CN116785727B - A block generation method for a Candy Crush game - Google Patents
A block generation method for a Candy Crush game Download PDFInfo
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- A63F13/60—Generating or modifying game content before or while executing the game program, e.g. authoring tools specially adapted for game development or game-integrated level editor
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Abstract
本发明公开了一种用于消消乐游戏的方块生成方法，首先创建初始预期区域，并在初始预期区域中假设生成8种类型的方块，基于初始预期区域创建的下一级预期区域，采用创建预期区域的方式来模拟玩家计算一次或多次点击之后消消乐游戏的“主游戏区域”的新场景，得到标准化得分，接着分别计算出玩家水平系数和时间系数，综合两者得到生成方块难度系数，引入方块概率修正概率，进而得到方块生成权重，最后方块生成权重最高的方块即为本次生成的新方块的类型；优点是会根据玩家水平和游戏进度分析出玩家需要的游戏难度，并能够基于玩家需要的游戏难度生成符合游戏难度需求的游戏方块，从而控制游戏难度在特定区间内，以改善游戏的公平性和挑战性。The invention discloses a block generation method for a Candy Crush Saga game. First, an initial expected area is created, and 8 types of blocks are assumed to be generated in the initial expected area. A next-level expected area is created based on the initial expected area, and a method of creating the expected area is adopted to simulate a new scene of a "main game area" of the Candy Crush Saga game after a player calculates one or more clicks to obtain a standardized score. Then, the player level coefficient and the time coefficient are calculated respectively, and the two are combined to obtain a block generation difficulty coefficient. A block probability correction probability is introduced to obtain a block generation weight, and finally the block with the highest block generation weight is the type of the new block generated this time. The method has the advantages of analyzing the game difficulty required by the player according to the player level and the game progress, and being able to generate game blocks that meet the game difficulty requirements based on the game difficulty required by the player, thereby controlling the game difficulty within a specific range to improve the fairness and challenge of the game.
Description
Technical Field
The invention relates to a block generation method, in particular to a block generation method for a Xiaojiale game.
Background
The existing main game interface of the Xiaoxiaole game developed based on the elimination playing method is divided into two parts, namely a game part and a functional part. The game part is a region with a width of N square blocks and a height of M+1 square blocks, wherein N is the number of a row of square blocks set by a player, and M=N+2. The game part can be divided into two adjacent areas, and the upper part is a square generation area with the height of 1 square and the width of N squares, and the lower part is a main game area with the height of M squares and the width of N squares. Dividing the game part into N square lattices in the width direction and the height direction of M+1 equally, wherein the N square lattices are divided into (M+1) N square lattices, each square lattice can accommodate one square, and the N square lattices are distributed according to M+1 rows and N columns. According to different orientations of the square grid in the game part, the positions of the square grids are expressed by coordinates, the coordinates of the square grid at the leftmost lower corner are defined as (1, 1), the coordinates of the square grid at the rightmost upper corner are defined as (M+1, N), so that the positions of each square grid can be expressed by coordinates (x, y), x is called the ordinate, the number of rows of the square grid is equal to the abscissa, y is called the abscissa, the number of columns of the square grid is equal to the number of columns of the square grid, the square grid always occupies exactly one square grid in the game part, and unique coordinate values (the position coordinates of the occupied square grid) correspond to the square grid. The coordinates of the square grid in the square generation area are (m+1, y 1), y1=1, 2,..n, the block generation area is used for sequentially generating blocks according to a set time interval, and the generation sequence of the blocks is from left to right. At the start of the game, there are no squares in the square generation area. During the game, a square is generated at (m+1, i) every predetermined time of the game, i=1 if there are no squares in the square generation area, and i=n+1 if there are N squares in the square generation area (N < =n-1). When generating tiles at positions (m+1, n), it means that all the tiles in the tile generation area are generated, at which time all the tiles in the tile generation area fall from the "tile generation area" to the "main game area" simultaneously, wherein if the tiles in the "main game area" are not piled up to the top (i.e., not capped), i.e., no tiles exist in the m+1st row, each tile in the tile generation area moves down to the tile grid which is located in the same column as it, and there is no tile therebetween, and one tile which is furthest away from it and is not occupied by a tile is regenerated according to a predetermined rule, and the process is repeated until x is completed, and if the tiles in the "main game area" are piled up to the top (i.e., capped), i.e., there is a tile in the m+1st row, at which time the game is completed. At the beginning of the game, blocks with a height of N-4 grids and a width of N grids are automatically generated in a main game area. Any square in the main game area, if there is no square in the square grid below it, will drop into the square grid. When there are no tiles in the main game area, the game will still proceed normally, waiting for the tiles in the "tile generation area" to drop. During the game, the player can only operate the square in the 'main game area', and cannot operate the square in the square generation area, and the square in the square generation area cannot respond to the operation of the player before falling into the main game area, and cannot interact with other squares at all. the functional section is located below the "main game area" for displaying game data including a score and a time.
The main playing method of the anti-music-elimination game developed based on the anti-music-elimination method comprises the steps that a player clicks a square in a main game area according to a specific rule preset by the game to eliminate associated squares and score, and a proper square elimination strategy is formulated by reasonably utilizing prop squares so as to pursue higher scores. The user can delete the square by clicking, when the player clicks on the normal square, if there is a square "associated" with the square in the main game area, the square "associated" with the square will be deleted together, otherwise the normal square is not deleted. The definition and nature of the blocks "associated" with each other is as follows:
a. The method is characterized in that 8 types of blocks in a game are respectively A1, A2, A3, A4, A5, A6, A7 and A8, all types of blocks can be expressed by Ai, i=1, 2,3,4,5,6,7,8, A1-A4 types of blocks are four types of common blocks, A1-A4 types of blocks are sequentially red blocks, blue blocks, green blocks and yellow blocks, A5-A8 types of blocks are four types of prop blocks, and A5-A8 types of blocks are sequentially transverse elimination blocks, longitudinal elimination blocks, left-upper right-lower oblique elimination blocks and left-lower right-upper oblique elimination blocks. If the square types of the square A and the square B are the same and are common squares, and the absolute value of the difference of the vertical coordinate values of the square A and the square B is equal to 1, or the absolute value of the difference of the horizontal coordinate values of the square A and the square B is equal to 1, and the vertical coordinate values are equal, the square A and the square B are mutually associated. In addition, each block is "associated" with itself, blocks in the block generation area are not associated with any blocks, and prop blocks are not associated with any blocks.
B. The property "associated" is transitive in that if a blocks are "associated" with B blocks and a blocks are "associated" with C blocks, B blocks are "associated" with C blocks. The association has real-time property, and when the position of any square block in the scene changes, all association relations in the scene are reset.
When a player clicks on a prop box, the prop box will be erased. Different types of prop blocks have different prop effects, and when the prop blocks are erased by clicking operation or erased by clicking operation of other prop blocks, the prop blocks trigger the prop effects of the prop blocks. The prop effect can only affect the squares in the main game area, and has no effect on the squares in the square generation area. The prop effects of the different types of prop blocks are respectively as follows:
a. And (3) transversely eliminating the blocks, namely eliminating all the blocks positioned in the same row.
B. The blocks are eliminated vertically, and all blocks in the same column are eliminated together.
C. And a left-upper-right-lower-diagonal elimination block that eliminates all blocks existing in the diagonal direction if the left-upper-right-lower-diagonal elimination block is in a diagonal direction formed by the connection of the block at the coordinates (N, 1) and the block at the coordinates (1, N), and eliminates all blocks existing in a diagonal direction parallel to the diagonal direction if the left-upper-right-lower-diagonal elimination block is not in a diagonal direction formed by the connection of the block at the coordinates (N, 1) and the block at the coordinates (1, N).
D. And a lower left-right upper-diagonal elimination block that eliminates all blocks existing in the diagonal direction if the lower left-right upper-diagonal elimination block is in a diagonal direction formed by the connection of the block at the coordinates (1, 1) and the block at the coordinates (N, N), and eliminates all blocks existing in a diagonal direction parallel to the diagonal direction if the lower left-right upper-diagonal elimination block is not in a diagonal direction formed by the connection of the block at the coordinates (1, 1) and the block at the coordinates (N, N).
In the above-mentioned game of eliminating music based on eliminating the play development, an important factor influencing the game difficulty is the type of "square generation area" generation square, in order to promote the game experience, the game needs to dynamically adjust the game difficulty for players of different game levels or different game stages of the same player during the game, so as to increase the entertainment and the challenge of the game. However, in the said game of eliminating music developed based on eliminating playing method, the block generation method is that "when a block needs to be generated, the probability of generating a prop block is firstly determined, if the result of determination is true, a random prop block is generated, otherwise a random ordinary block is generated. The probability of generating a prop square is a fixed value. The square generation method can not dynamically adjust and change the game difficulty, and can lead to overlarge randomness of the game, reduce fairness and challenges of the game, and lead to reduced game enthusiasm of players.
Disclosure of Invention
The invention aims to solve the technical problem of providing a block generation method for a vanishing game, which is used for analyzing game difficulty required by a player according to the level of the player and the game progress when different players perform vanishing game developed based on a vanishing play method, and generating game blocks meeting the game difficulty requirement based on the game difficulty required by the player, so that the game difficulty is controlled to be in a specific interval, and the fairness and the challenges of the game are improved.
The invention solves the technical problems by adopting the technical scheme that the square generation method for the vanishing game comprises the steps of marking the width of a game part of the vanishing game as N squares and the height as M+1 squares, forming a region with the height of M+1 squares and the width of N squares by the game part of the vanishing game, wherein M=N+2, the width direction is taken as a column direction, the height direction is taken as a row direction, the rows 1 to M+1 are sequentially taken from bottom to top, the columns 1 to N are sequentially taken from left to right, the square generation region of the vanishing game is positioned in the M+1, the main game region of the vanishing game is positioned in the 1 st to M rows, the square positions of the b row of the vanishing game in the game part of the vanishing game are marked as (a, b), a=1, 2, M+1, b=1, 2, N, and when the vanishing game is carried out, the whole number of the m+1 is generated in the process, and the m+1 is 0, when the whole number of the vanishing game is generated in the following steps:
step (1), assuming that a square block with a type Ai is generated at the position (M+1, y 0), initializing i to ensure that i=1;
Step (2), calculating to obtain the score of the square block with the type of Ai, wherein the specific calculation process is as follows:
S2-1, copying a current game part of a player and naming the current game part as an i type 0 th layer initial expected area, then firstly generating a square block with a type of Ai at (M+1, y 0) of a square block generation area of the i type 0 th layer initial expected area, then enabling all square blocks in the current square block generation area of the i type 0 th layer initial expected area to fall, and in the falling process, if one square block in the current square block generation area of the i type 0 th layer initial expected area cannot fall due to square block capping in a main game area of the i type 0 th layer initial expected area, directly deleting the square block, namely an i type 0 th layer expected area, setting a parameter of the i type 0 th layer expected area, namely a score, and initializing the score to be equal to 0;
s2-2, setting a variable t, initializing t, and enabling t=1;
S2-3, counting the number of the expected areas of the t-1 th layer of the type i, judging whether the number of the expected areas of the t-1 th layer of the type i is larger than 0, if so, continuing to execute the step S2-4, otherwise, acquiring the current value of t, marking t-2 as n, and jumping to the step S2-6 to continue executing the step;
S2-4, respectively performing calculation operation on each i type t-1 layer expected area to obtain an i type t-1 layer expected area corresponding to each i type t-1 layer expected area, wherein the specific process of performing calculation operation on any i type t-1 layer expected area is as follows:
s2-4-1, taking a certain i type t-1 layer expected area which is currently subjected to calculation operation as a current calculation expected area;
S2-4-2, acquiring all solutions of a current calculation expected area, namely counting all data which accord with rules and can eliminate clicking operation of blocks in the current calculation expected area, wherein if the blocks clicked by a plurality of clicking operations are associated with each other, any one of the clicking operations is randomly selected as one solution of the current calculation expected area, other clicking operations are ignored, and if the block clicked by a certain clicking operation is not associated with the block clicked by any other clicking operation, the clicking operation is used as one solution of the current calculation expected area;
S2-4-3, judging whether the number of solutions of the current calculation expected area is larger than 0, if so, continuing to execute the step S2-4-4, otherwise, judging that no solution exists in the current calculation expected area, and ending the calculation operation;
s2-4-4, operating the current calculation expected area by using clicking operation of each solution, wherein the result obtained by operating the current calculation expected area by using clicking operation of each solution is an i-type t-layer expected area corresponding to each solution, and the score of the i-type t-layer expected area corresponding to each solution is equal to the score of the current calculation expected area plus the number of blocks eliminated by clicking operation of the corresponding solution;
S2-5, after the i type t layer expected areas corresponding to all the i type t-1 layer expected areas and scores thereof are obtained, the current value of t is added with 1 and the value of t is updated, and the step S2-3 is returned;
S2-6, calculating the average of the scores of all i types of j-th layer expected areas, and recording the average as S i,j, wherein j=0, 1..n, and calculating the score of a square block with the type Ai by using the formula (1) as C i:
S2-7, judging whether the current value of i is equal to 8, if not, firstly adopting the sum of the current value of i and 1 to update the value of i, then returning to the step (2) to calculate the score of the square block of the next type, and if so, entering the step (3);
Taking the maximum value of C 1 to C 8, recording the maximum value as Cmax, and calculating a normalized score SC k of the square with the type of Ak by adopting the formula (2):
Wherein k=1, 2, 8;
step (4), the player level coefficient is marked as D 1, and D 1 is obtained by calculation according to the formula (3):
D1=L/25 (3)
in the formula (3), L is the operation level of a player, and the operation level of the player is directly generated after the player logs in the Xiaoque game;
Step (5), setting a time coefficient D 2, calculating to obtain the accumulated time length T of the current game of the player, wherein the unit is seconds(s), wherein T is equal to the time interval between the current time (i.e., the time when a new square needs to be generated at the (m+1, y 0) position in the square generation area) and the time when the player starts the present vanishing game;
If T is greater than 0 and less than 120s, the time coefficient D 2 = [ T/30] +1, [ ] represents a downward rounding, and if T > = 120s, the time coefficient D 2 is equal to 4;
Setting the difficulty coefficient of the current generation block as D, wherein D=D 1+D2, and calculating the difficulty coefficient D to obtain the prop block generation target probability AW=0.12-0.008D;
step (7), obtaining the number and types of blocks generated by a block generation area of the vanishing game from the game starting time to the current time of the player, marking the total number of the blocks generated by the block generation area of the vanishing game as BN, marking the total number of prop blocks generated by the block generation area of the vanishing game as IN, and calculating to obtain the actual frequency TW=IN/BN of block generation;
step (8), calculating a probability correction coefficient W k of a square block with the type of Ak:
For a square of type Ah, h=1, 2,3,4, w h =1+ (TW-AW)/AW;
for a square of type Am, m=5, 6,7,8, w m =1+ (AW-TW)/AW;
Step (9), calculating by using formula (4) to obtain a generation weight S k of a square block with the type of Ak as follows:
Sk＝(SCk)0.1*(3.5-D)*(SCk+1)*Wk (4)
wherein, is the multiplication operation symbol;
step (10), obtaining the maximum value in S 1 to S 8, and assuming that the obtained maximum value is S r, wherein r is an integer greater than or equal to 1 and less than or equal to 8, and Ar is the type of square block to be generated;
and (11) generating a square with the type Ar at the position (M+1, y 0) of the square generation area of the XiaoLe game.
Compared with the prior art, the method has the advantages that when a new square is needed to be generated at a certain position in the square generation area of the Xiaoque game, the current game part of a player is duplicated, an initial expected area is created, and squares with the types of Ai are assumed to be generated at the same coordinates in the initial expected area, i.e. the possible values of i are 1,2 and 3..8, the squares in the square generation area in the initial expected area are dropped to obtain an i type 0 expected area, i.e. the i type 0 expected area is the created expected area, a new scene of the main game area of the Xiaoque game after one or more clicks are calculated by simulating the player by adopting a mode of creating the expected area, different solutions are considered to obtain a better operation strategy, as different players also have different thought depths, the high-level players tend to calculate clicks with more numbers, i.e. the thought depths are deeper, the expected scene with higher number of layers can be calculated, the subsequent iteration is performed from t=1, the i type 0 expected area is obtained, i type 0 expected area is calculated by calculating the corresponding type i type 0 expected area, i type 0 expected area is calculated by calculating the expected layer i type i, and all types are calculated by carrying out iteration, i type j is calculated, i expected area is calculated after all types of expected area is calculated, i expected layer type i expected area is calculated, i is calculated by calculating type t expected layer type 1 expected area is calculated, i is calculated by calculating type j is calculated, and j is calculatedObtaining a score value of a j-th layer of an i type, summing the score values of all layers to obtain a score value C i of a square with a generation type Ai, wherein the score value represents a player expected score after a square with the generation type Ai is considered, the thinking difficulty is larger when the thinking depth is deeper, so that the influence factor of an expected area with the higher layer is smaller, the influence of the score on the player expected score is also smaller, the scores C k of the 8 types of squares are subjected to standardization processing to obtain standardized scores SC k, the possible values of k are 1,2, 3..8, the standardized score of each type of square represents the relative value of the player expected score of a game scene after the square with the generation type Ai is generated, the higher the value represents the higher expected score of the player after the square with the generation type Ai is generated, namely the relative lower of the game scene after the square with the generation type Ai is generated, the player operation level and the player game accumulation time coefficient are respectively calculated, the coefficient of level difficulty and the coefficient of the time coefficient of the player level difficulty are comprehensively measured, and the coefficient of the difficulty is higher when the coefficient of the square is used for generating the square with the higher level of difficulty is required to be generated, and the coefficient of the expected difficulty is higher; when the difficulty coefficient of the generated square is high, the square generation weight is inversely proportional to the standardized score, namely, the square type with lower expected score generates higher weight, a game scene with higher difficulty is created for a player, the standardized score value of 8 types of square is multiplied by the respective square probability correction coefficient, the square generation weight is obtained according to a formula, in most cases, generating the prop square can enable a player to eliminate more square blocks, so that the square standardization score of the prop type square is always higher than that of the square standardization score of the ordinary type square, if no square probability correction causes the generation frequency of the prop square to be higher, the game difficulty is too low, and therefore the square probability correction coefficient is introduced to balance the square generation weight of the ordinary square and the prop square, when the generation frequency of the prop square is too high, the generation weight of the prop square is reduced, otherwise, the generation weight of the prop square is increased, the generation frequency of the prop square is controlled within a certain interval, finally, the square with the highest generation weight is the type of the new square generated at this time according to the size sorting of the square generation weight.
Detailed Description
The present invention is described in further detail below with reference to examples.
The embodiment of the block generation method for the vanishing game is characterized in that the width of a game part of the vanishing game is recorded as N blocks, the height is recorded as M+1 blocks, the game part of the vanishing game forms a region with the height of M+1 blocks and the width of N blocks, the M=N+2 takes the width direction as a column direction, the height direction as a row direction, the row 1 to the row M+1 is sequentially from bottom to top, the column 1 to the column N is sequentially from left to right, a block generation region of the vanishing game is positioned in the row M+1, a main game region of the vanishing game is positioned in the row 1 to the row M, the block positions of the a row b in the game part of the vanishing game are recorded as (a, b), a=1, 2, m+1, b=1, 2, and N, and in the process of the vanishing game, when the position (M+1, y0) of the block generation region of the vanishing game is required to be generated by a player, the new generation region of the vanishing game is 0, wherein the new generation region is 0 is generated in the following integer or less than or equal to the following steps:
step (1), assuming that a square block with a type Ai is generated at the position (M+1, y 0), initializing i to ensure that i=1;
Step (2), calculating to obtain the score of the square block with the type of Ai, wherein the specific calculation process is as follows:
S2-1, copying a current game part of a player and naming the current game part as an i type 0 th layer initial expected area, then firstly generating a square block with a type of Ai at (M+1, y 0) of a square block generation area of the i type 0 th layer initial expected area, then enabling all square blocks in the current square block generation area of the i type 0 th layer initial expected area to fall, and in the falling process, if one square block in the current square block generation area of the i type 0 th layer initial expected area cannot fall due to square block capping in a main game area of the i type 0 th layer initial expected area, directly deleting the square block, namely an i type 0 th layer expected area, setting a parameter of the i type 0 th layer expected area, namely a score, and initializing the score to be equal to 0;
s2-2, setting a variable t, initializing t, and enabling t=1;
S2-3, counting the number of the expected areas of the t-1 th layer of the type i, judging whether the number of the expected areas of the t-1 th layer of the type i is larger than 0, if so, continuing to execute the step S2-4, otherwise, acquiring the current value of t, marking t-2 as n, and jumping to the step S2-6 to continue executing the step;
S2-4, respectively performing calculation operation on each i type t-1 layer expected area to obtain an i type t-1 layer expected area corresponding to each i type t-1 layer expected area, wherein the specific process of performing calculation operation on any i type t-1 layer expected area is as follows:
s2-4-1, taking a certain i type t-1 layer expected area which is currently subjected to calculation operation as a current calculation expected area;
S2-4-2, acquiring all solutions of a current calculation expected area, namely counting all data which accord with rules and can eliminate clicking operation of blocks in the current calculation expected area, wherein if the blocks clicked by a plurality of clicking operations are associated with each other, any one of the clicking operations is randomly selected as one solution of the current calculation expected area, other clicking operations are ignored, and if the block clicked by a certain clicking operation is not associated with the block clicked by any other clicking operation, the clicking operation is used as one solution of the current calculation expected area;
S2-4-3, judging whether the number of solutions of the current calculation expected area is larger than 0, if so, continuing to execute the step S2-4-4, otherwise, judging that no solution exists in the current calculation expected area, and ending the calculation operation;
s2-4-4, operating the current calculation expected area by using clicking operation of each solution, wherein the result obtained by operating the current calculation expected area by using clicking operation of each solution is an i-type t-layer expected area corresponding to each solution, and the score of the i-type t-layer expected area corresponding to each solution is equal to the score of the current calculation expected area plus the number of blocks eliminated by clicking operation of the corresponding solution;
S2-5, after the i type t layer expected areas corresponding to all the i type t-1 layer expected areas and scores thereof are obtained, the current value of t is added with 1 and the value of t is updated, and the step S2-3 is returned;
S2-6, calculating the average of the scores of all i types of j-th layer expected areas, and recording the average as S i,j, wherein j=0, 1..n, and calculating the score of a square block with the type Ai by using the formula (1) as C i:
S2-7, judging whether the current value of i is equal to 8, if not, firstly adopting the sum of the current value of i and 1 to update the value of i, then returning to the step (2) to calculate the score of the square block of the next type, and if so, entering the step (3);
Taking the maximum value of C 1 to C 8, recording the maximum value as Cmax, and calculating a normalized score SC k of the square with the type of Ak by adopting the formula (2):
Wherein k=1, 2, 8;
step (4), the player level coefficient is marked as D 1, and D 1 is obtained by calculation according to the formula (3):
D1=L/25 (3)
in the formula (3), L is the operation level of a player, and the operation level of the player is directly generated after the player logs in the Xiaoque game;
Step (5), setting a time coefficient D 2, calculating to obtain the accumulated time length T of the current game of the player, wherein the unit is seconds(s), wherein T is equal to the time interval between the current time (i.e., the time when a new square needs to be generated at the (m+1, y 0) position in the square generation area) and the time when the player starts the present vanishing game;
If T is greater than 0 and less than 120s, the time coefficient D 2 = [ T/30] +1, [ ] represents a downward rounding, and if T > = 120s, the time coefficient D 2 is equal to 4;
Setting the difficulty coefficient of the current generation block as D, wherein D=D 1+D2, and calculating the difficulty coefficient D to obtain the prop block generation target probability AW=0.12-0.008D;
step (7), obtaining the number and types of blocks generated by a block generation area of the vanishing game from the game starting time to the current time of the player, marking the total number of the blocks generated by the block generation area of the vanishing game as BN, marking the total number of prop blocks generated by the block generation area of the vanishing game as IN, and calculating to obtain the actual frequency TW=IN/BN of block generation;
step (8), calculating a probability correction coefficient W k of a square block with the type of Ak:
For a square of type Ah, h=1, 2,3,4, w h =1+ (TW-AW)/AW;
for a square of type Am, m=5, 6,7,8, w m =1+ (AW-TW)/AW;
Wherein, the square blocks of A1 to A4 are four types of common square blocks, the square blocks of A1 to A4 are red square blocks, blue square blocks, green square blocks and yellow square blocks in sequence, the square blocks of A5 to A8 are four types of prop square blocks, and the square blocks of A5 to A8 are horizontal elimination square blocks, longitudinal elimination square blocks, left upper right lower-oblique elimination square blocks and left lower right upper-oblique elimination square blocks in sequence;
Step (9), calculating by using formula (4) to obtain a generation weight S k of a square block with the type of Ak as follows:
Sk＝(SCk)0.1*(3.5-D)*(SCk+1)*Wk (4)
wherein, is the multiplication operation symbol;
step (10), obtaining the maximum value in S 1 to S 8, and assuming that the obtained maximum value is S r, wherein r is an integer greater than or equal to 1 and less than or equal to 8, and Ar is the type of square block to be generated;
and (11) generating a square with the type Ar at the position (M+1, y 0) of the square generation area of the XiaoLe game.
In the square generation method for the Xiaoque game, when a new square is required to be generated at a certain position in a square generation area of the Xiaoque game, a current game part of a player is duplicated, an initial expected area is created, squares with a type of Ai are supposed to be generated at the same coordinates in the initial expected area, the squares in the square generation area in the initial expected area drop to obtain an i type 0 layer expected area, the i type 0 layer expected area is a created expected area, the invention simulates a new scene of a main game area of the Xiaoque game after one or more clicks are performed by a player by adopting a mode of creating the expected area, thinking is performed by different solutions to obtain a better operation strategy, because the thinking depth of different players is also different, the number of clicks calculated by a high level player is often more, namely, the thinking depth is deeper, the expected scene can be calculated, iteration is set up from t=1, the i type 0 layer expected area is obtained, the i type 0 layer expected area is calculated by calculating the corresponding type t-1 layer expected area, the number of layers is calculated by calculating the corresponding type i layer expected area, the type j is calculated, the value is calculated by multiplying all the expected layer types are calculated, and the expected area is calculated by the expected layer value j is calculated by the iteration factor, the i layer type 1 is calculated after all the expected layer is calculated, the expected value is calculated by the expected layer j is calculatedObtaining a score of an i-type jth layer expected region, summing the scores of all the layer expected regions to obtain a score value C i for generating a square of type Ai, the score value representing a player expected score after simulating a block elimination strategy of a player after generating a square of type Ai, the deeper the thinking depth, the greater the thinking difficulty, and therefore the smaller the expected region influence factor of the higher the number of layers, the smaller the influence of the score on the player expected score, the score C k of each of 8 types of squares is normalized to obtain a normalized score SC k, the value of k is 1,2, 3..8, the normalized score of each type of square represents the relative value of the player expected score of a game scene of a "main game region" of a post-consumer-game of the type of square, the higher the value of the coefficient is, the higher the expected score can be, namely the relative difficulty of the game scene after the type of square is generated is lower, the operation level of the player and the accumulated time of the game of the player are led in, the player level coefficient and the time coefficient are calculated respectively, the coefficient of difficulty of the generated square is obtained by integrating the two coefficients, the coefficient of difficulty is used for measuring the level of difficulty required by the generated square, when the coefficient of difficulty of the generated square is low, the square generation weight is in direct proportion to the standardized score of the square, namely the higher the expected score is, the higher the square type generation weight is, and the game difficulty is low; when the difficulty coefficient of the generated square is high, the square generation weight is inversely proportional to the standardized score, namely the square type with lower expected score generates higher weight, a game scene with higher difficulty is created for a player, the standardized score value of 8 types of square is multiplied by the respective square probability correction coefficient respectively, the square generation weight is obtained according to a formula, in most cases, the player can eliminate more blocks by generating the prop blocks, so that the block standardization score of the prop type blocks is always higher than that of the ordinary type blocks, if no square probability correction is adopted, the generation frequency of the prop blocks is higher, the difficulty of games is excessively low, therefore, the block probability correction coefficient is introduced for balancing the block generation weights of the ordinary blocks and the prop blocks, the generation weight of the prop blocks is reduced when the generation frequency of the prop blocks is excessively high, otherwise, the generation weight of the prop blocks is increased, the generation frequency of the prop blocks is controlled within a certain interval, finally, the block types with the highest generation weights are the types of new blocks generated at this time according to the size sequence of the block generation weights.
The square generation method for the Xiaoque game analyzes the influence of the square of different types on the elimination difficulty and complexity degree of the main game area of the Xiaoque game of the current player, analyzes the currently required game difficulty interval by controlling the generated square type in combination with the player level and the game progress time, generates the square of the proper difficulty corresponding type, reduces the adverse influence of the square generation randomness on the game experience of the player, improves the fairness and the challenge of the game, and can improve the game enthusiasm of the player.
Claims (1)
1. The method for generating the square blocks for the vanishing game comprises the steps of marking the width of a game part of the vanishing game as N square blocks, marking the height as M+1 square blocks, forming a region with the height of M+1 square blocks and the width of N square blocks by the game part of the vanishing game, wherein M=N+2, the width direction is taken as a column direction, the height direction is taken as a row direction, the rows 1 to M+1 are sequentially from bottom to top, the columns 1 to N are sequentially from left to right, the 'square block generation region' of the vanishing game is positioned in the M+1, the 'main game region' of the vanishing game is positioned in the M+1 row, and the square block positions positioned in the b column of the a row in the game part of the vanishing game are marked as (a, b), a=1, 2, m+1, b=1, 2, and N; the method is characterized in that when a new square needs to be generated at the position (M+1, y 0) of the square generation area of the Xiaoque game in the process that a player plays the Xiaoque game, wherein y0 is an integer which is more than or equal to 1 and less than or equal to N, the specific generation method comprises the following steps:
step (1), assuming that a square block with a type Ai is generated at the position (M+1, y 0), initializing i to ensure that i=1;
Step (2), calculating to obtain the score of the square block with the type of Ai, wherein the specific calculation process is as follows:
S2-1, copying a current game part of a player and naming the current game part as an i type 0 th layer initial expected area, then firstly generating a square block with a type of Ai at (M+1, y 0) of a square block generation area of the i type 0 th layer initial expected area, then enabling all square blocks in the current square block generation area of the i type 0 th layer initial expected area to fall, and in the falling process, if one square block in the current square block generation area of the i type 0 th layer initial expected area cannot fall due to square block capping in a main game area of the i type 0 th layer initial expected area, directly deleting the square block, namely an i type 0 th layer expected area, setting a parameter of the i type 0 th layer expected area, namely a score, and initializing the score to be equal to 0;
s2-2, setting a variable t, initializing t, and enabling t=1;
S2-3, counting the number of the expected areas of the t-1 th layer of the type i, judging whether the number of the expected areas of the t-1 th layer of the type i is larger than 0, if so, continuing to execute the step S2-4, otherwise, acquiring the current value of t, marking t-2 as n, and jumping to the step S2-6 to continue executing the step;
S2-4, respectively performing calculation operation on each i type t-1 layer expected area to obtain an i type t-1 layer expected area corresponding to each i type t-1 layer expected area, wherein the specific process of performing calculation operation on any i type t-1 layer expected area is as follows:
s2-4-1, taking a certain i type t-1 layer expected area which is currently subjected to calculation operation as a current calculation expected area;
S2-4-2, acquiring all solutions of a current calculation expected area, namely counting all data which accord with rules and can eliminate clicking operation of blocks in the current calculation expected area, wherein if the blocks clicked by a plurality of clicking operations are associated with each other, any one of the clicking operations is randomly selected as one solution of the current calculation expected area, other clicking operations are ignored, and if the block clicked by a certain clicking operation is not associated with the block clicked by any other clicking operation, the clicking operation is used as one solution of the current calculation expected area;
S2-4-3, judging whether the number of solutions of the current calculation expected area is larger than 0, if so, continuing to execute the step S2-4-4, otherwise, judging that no solution exists in the current calculation expected area, and ending the calculation operation;
s2-4-4, operating the current calculation expected area by using clicking operation of each solution, wherein the result obtained by operating the current calculation expected area by using clicking operation of each solution is an i-type t-layer expected area corresponding to each solution, and the score of the i-type t-layer expected area corresponding to each solution is equal to the score of the current calculation expected area plus the number of blocks eliminated by clicking operation of the corresponding solution;
S2-5, after the i type t layer expected areas corresponding to all the i type t-1 layer expected areas and scores thereof are obtained, the current value of t is added with 1 and the value of t is updated, and the step S2-3 is returned;
S2-6, calculating the average of the scores of all i types of j-th layer expected areas, and recording the average as S i,j, wherein j=0, 1..n, and calculating the score of a square block with the type Ai by using the formula (1) as C i:
S2-7, judging whether the current value of i is equal to 8, if not, firstly adopting the sum of the current value of i and 1 to update the value of i, then returning to the step (2) to calculate the score of the square block of the next type, and if so, entering the step (3);
Taking the maximum value of C 1 to C 8, recording the maximum value as Cmax, and calculating a normalized score SC k of the square with the type of Ak by adopting the formula (2):
Wherein k=1, 2, 8;
step (4), the player level coefficient is marked as D 1, and D 1 is obtained by calculation according to the formula (3):
D1=L/25 (3)
in the formula (3), L is the operation level of a player, and the operation level of the player is directly generated after the player logs in the Xiaoque game;
Step (5), setting a time coefficient D 2, calculating to obtain the accumulated time length T of the current game of the player, wherein the unit is seconds(s), wherein T is equal to the time interval between the current time, i.e., the time at which a new tile needs to be generated at the (M+1, y 0) position in the tile generation area, and the time at which the player starts the present xiaole game;
If T is greater than 0 and less than 120s, the time coefficient D 2 = [ T/30] +1, [ ] represents a downward rounding, and if T > = 120s, the time coefficient D 2 is equal to 4;
Setting the difficulty coefficient of the current generation block as D, wherein D=D 1+D2, and calculating the difficulty coefficient D to obtain the prop block generation target probability AW=0.12-0.008D;
step (7), obtaining the number and types of blocks generated by a block generation area of the vanishing game from the game starting time to the current time of the player, marking the total number of the blocks generated by the block generation area of the vanishing game as BN, marking the total number of prop blocks generated by the block generation area of the vanishing game as IN, and calculating to obtain the actual frequency TW=IN/BN of block generation;
step (8), calculating a probability correction coefficient W k of a square block with the type of Ak:
For a square of type Ah, h=1, 2,3,4, w h =1+ (TW-AW)/AW;
for a square of type Am, m=5, 6,7,8, w m =1+ (AW-TW)/AW;
Step (9), calculating by using formula (4) to obtain a generation weight S k of a square block with the type of Ak as follows:
Sk＝(SCk)0.1*(3.5-D)*(SCk+1)*Wk (4)
wherein, is the multiplication operation symbol;
step (10), obtaining the maximum value in S 1 to S 8, and assuming that the obtained maximum value is S r, wherein r is an integer greater than or equal to 1 and less than or equal to 8, and Ar is the type of square block to be generated;
and (11) generating a square with the type Ar at the position (M+1, y 0) of the square generation area of the XiaoLe game.
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