CN112562037A

CN112562037A - Virtual map generation method and device, electronic equipment and readable storage medium

Info

Publication number: CN112562037A
Application number: CN202011497994.4A
Authority: CN
Inventors: 陈坤龙
Original assignee: Bigo Technology Pte Ltd
Current assignee: Bigo Technology Pte Ltd
Priority date: 2020-12-17
Filing date: 2020-12-17
Publication date: 2021-03-26

Abstract

The application discloses a virtual map generation method, a virtual map generation device, virtual map generation equipment and a readable storage medium, and belongs to the technical field of the Internet. The method comprises the following steps: obtaining evaluation data of the initial virtual map, determining a target configuration scheme corresponding to the initial configuration scheme according to the evaluation data and the initial configuration scheme, generating the target virtual map by adopting the target configuration scheme, replacing the initial virtual map by adopting the target virtual map, repeatedly executing the process of generating the target virtual map until a set finishing condition is reached, and taking the initial virtual map of which the evaluation data accords with the evaluation condition as a new virtual map. In the process of generating the virtual map, the configuration of map elements is adjusted according to the evaluation data of the virtual map to generate a new virtual map, so that the layout of the generated virtual map is more reasonable, and more virtual maps with unreasonable layouts are avoided.

Description

Virtual map generation method and device, electronic equipment and readable storage medium

Technical Field

The invention belongs to the technical field of internet, and particularly relates to a virtual map generation method, a virtual map generation device, electronic equipment and a readable storage medium.

Background

With the development of internet technology, applications based on virtual scenes, such as virtual shopping, virtual games, virtual exhibitions, and the like, are increasing. The construction of the virtual scene requires a virtual map, and in some cases, the virtual scene needs to be changed continuously, so that different virtual maps need to be set for each virtual scene.

In the prior art, in order to generate a large number of virtual maps which are different from each other, map elements in the virtual maps are randomly combined according to a certain rule to generate different virtual maps. The virtual maps are generated in a random combination mode, although a large number of virtual maps can be generated, in the generation process of the virtual maps, the randomness is high, and the number of virtual maps which are unreasonably arranged is large.

Disclosure of Invention

In view of this, the invention provides a virtual map generation method, a virtual map generation device, an electronic device and a readable storage medium, which solve the problem of a large number of virtual maps with unreasonable layout in the virtual map generation process to a certain extent.

In order to solve the technical problem, the present application is implemented as follows:

in a first aspect, an embodiment of the present application provides a virtual map generation method, where the method includes:

obtaining evaluation data of an initial virtual map; the evaluation data is determined according to an initial configuration scheme of at least one map element in the initial virtual map;

determining a target configuration scheme corresponding to the initial configuration scheme according to the evaluation data and the initial configuration scheme;

generating a target virtual map by adopting the target configuration scheme;

replacing the initial virtual map with the target virtual map, and repeatedly executing the process of generating the target virtual map until a set ending condition is reached;

and taking the initial virtual map with the evaluation data meeting the evaluation conditions as a new virtual map.

In a second aspect, an embodiment of the present application provides a virtual map generation apparatus, including:

generating a target virtual map by adopting the target configuration scheme;

In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instructions stored on the memory and executable on the processor, and when executed by the processor, the program or instructions implement the steps of the method according to the first aspect.

In a fourth aspect, embodiments of the present application provide a readable storage medium, on which a program or instructions are stored, which when executed by a processor implement the steps of the method according to the first aspect.

In a fifth aspect, an embodiment of the present application provides a chip, where the chip includes a processor and a communication interface, where the communication interface is coupled to the processor, and the processor is configured to execute a program or instructions to implement the method according to the first aspect.

In the embodiment of the application, the electronic device acquires evaluation data of an initial virtual map, determines a target configuration scheme corresponding to the initial configuration scheme according to the evaluation data and the initial configuration scheme, generates a target virtual map by using the target configuration scheme, replaces the initial virtual map by using the target virtual map, repeatedly executes a process of generating the target virtual map until a set end condition is reached, and takes the initial virtual map of which the evaluation data meets the evaluation condition as a new virtual map. In the process of generating the virtual map, the configuration of map elements is adjusted according to the evaluation data of the virtual map to generate a new virtual map, so that the layout of the new virtual map can be more reasonable, and more virtual maps with unreasonable layouts can be avoided.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

fig. 1 is a flowchart illustrating steps of a virtual map generation method according to an embodiment of the present disclosure;

fig. 2 is a schematic structural diagram of a virtual map provided in an embodiment of the present application;

fig. 3 is a schematic diagram of bayesian optimization provided in an embodiment of the present application;

FIG. 4 is a schematic diagram of an optimization process provided by an embodiment of the present application;

FIG. 5 is a flowchart illustrating steps of another virtual map generation method according to an embodiment of the present disclosure;

fig. 6 is a block diagram of a virtual map generation apparatus according to an embodiment of the present application;

fig. 7 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.

Detailed Description

Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

Fig. 1 is a flowchart of steps of a virtual map generation method provided in an embodiment of the present application, and as shown in fig. 1, the method may include:

and 101, acquiring evaluation data of the initial virtual map.

The evaluation data is determined according to an initial configuration scheme of at least one map element in the initial virtual map, and the evaluation data is used for measuring the rationality of the initial virtual map.

In this embodiment, the virtual map generation method may be executed by an electronic device such as a personal computer or a server, where the initial virtual map is a template used for generating a target virtual map, and the initial virtual map includes a map element and an initial configuration scheme of the map element. The electronic device may adjust an initial configuration scheme of at least one map element to obtain a target virtual map corresponding to the initial virtual map.

Illustratively, as shown in fig. 2, fig. 2 is a schematic structural diagram of a virtual map provided in an embodiment of the present application, where the virtual map shown in fig. 2 is a virtual map for a virtual game, the initial virtual map includes a map element grid, a plurality of grids are arranged in the initial virtual map in order from small to large according to the number of the grids, and the plurality of grids may represent G ═ { G ═ as follows₁、G₂、G₃、G₄.........G_NN are positive integers, the subscript of each grid indicating the position of the grid in the initial virtual map, e.g. G₂Representing the second grid in the initial virtual map, G_NRepresenting the nth, i.e., last, grid in the initial virtual map.

The user may set a corresponding type of map element in the initial virtual map according to the game rules. For example, the virtual game includes a character a and a character B, and in the game rule, the character a and the character B are located in the first grid G in the initial virtual map at the start of the game₁When the user throws the dice once, the user can throw any one of the points from 1 to 6, and the probability of the six points is the same. After obtaining the points of the dice, the user can select one of the characters to advance along the direction shown by the arrow 201 by the grid of the corresponding points, when any one of the character a and the character B reaches the last grid in the initial virtual map, namely the Nth grid G_NWhen this happens, a game is over. The user can set a certain number of primary reward organs in the initial virtual map, the primary reward organs are map elements, virtual rewards are set for each primary reward organ respectively, and the virtual rewards can be a certain number of virtual currencies. Example (b)For example, a first reward authority may be set to G₁₀The second reward organ is G₈₀And a first reward organ G is arranged₁₀The corresponding virtual reward is 10 virtual currencies, and a second reward organ G is set₈₀The corresponding virtual awards are 15 virtual currencies, and the initial arrangement schemes of the first and second awarding organs can be respectively represented by (V1-10, L1-10) and (V2-80, L2-15). In the initial configuration of the first awarding authority, V1-10 indicates the grid G₁₀L1 ═ 10 denotes 10 virtual currencies; in the initial configuration of the second prize authority, V2-80 represents the grid G₈₀And L2 ═ 15 indicates 15 virtual currencies. At the same time, the last cell G may be set_NThe initial configuration scheme of the secondary rewarding organ is R virtual currencies, and when two characters reach the last grid G simultaneously_NIn time, the user can get R virtual currencies.

Similarly, the user may set a jump mechanism in the initial virtual map, where the jump mechanism is a map element, and the jump mechanism includes a start grid and a target grid, and when the character a or the character B advances to the start grid, the jump mechanism may directly jump to the target grid to increase the advancing speed of the character. For example, the 20 th cell may be set as the start cell of the first skip organ, the 25 th cell as the target cell of the first skip organ, and the 40 th cell as the start cell of the second skip organ, the 48 th cell as the target cell of the second skip organ. The initial configuration schemes of the first and second hopping mechanisms can be represented by (S1-20, E1-25) and (S2-40, E2-48), respectively. In the initial configuration of the first jump mechanism, S1 ═ 20 indicates that the starting grid is G₂₀E1 ═ 25 denotes that the target cell is G₂₅(ii) a In the initial configuration of the second jump mechanism, S2-40 indicates that the starting grid is G₄₀E2 ═ 48 denotes that the target cell is G₄₈。

During the game, the amount of virtual money used by the user to roll the dice once can be represented by C, the cost of each game is C x T, T is the number of times the user rolls the dice, all the virtual money obtained by the user in each game is income, and the income is represented by S.

In practical applications, the initial virtual map may also be other types of virtual maps, for example, a virtual map in virtual shopping, a virtual map in virtual exhibition, or other types of map elements may also be included in the initial virtual map, rules of a virtual game, and a setting method of the initial configuration scheme may be set according to requirements, which is not limited in this embodiment.

In one embodiment, in the process of generating the target virtual map, the electronic device may first acquire evaluation data of the initial virtual map to adjust an initial configuration scheme of the map elements according to the evaluation data.

Illustratively, step 101 may be implemented as follows:

and determining evaluation data according to the initial configuration scheme of the target map element.

In this embodiment, the electronic device may directly evaluate the rationality of the initial virtual map according to the initial configuration scheme of the map element, so as to obtain evaluation data of the initial virtual map. For example, the jump length of the jump authority may be used as an index for measuring reasonableness, the target map elements may include the first jump authority and the second jump authority in the above embodiments, and the evaluation data of the initial virtual map may be calculated by the following method:

where Y1 is evaluation data, "abs (S1-E1)" represents S1 minus the absolute value of E1, and when the difference between the starting cell and the target cell in the initial arrangement scheme of the first jumping authority is greater than or equal to 8 and the difference between the starting cell and the target cell in the initial arrangement scheme of the second jumping authority is greater than or equal to 8, the evaluation data Y1 of the initial virtual map is positive 20; in contrast, when the difference between the start grid and the target grid of any one jump mechanism is less than 8, the evaluation data Y1 of the initial virtual map is minus 20.

For another example, the difference between the primary and secondary reward organs may be used as an index for measuring the reasonability of the initial virtual map, the target map elements may include the first reward organ, the second reward organ and the secondary reward organ in the above embodiments, and the evaluation data of the initial virtual map may be calculated by the following processing method:

wherein, Y2 is evaluation data, mean (L1+ L2) is the average value of L1 and L2, namely the average reward amount of the primary reward organ, and when the ratio of the reward amount of the secondary reward organ to the average reward amount is greater than or equal to 2, the evaluation data Y2 is positive 20; in contrast, the evaluation data Y2 is minus 10.

In practical application, the evaluation data is determined according to the initial configuration scheme of the target map elements, so that the evaluation data of the initial virtual map can be determined simply and quickly, and the map generation efficiency is improved. The reasonability of the initial virtual map can also be measured by other indexes, and the specific calculation method of the evaluation data can be specifically set according to map elements, which is not limited in this embodiment.

And 102, determining a target configuration scheme corresponding to the initial configuration scheme according to the evaluation data and the initial configuration scheme.

In an embodiment, after determining the evaluation data of the initial virtual map and the initial configuration scheme of the map element, the initial configuration scheme may be optimized according to the evaluation data, so as to obtain a target configuration scheme corresponding to the initial configuration scheme. For example, the initial configuration scheme may be optimized by using an optimization algorithm according to the evaluation data and the initial configuration scheme, the optimization algorithm may select a Bayesian Optimization Algorithm (BOA), the Bayesian optimization algorithm includes a Gaussian Process (GP) and a parameter selection Process, the electronic device may first determine a selection range corresponding to the initial configuration scheme, that is, a selection range of the target configuration scheme, and then may sample within the selection range by using an acquisition function (acquisition function), so as to obtain the target configuration scheme.

Specifically, an objective function f (x) related to the evaluation data and the initial configuration scheme may be defined first, and the objective function f (x) may be represented by the following form:

y_i＝f(x_i)+∈，∈～N(0，σ_n^2)

wherein x is_iBeing an argument of the objective function, i.e. the initial configuration scheme, y, of the map element_iThe objective function can be optimized through a Bayesian optimization algorithm for the dependent variable of the objective function, namely the evaluation data corresponding to the initial configuration scheme, and the target configuration scheme corresponding to the initial configuration scheme is determined. In connection with the above example, if the map element includes a first jump mechanism and a second jump mechanism, x_iIs a multi-dimensional vector comprising S1, E1, S2 and E2, x_iCan be represented by X ═ (S1, E1, S2, E2). "∈" is the noise of the objective function, which follows a positive too distribution with a mean of 0. In this case, the objective function f (x) follows a joint gaussian distribution, which can be determined by the mean vector μ and the covariance matrix Σ. The gaussian process is determined by a mathematical expectation function (mean function) and a kernel function (kernel function), also known as a covariance function. For ease of reference, the mathematical expectation function is denoted herein by "m" and the kernel function is denoted by "k".

According to the Bayes law, the posterior distribution probability (spatial distribution over functions) of the target function f (x) can be determined as follows:

where p (f) ═ GP (m, k) is the prior probability distribution of the objective function, m is the above mathematical expectation function, and k is the kernel function.

For the likelihood function, p (y/X) ═ p (y | f, X) p (f | X) df is an evidence function, and p (f | X, y) ═ GP (m |, X) is an evidence function_post，k_post) Is a posterior distribution probability function of the objective function. By the formula as described above it can be derived:

wherein x is_★To obtain the input variable, m, after discretizing the vector in X_post(x_★) The objective function learned for the Gaussian process function is at x_★Mean value of posterior predicted distribution of (k)_post(x_★，x_★) The objective function learned for the Gaussian process function is at x_★The posterior prediction of the distribution variance. m (X) is the prior distribution of the mathematical expectation function, K ═ K (X, X) is the covariance matrix of the input variables, K (X)_★X) is the covariance vector of the input variables of the data point to be predicted, k (X, X)_★) Is k (x)_★And X). k (x)_★，x_★) Being a kernel function, the kernel function may be of the form:

k(x₁，x₂)＝exp(-|d(x₁，x₂)|²)

wherein d (x)₁，x₂) Is x₁，x₂The euclidean distance between them.

As shown in fig. 3, fig. 3 is a schematic diagram of bayesian optimization provided in this embodiment of the present application, in which the abscissa represents an independent variable of an objective function, the ordinate represents a dependent variable of the objective function, and a solid line 301 is a predicted mean value m of the objective function_post(x_★) The dotted line 302 represents a plurality of observation points 303 (corresponding to the observation points, i.e., the initial configuration scheme) according to the inputMulti-dimensional vector of (c) the gray area 304 is the confidence interval defined by the variance k_post(x_★，x_★) And (6) determining. As shown in fig. 3, in the interval [0, 4 ]]In the method, observation values corresponding to a plurality of observation points 303 exist, confidence intervals determined by the observation points 303 are very small, and it is indicated that a Gaussian process function determines a target function f (x); in contrast, in the interval [5, 7 ]]The number of inner observation points 303 is small, the confidence interval is large, and the Gaussian process function cannot determine the target function f (x).

After determining the confidence interval of X, i.e. the selection range, through the gaussian process, the next observation point corresponding to the current observation point, i.e. the target configuration scheme, can be selected from the selection range through exploration and development (exploration and deployment) rules. For example, the acquisition function may use a ucb (upper Confidence bound) function:

α_UCB(x)＝μ(x)+βσ(x)

where μ (x) is the mean of the objective function and σ (x) is the variance of the objective function. The maximum value of the acquisition function may be calculated, and the mean and the variance corresponding to the maximum value of the acquisition function may be taken as the mean and the variance at the next observation point in the target function, so that X at the next observation point, i.e., a target configuration, may be determined according to the mean and the variance at the next observation point, for example (S1 ═ 60, E1 ═ 68, S2 ═ 54, and E2 ═ 71).

In practical application, the specific process of the bayesian optimization can be set according to requirements, and this embodiment will not be described in detail. The Optimization algorithm may also adopt Optimization algorithms such as a Genetic algorithm (Genetic algorithm), a Particle Swarm Optimization (Particle Swarm Optimization), an Ant Colony Optimization (Ant Colony Optimization), etc., and the acquisition function may also adopt acquisition functions such as expected improvement (expected improvement), knowledge gradient (knowledge gradient), etc., and this embodiment does not limit the specific types of the Optimization algorithm and the acquisition function.

And 103, generating a target virtual map by adopting a target configuration scheme.

In this embodiment, after determining the target configuration scheme corresponding to the initial configuration scheme, the initial configuration scheme in the initial virtual map may be replaced with the corresponding target configuration scheme, so as to obtain the target virtual map.

With reference to the above example, in the initial arrangement scheme of the first jump mechanism in the initial virtual map, the initial arrangement of the start grid is 20, and the initial arrangement of the target grid is 25, and in the target arrangement scheme corresponding to the initial arrangement scheme of the first jump mechanism, the start grid is 60, and the target grid is 68. At this time, the start lattice in the first skip gate may be set to G₆₀The target grid is set to G₆₈. Similarly, the initial configuration scheme of the second jump mechanism is replaced by the target configuration scheme, so that the target virtual map corresponding to the initial virtual map can be obtained, and the configurations of the jump mechanisms in the initial virtual map and the target virtual map are different.

And step 104, replacing the initial virtual map with the target virtual map, and repeatedly executing the process of generating the target virtual map until a set ending condition is reached.

In this embodiment, after obtaining the target virtual map, the target virtual map may be used as a new initial virtual map, and step 101 to step 103 are continuously executed according to the new initial virtual map to obtain another target virtual map.

As shown in fig. 4, fig. 4 is a schematic diagram of an optimization process provided in an embodiment of the present application, where X in an initial virtual map corresponds to a first observation point 401, (S1, E1, S2, E2), a second observation point 402 corresponding to the first observation point 401, that is, a target configuration scheme corresponding to the initial configuration scheme, may be determined through a first sub-optimization, after a first target virtual map is generated according to the target configuration scheme, the first target virtual map is used as a new initial virtual map, and steps 101 to 103 are repeatedly performed, so that a predicted mean value of an objective function shown by a solid line 403, an objective function shown by a dashed line 404, and an acquisition function shown by a solid line 405 may be obtained.

Determining the maximum value of the acquisition function, wherein an arrow 406 is shown as the maximum value of the acquisition function, the mean value and the variance corresponding to the position of the arrow 406 are the mean value and the variance of the next observation point, namely the mean value and the variance corresponding to the third observation point 407, determining the target configuration scheme corresponding to the third observation point 407 according to the mean value and the variance of the third observation point 407, and generating a second target virtual map according to the target configuration scheme corresponding to the third observation point 407.

By analogy, a fourth observation point 408 can be determined according to the first observation point 401, the second observation point 402 and the third observation point 407, and a target configuration scheme corresponding to the fourth observation point 408 is determined, so as to generate a third target virtual map.

In this embodiment, when the number of the target virtual maps reaches the target number, it may be determined that the set end condition is reached, and the generation of the target virtual map is stopped, at this time, a plurality of target virtual maps and a plurality of corresponding initial virtual maps are obtained, and the evaluation data of each initial virtual map is determined at the same time.

In practical applications, after the function value of the objective function is stable, the generation of the target virtual map may be stopped, that is, when the evaluation data of a plurality of continuous initial virtual maps are stable within the preset interval, the process of generating the target virtual map is ended. The setting end condition may be set according to a requirement, and this embodiment does not limit this.

And 105, taking the initial virtual map with the evaluation data meeting the evaluation conditions as a new virtual map.

In this embodiment, after obtaining the plurality of initial virtual maps, an initial virtual map that meets the evaluation condition may be selected from the plurality of initial virtual maps as a new virtual map according to the evaluation data of the plurality of initial virtual maps.

Illustratively, step 105 may be implemented as follows:

and taking the initial virtual map with the evaluation data larger than or equal to the preset evaluation threshold value as a new virtual map.

With reference to the above example, after the target virtual map is obtained, the target virtual map is used as a new initial virtual map, and evaluation data of the new initial virtual map is obtained. A preset evaluation threshold value may be set to 20, and when the evaluation data of the initial virtual map is greater than or equal to the preset evaluation threshold value, it is determined that the initial virtual map meets the evaluation condition, and the initial virtual map may be taken as a new virtual map. At this time, a new virtual map may be applied to the virtual game, and a new virtual scene may be constructed for the virtual game through the new virtual map.

In the process of generating the target virtual map, the initial virtual map used for the first time is a virtual map manually set by the user. After a certain number of virtual maps are generated, the virtual map with the evaluation data larger than or equal to the preset evaluation threshold value is used as a new virtual map, and the virtual map with higher evaluation data, namely more reasonable evaluation data, can be selected.

In summary, in this embodiment, the evaluation data of the initial virtual map is obtained, the target configuration scheme corresponding to the initial configuration scheme is determined according to the evaluation data and the initial configuration scheme, the target virtual map is generated by using the target configuration scheme, the initial virtual map is replaced by the target virtual map, the process of generating the target virtual map is repeatedly executed until the set end condition is reached, and the initial virtual map whose evaluation data meets the evaluation condition is used as a new virtual map. In the process of generating the virtual map, the configuration of map elements is adjusted according to the evaluation data of the virtual map to generate a new virtual map, so that the layout of the generated virtual map is more reasonable, and more virtual maps with unreasonable layouts are avoided.

Fig. 5 is a flowchart of steps of another virtual map generation method provided in an embodiment of the present application, and as shown in fig. 5, the method may include:

and 501, acquiring simulation result data generated in multiple times of simulation running of the initial virtual map.

Wherein the simulation result data corresponds to the map elements.

In this embodiment, the electronic device may perform multiple simulation operations on the initial virtual map to obtain simulation result data generated by the multiple simulation operations. For example, the electronic device may input an initial virtual map into a user simulation system, which may simulate a process in which a user uses the virtual map. By combining the above examples, the user simulation system may simulate the user to throw the dice, and after the dice is thrown to obtain the corresponding points, move the character a or the character B to advance the grid of the corresponding points. When the character A or the character B moves to the last grid, ending one game, and obtaining simulation result data such as the income S obtained by the game, the cost C multiplied by T of the game, the number T of times of throwing dices in the game, and the like.

The electronic device may repeat the simulation for multiple times (for example, 100 times), and statistics is performed on results of the multiple times of simulation to obtain simulation result data generated by multiple times of simulation operation.

In practical application, the simulation result data may further include other data, and the specific process of the simulation operation may be set according to requirements, which is not limited in this embodiment.

And 502, determining evaluation data according to the initial configuration scheme and the simulation result data.

In this embodiment, the electronic device may determine the evaluation data according to the simulation result data and the initial configuration scheme. For example, the electronic device may determine the evaluation data based on the total revenue and total cost generated by the multiple simulation runs. With reference to the above example, after the initial virtual map is subjected to multiple simulation runs, the cost C × T generated by each simulation run and the benefit S generated by each simulation run can be obtained, and if the simulation times are N times, the total cost of the N simulation runs is N × C × T, and the total benefit is N × S. In this case, the ratio of the total profit to the total cost may be used as an index for measuring the reasonability of the initial virtual map, the evaluation data may be determined by the ratio of the total profit to the total cost, the ratio of the total profit to the total cost may be expressed by RTP, and V_totalRepresents the total profit, C_totalRepresenting the total cost, the value of RTB can be determined as follows:

wherein Y3 is evaluation data, RTP is a ratio of total profit to total cost, abs (1-RTP) is an absolute value between RTP and 1, and when the ratio of total profit to total cost is greater than or equal to 0.9 and less than or equal to 1.1, the evaluation data Y3 is 100-abs (1-RTP) × 1000; in contrast, the evaluation data Y3 is minus 30. The specific calculation method of the evaluation data may be set according to the requirement, and this embodiment does not limit this.

As another example, the average number of times dice are thrown in each game may be used as an indicator of the reasonableness of the initial virtual map. The electronic equipment can count the times of throwing the dice in each simulation operation in the process of multiple simulation operations, calculate the total times of throwing the dice, and obtain the average throwing times by dividing the total times by the simulation times. At this time, the evaluation data may be calculated as follows:

wherein Y4 is the evaluation data, R_aFor the average number of throws, "abs (35-R)_a) "is 35 minus R_aAbsolute value of (a). When the average number of throws was 20 or more and 50 or less, evaluation data Y4 was 100-abs (35-R)_a) X 7; in contrast, the evaluation data Y4 is negative 20.

In practical application, the virtual map is simulated and operated to generate simulation result data, and the evaluation data of the virtual map is determined according to the simulation result data, so that the evaluation data can better accord with the actual situation, and the virtual map generated according to the evaluation data can better accord with the actual situation and is more reasonable.

Optionally, the assessment data comprises a plurality of sub-assessment terms;

accordingly, step 302 may be implemented as follows:

determining sub-evaluation data corresponding to the sub-evaluation items according to the simulation result data corresponding to the sub-evaluation items and the initial configuration scheme;

and determining the evaluation data according to the sub-evaluation data corresponding to the sub-evaluation item.

In this embodiment, the evaluation data of the initial virtual map may be determined by a plurality of evaluation indexes. Each evaluation index may correspond to one sub-evaluation item, and the evaluation data may be determined by the sub-evaluation data corresponding to all the sub-evaluation items. In combination with the above examples, the rationality of the virtual map can be measured by combining indexes such as the length of the jump organ, the difference between the secondary reward organ and the primary reward organ, the ratio of the total income to the total cost, the average throwing times and the like. At this time, the sub-evaluation items may include a sub-evaluation item corresponding to the length of the jump organ, a sub-evaluation item corresponding to the difference between the secondary reward organ and the primary reward organ, a sub-evaluation item corresponding to the ratio of the total profit to the total cost, and a sub-evaluation item corresponding to the average throwing number. The comment data of the initial virtual map may be the sum of Y1, Y2, Y3, and Y4. Or different weights can be set for different sub-evaluation scores according to the importance degrees of different evaluation indexes.

In practical application, the evaluation data of the virtual map is determined according to the sub-evaluation scores corresponding to the sub-evaluation items, so that the evaluation data can be more scientific and reasonable, and a more reasonable virtual map can be generated.

Step 503, determining a target configuration scheme corresponding to the initial configuration scheme according to the evaluation data and the initial configuration scheme.

And step 504, generating a target virtual map by adopting a target configuration scheme.

Optionally, step 504 may be implemented as follows:

and when the target configuration scheme does not meet the preset limiting conditions, generating a target virtual map according to the preset configuration scheme corresponding to the preset limiting conditions.

In one embodiment, a constraint condition may be set for the target configuration scheme to control the generation process of the virtual map, so that the virtual map meets a certain condition. In connection with step 103, in order to avoid the first jump mechanism appearing at the end of the virtual map, the preset limit condition for the start grid may be 45 or less and the preset limit condition for the target grid may be 60 or less for the first jump mechanism. Correspondingly, in the preset configuration scheme corresponding to the preset limiting condition, the starting grid is 45, and the target grid is 60. When the starting cell of the first jump round in the target configuration scheme is 60, it may be determined that the starting cell does not meet the preset limit condition, and when the target cell is 68, it may be determined that the target cell does not meet the preset limit condition. At this time, the target virtual map may be generated according to the start grid 45 and the target grid 60 in the preset configuration scheme, where the start grid of the first jump mechanism in the target virtual map is 45 and the target grid is 60. Similarly, in order to avoid the second jump mechanism appearing at the front end of the virtual map, the preset limit condition for the start grid may be greater than or equal to 50 and the preset limit condition for the target grid may be less than or equal to 95 for the second jump mechanism. The preset restriction scheme and the preset restriction condition may be specifically set according to the map element and the user requirement, which is not limited in this embodiment.

In practical application, corresponding preset limiting conditions are set for the target configuration scheme, and the generation process of the virtual map can be controlled, so that the generation of the virtual map meets certain requirements. In connection with the above example, the limiting conditions are set for the first and second jumping mechanisms, which may be caused to occur at expected locations in the map, to rationally arrange the first and second jumping mechanisms in the virtual map.

And 505, replacing the initial virtual map with the target virtual map, and repeatedly executing the process of generating the target virtual map until a set ending condition is reached.

And step 506, taking the initial virtual map with the evaluation data meeting the evaluation conditions as a new virtual map.

Alternatively, step 506 may be implemented as follows:

sequencing the plurality of initial virtual maps according to the evaluation data of the initial virtual maps to obtain a sequencing result;

and taking the initial virtual maps with the preset number which are ranked in the top in the ranking result as new virtual maps.

In this embodiment, after obtaining the plurality of initial virtual maps and the evaluation data of each initial virtual map, a preset number of initial virtual maps with higher evaluation data may be selected from the plurality of initial virtual maps as a new virtual map according to the evaluation data. Specifically, after the plurality of initial virtual maps are obtained, the plurality of initial virtual maps may be sequentially sorted from large to small according to the size of the evaluation data, so as to obtain a sorting result. After the sequencing result is obtained, determining that the initial virtual maps in the preset number accord with the evaluation condition from the maximum evaluation data to obtain a new virtual map. The specific value of the preset number can be set according to the requirement, and this embodiment does not limit this.

In practical application, a preset number of virtual maps which are ranked in the front are selected from the plurality of virtual maps as new virtual maps according to the ranking result, so that virtual maps which meet the requirement of quantity and are reasonable can be obtained.

Fig. 6 is a block diagram of a virtual map generation apparatus provided in an embodiment of the present application, and as shown in fig. 6, the apparatus 600 may include:

an obtaining module 601, configured to obtain evaluation data of an initial virtual map; the evaluation data is determined based on an initial configuration scheme of at least one map element in the initial virtual map.

A determining module 602, configured to determine, according to the evaluation data and the initial configuration scheme, a target configuration scheme corresponding to the initial configuration scheme.

A generating module 603, configured to generate a target virtual map by using a target configuration scheme.

A replacing module 604, configured to replace the initial virtual map with the target virtual map, and repeatedly execute a process of generating the target virtual map until a set end condition is reached;

and a selecting module 605, configured to use the initial virtual map with the evaluation data meeting the evaluation condition as a new virtual map.

Optionally, the obtaining module 601 includes:

the system comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring simulation result data generated in multiple times of simulation operation of an initial virtual map; the simulation result data corresponds to the map elements.

And the determining unit is used for determining the evaluation data according to the initial configuration scheme and the simulation result data.

Optionally, the assessment data comprises a plurality of sub-assessment items.

And the determining unit is specifically used for determining the sub-evaluation data corresponding to the sub-evaluation item according to the simulation result data corresponding to the sub-evaluation item and the initial configuration scheme.

Optionally, the obtaining module is specifically configured to determine the evaluation data according to an initial configuration scheme of the target map element.

Optionally, the selecting module 605 is specifically configured to sort the plurality of initial virtual maps according to the evaluation data of the initial virtual maps, so as to obtain a sorting result; and taking the initial virtual maps with the preset number which are ranked in the top in the ranking result as new virtual maps.

Optionally, the selection module 605 is specifically configured to use the initial virtual map with the evaluation data greater than or equal to the preset evaluation threshold as the new virtual map.

Optionally, the generating module 603 is further configured to generate the target virtual map according to a preset configuration scheme corresponding to the preset limiting condition when the target configuration scheme does not meet the preset limiting condition.

The virtual map generation device provided by the embodiment of the application has the corresponding functional module for executing the virtual map generation method, can execute the virtual map generation method provided by the embodiment of the application, and can achieve the same beneficial effects.

In another embodiment provided by the present invention, there is also provided an electronic device, which may include: the processor executes the program to realize each process of the virtual map generation method embodiment, and can achieve the same technical effect, and the details are not repeated here in order to avoid repetition.

Exemplarily, as shown in fig. 7, fig. 7 is a schematic diagram of a hardware structure of an electronic device provided in an embodiment of the present application, where the electronic device may specifically include: a processor 701, a storage device 702, a display screen 703 with touch functionality, an input device 704, an output device 705, and a communication device 706. The number of the processors 701 in the electronic device may be one or more, and one processor 701 is taken as an example in fig. 7. The processor 701, the storage means 702, the display 703, the input means 704, the output means 705 and the communication means 706 of the electronic device may be connected by a bus or other means.

In yet another embodiment of the present invention, a computer-readable storage medium is further provided, which stores instructions that, when executed on a computer, cause the computer to execute the virtual map generation method described in any of the above embodiments.

In yet another embodiment, a computer program product containing instructions is provided, which when run on a computer, causes the computer to perform the virtual map generation method described in any of the above embodiments.

It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.

Claims

1. A virtual map generation method, comprising:

generating a target virtual map by adopting the target configuration scheme;

2. The method of claim 1, wherein obtaining evaluation data for the initial virtual map comprises:

acquiring simulation result data generated in multiple simulation runs of the initial virtual map; the simulation result data corresponds to the map element;

and determining the evaluation data according to the initial configuration scheme and the simulation result data.

3. The method of claim 2, wherein the assessment data comprises a plurality of sub-assessment terms;

the determining the evaluation data according to the initial configuration scheme and the simulation result data comprises:

4. The method of claim 1, wherein obtaining evaluation data for the initial virtual map comprises:

and determining the evaluation data according to the initial configuration scheme of the target map element.

5. The method according to claim 1, wherein the step of regarding the initial virtual map with evaluation data meeting the evaluation condition as a new virtual map comprises:

and taking the initial virtual maps with the preset number ranked at the top in the ranking result as new virtual maps.

6. The method according to claim 1, wherein the step of regarding the initial virtual map with evaluation data meeting the evaluation condition as a new virtual map comprises:

and taking the initial virtual map with the evaluation data larger than or equal to a preset evaluation threshold value as a new virtual map.

7. The method according to any one of claims 1-6, wherein when generating the target virtual map using the target configuration scheme, the method comprises:

and when the target configuration scheme does not meet the preset limiting conditions, generating the target virtual map according to the preset configuration scheme corresponding to the preset limiting conditions.

8. A virtual map generation apparatus, comprising:

the acquisition module is used for acquiring evaluation data of the initial virtual map; the evaluation data is determined according to an initial configuration scheme of at least one map element in the initial virtual map;

a determining module, configured to determine, according to the evaluation data and the initial configuration scheme, a target configuration scheme corresponding to the initial configuration scheme;

the generating module is used for generating a target virtual map by adopting the target configuration scheme;

the replacing module is used for replacing the initial virtual map by the target virtual map and repeatedly executing the process of generating the target virtual map until a set ending condition is reached;

and the selection module is used for taking the initial virtual map of which the evaluation data accords with the evaluation conditions as a new virtual map.

9. An electronic device comprising a processor, a memory, and a program or instructions stored on the memory and executable on the processor, the program or instructions when executed by the processor implementing the steps of the virtual map generation method of claims 1-7.

10. A readable storage medium, characterized in that it stores thereon a program or instructions which, when executed by a processor, implement the steps of the virtual map generation method according to claims 1-7.