefficient between task progress and game position; The location difficulty is determined based on the terrain and virtual monster distribution in each area of ​​the game map, and a matching analysis is performed based on the task difficulty level and location difficulty of the current game task to obtain the difficulty matching coefficient. Based on the correlation coefficient, the difficulty matching coefficient, and the location heatmap of the game map, the potential reward trigger points are generated; the location heatmap represents the popularity of each area and is constructed based on the frequency of game characters appearing in different game locations.

3. The method for distributing random map exploration rewards in a 2D game according to claim 2, characterized in that, The generation of potential reward trigger points based on the correlation coefficient, the difficulty matching coefficient, and the location heatmap of the game map includes: Based on the correlation coefficient, the difficulty matching coefficient, and the location heatmap of the game map, the initial probability of each location in the game map becoming a reward trigger point is obtained. The probability of each location becoming a reward trigger point is adjusted based on the current game time and in-game activity frequency of the game character to obtain the final probability of each location becoming a reward trigger point. Iterate through the final probability of each position becoming a reward trigger point, and determine the reward trigger points whose final probability is greater than or equal to a preset probability threshold as the potential reward trigger points.

4. The method for distributing random map exploration rewards in a 2D game according to any one of claims 1 to 3, characterized in that, The method of determining the exploration reward category based on the game character's current level and current game progress includes: Map the current game character level and the current game progress to obtain the level mapping result and the progress stage division result; Based on the level mapping results and the progress stage division results, a cross-influence analysis is performed to obtain the cross-influence value between game character level and game progress. The characteristics of the explored areas are determined based on the degree of danger and the abundance of resources in the areas explored by the game characters during the exploration of the game map; The exploration reward category is determined based on the cross-influence value, the characteristics of the exploration area, and the character's career orientation characteristics.

5. The method for distributing random map exploration rewards in a 2D game according to any one of claims 1 to 3, characterized in that, The process of determining exploration reward items and their levels based on the game character's current attributes, cumulative in-game time, and game world status includes: The cumulative time in the game is broken down according to different game behaviors, and the time factor of the game time for each game behavior on the exploration reward is obtained. Based on the current game character attributes, the time factor of exploration rewards for each game action, and the topological structure of the game world state, the initial exploration reward potential of the game character in the current state is determined; the topological structure is constructed with each region in the game world as a node and the connection relationship between regions as node edges. The initial exploration reward potential is adjusted based on dynamic events that occur in real time in the game world to obtain the adjusted reward potential value of the game character in the current state; Based on the revised reward potential value, the item mapping is performed to obtain the exploration reward item and the reward item level.

6. A device for distributing random map exploration rewards in a 2D game, characterized in that, The method for distributing random map exploration rewards in a 2D game as described in any one of claims 1 to 5 includes: The trigger point generation module is used to generate potential reward trigger points based on the completion status of the game character's current game task and the game character's position on the game map, which are obtained in real time during the operation of the 2D game. The settings module is used to set trigger conditions for each potential reward trigger point; The reward pool matching module is used to match the target reward pool in the reward pool set according to the combination of interactive behaviors completed by the game character in the game character's exploration of the game map if the game character arrives at a potential reward trigger point and the game character's interactive behavior meets the trigger conditions. The reward information generation module is used to determine the exploration reward category based on the game character's current game character level and current game progress, and to determine the exploration reward items and reward item levels based on the game character's current game character attributes, cumulative in-game time, and game world status; The reward distribution module is used to extract the final exploration reward from the target reward pool based on the exploration reward category, the exploration reward item, and the reward item level, and to display the final exploration reward at the potential reward trigger point. The step of matching the target reward pool from the reward pool set based on the combination of interactive behaviors performed by the game character includes: Based on the behavioral characteristics of the game character when completing each target interactive behavior in the combination of interactive behaviors, the behavioral characteristic value of each target interactive behavior is determined. The behavior combination complexity of the interaction behavior combination is calculated based on the time interval between the target interaction behaviors in the interaction behavior combination and the behavior feature value of each target interaction behavior. Based on the combined complexity of the behaviors, a matching process is performed in the reward pool set to obtain a candidate set for the reward pool. Based on the correlation analysis of the candidate set of the reward pool and the game context when the combination of interactive behaviors occurs, the target reward pool of the combination of interactive behaviors is obtained. The step of performing correlation analysis based on the candidate set of the reward pool and the game context in which the interaction behavior combination occurs to obtain the target reward pool for the interaction behavior combination includes: Based on the current stage of the game, the attribute state of the player character, and the environmental state of the game world when the interaction behavior combination occurs, the correlation between the interaction behavior combination and the game context is determined. Based on the correlation, the candidate set of the reward pool is matched to obtain the final reward pool set; Based on the frequency of occurrence of the interaction behavior combination in the game history and the latest rewards obtained by the game character, the compatibility between the interaction behavior combination and each reward pool in the final reward pool set is determined. Iterate through the fit of each reward pool and determine the reward pool with the largest fit in the final reward pool set as the target reward pool.

7. An electronic device, comprising: Memory, used to store computer software programs; A processor for reading and executing the computer software program, characterized in that, when the processor executes the computer software program, it implements the method for distributing random exploration rewards in a 2D game map as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium storing a computer software program, characterized in that, When the computer software program is executed by the processor, it implements the method for distributing random map exploration rewards in a 2D game as described in any one of claims 1 to 5.

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