Meat pigeon element-based random map generation method and device, equipment and medium

Abstract

The application discloses a random map generation method and device based on meat pigeon elements, equipment and medium. The method comprises the following steps: acquiring a map preference setting and a meat pigeon element parameter of a to-be-generated map, the meat pigeon element parameter comprising a plurality of meat pigeon element categories and respective preset distribution rules and preset element attributes corresponding to the meat pigeon element categories; generating a basic map framework of the to-be-generated map based on the map preference setting and the meat pigeon element parameter; and filling each meat pigeon element category in the basic map framework according to the map preference setting and the respective preset distribution rules and preset element attributes corresponding to each meat pigeon element category to generate a random map. The filling mechanism jointly formed by the map preference setting and the meat pigeon element parameter is constructed, the dynamic balance between the structural rationality of the map content and the randomness of the generation is achieved, and the playability and the repeated play value of the meat pigeon game map are improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, apparatus, device and medium for generating random maps based on pigeon elements. Background Technology

[0002] With the continuous development of the gaming industry, procedural content generation technology has been widely applied in game scenarios, especially in roguelike games, where random map generation has become a key means to enhance replayability and player immersion. In roguelike games, maps typically consist of various functional elements, such as terrain structures, obstacle areas, resource points, combat events, NPCs, and reward items. These elements have their own attributes and interactive functions, and their distribution on the map must satisfy specific rules and logical relationships. Therefore, how to efficiently construct a structurally sound and content-rich map based on player or client-defined map preferences, while satisfying the distribution rules and attribute constraints of roguelike elements, has become a critical technical problem that map generation systems urgently need to solve.

[0003] Currently, random map generation technology in roguelike games primarily relies on the splicing and random arrangement of preset map tiles. While this method enhances map diversity to some extent, it still has significant limitations. For example, map structures are highly predictable and repetitive, and the randomly generated results lack deep variations, leading to similar player experiences across multiple playthroughs and reducing the game's replayability and replay value. Furthermore, this method lacks the ability to dynamically adapt to player preferences, and the generation process lacks fine-grained element control and distribution scheduling mechanisms, making it difficult to meet higher-level demands for personalized content and intelligent system generation. Summary of the Invention

[0004] This application provides a method, apparatus, device, and medium for generating random maps based on roguelike elements. It can acquire map preference settings sent by the client, along with corresponding roguelike element parameters. These parameters include several types of roguelike elements and their respective preset distribution rules and element attributes. Based on this, a basic map framework for the map to be generated is generated. Then, combining the map preference settings and roguelike element parameters, various roguelike elements are randomly filled into the map framework to construct the final map structure. This technical solution effectively solves the problems of disordered element distribution, high repetition in map structure, and monotonous player experience in traditional random map generation methods. It achieves a balance between logical rationality of map structure and diversity of content generation, significantly improving the generation efficiency, replay value, and gameplay depth of roguelike game maps.

[0005] Firstly, this application provides a method for generating random maps based on pigeon elements, including: Obtain the map preference settings and rogue element parameters of the map to be generated. The rogue element parameters include several types of rogue elements and their respective preset distribution rules and preset element attributes. The basic map framework of the map to be generated is generated based on the map preference settings and the pigeon element parameters. Based on the map preference settings and the preset distribution rules and preset element attributes corresponding to each type of rogue element, a random map is generated by randomly filling various rogue elements on the basic map framework.

[0006] Secondly, this application provides a random map generation device based on pigeon elements, comprising: The acquisition module is used to acquire the map preference settings and rogue element parameters of the map to be generated. The rogue element parameters include several types of rogue elements and their respective preset distribution rules and preset element attributes. The framework module is used to generate the basic map framework of the map to be generated based on the map preference settings and the rogue element parameters; The fill module is used to randomly fill various types of rogue elements on the basic map framework to generate a random map based on the map preference settings and the preset distribution rules and preset element attributes corresponding to each type of rogue element.

[0007] Thirdly, this application provides a random map generation device based on pigeon elements, comprising: One or more processors; A memory that stores one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the random map generation method based on pigeon elements as described in the first aspect.

[0008] Fourthly, this application provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the random map generation method based on pigeon elements as described in the first aspect.

[0009] This application acquires user-defined map preferences and roguelike element parameters, extracts several types of roguelike elements, corresponding preset distribution rules, and element attributes, and constructs a structured representation of map content. Then, combined with the map construction goals, it implements a multi-dimensional element distribution and random generation process, achieving differentiated adaptation of map content under different preference conditions. Based on the extracted map elements, it automatically drives map framework construction and content filling, strategically configuring various roguelike elements to generate random map results covering multiple game scenario requirements. Subsequently, according to the map generation logic and element attributes, it completes the map content rendering and generation process, ensuring the map's integrity and playability under complex rules. This method enhances map diversity and replay value while increasing the flexibility and intelligence of map generation, significantly reducing the risk of content duplication due to templates or manual configuration. Through automated map construction and element filling mechanisms, it effectively improves game design efficiency and player experience quality, possessing high practical value and promotion potential. Attached Figure Description

[0010] Figure 1 This is a flowchart of a random map generation method based on pigeon elements provided in an embodiment of this application; Figure 2 This is a flowchart illustrating the generation of the basic map framework provided in the embodiments of this application; Figure 3 This is a flowchart illustrating the random filling of pigeon elements provided in an embodiment of this application; Figure 4 This is a flowchart illustrating the priority determination of pigeon element generation according to an embodiment of this application; Figure 5 This is a flowchart of the pigeon element filling based on element adaptation mapping provided in the embodiments of this application; Figure 6 This is a partial schematic diagram of the random map generated according to the embodiments of this application; Figure 7 This is a flowchart of random map adjustment provided in an embodiment of this application; Figure 8 This is a structural diagram of the random map generation device based on pigeon elements provided in the embodiments of this application; Figure 9 This is a structural diagram of the random map generation device based on pigeon elements provided in the embodiments of this application. Detailed Implementation

[0011] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as being processed sequentially, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. A process can be terminated when its operation is completed, but it may also have additional steps not included in the drawings. A process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0012] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0013] Currently, in the development and operation of Roguelike games, map generation mechanisms face increasingly prominent challenges in terms of diverse construction and player experience optimization. Existing map generation systems generally rely on a combination of preset map tiles and rule-driven approaches, lacking a unified structural generation model and dynamic adaptation capabilities. This results in high map content repetition rates, insufficient logical randomness, and difficulty in responding to players' continuously growing demands for map complexity and exploration depth, severely restricting the game's playability and lifecycle management efficiency. Different map regions exhibit significant differences in structural design, event distribution, and interaction mechanisms. Traditional generation methods struggle to achieve diversified and dynamic content coverage while maintaining reasonableness. Furthermore, key map information such as travel paths, enemy layouts, and mission trigger points lack centralized descriptions and semantic consistency support, leading to a lack of controllability in the map generation process and a lack of sustained appeal for replayability. In addition, the lack of version recording mechanisms for map structure adjustments and element configurations further exacerbates debugging difficulties and content consistency issues throughout the map's lifecycle.

[0014] Therefore, there is an urgent need for a map generation method for Roguelike games that possesses structural self-adaptation and intelligent content arrangement capabilities. This method should be able to uniformly collect generation elements and analyze spatial logic, automatically identify and adapt to player behavior characteristics and game mechanics requirements, construct a highly randomized map topology with clear gameplay orientation, and support a traceable generation and optimization mechanism. Through a well-structured and content-rich map generation system, not only can the efficient construction and dynamic evolution of game scenes be achieved, but replay value and user stickiness can also be enhanced. This provides game developers with reliable map content generation support, comprehensively promoting the intelligent development and sustainable operation capabilities of Roguelike games.

[0015] To address the aforementioned issues, this embodiment provides a random map generation method based on roguelike elements. By introducing map preference settings and a roguelike element parameter modeling mechanism, it achieves dynamic adaptation and intelligent arrangement of map structure and content elements, thereby constructing a diverse and highly playable map generation system. This method supports obtaining user-defined map preference parameters and, combined with structured configuration information containing multiple categories of roguelike elements, automatically constructs the basic spatial framework of the map to be generated. Roguelike element parameters cover core game content such as monster types, event nodes, and item mechanics, and preset distribution rules and attribute definitions for each type of element. Based on map preferences and element attributes, the system fills in content on the basic map structure according to random generation logic, achieving intelligent distribution and strategic combination of scene elements. Through this mechanism, decoupled modeling and dynamic reorganization of map structure and interactive content can be achieved, effectively replacing traditional generation methods that rely on fixed templates and manual configuration, significantly enhancing the personalization, logic, and replay value of map generation. This method not only improves the richness and efficiency of map content generation, but also enhances the system's adaptability to different game mechanics, comprehensively promoting the evolution of Roguelike game map generation towards automation and intelligence, and providing players with a more challenging and exploratory gaming experience.

[0016] The random map generation method based on pigeon elements provided in this embodiment can be executed by a random map generation device based on pigeon elements. This device can be implemented through software and / or hardware. The device can consist of two or more physical entities, or it can consist of a single physical entity. For example, the random map generation device based on pigeon elements can be an operations and maintenance server used to maintain the normal operation of services.

[0017] The rogue-element-based random map generation device has at least one type of operating system installed, including but not limited to Android, Linux, and Windows. The rogue-element-based random map generation device can install at least one application on the operating system; this application can be a built-in application of the operating system or an application downloaded from a third-party device or server. In this embodiment, the rogue-element-based random map generation device has at least one application capable of executing the rogue-element-based random map generation method.

[0018] For ease of understanding, this embodiment uses the operation and maintenance server as the main body for executing the random map generation method based on pigeon elements.

[0019] Figure 1 A flowchart of a random map generation method based on pigeon elements provided in an embodiment of this application is given. (Reference) Figure 1 The method for generating random maps based on pigeon elements specifically includes: S110. Obtain the map preference settings and rogue element parameters of the map to be generated. The rogue element parameters include several types of rogue elements and their respective preset distribution rules and preset element attributes.

[0020] In some embodiments, the map preference settings and corresponding roguelike element parameters of the map to be generated are first obtained. The map preference settings represent the user's or system's preset requirements for map type, difficulty, size, regional distribution, and other characteristics. The roguelike element parameters describe the configuration of game elements to be integrated into the map, including several types of roguelike elements and their corresponding attributes and generation rules. Roguelike elements refer to the basic units used to constitute map interactive gameplay, such as monsters, resource points, event triggering devices, traps, and power-ups. Each type of roguelike element has preset distribution rules and element attributes. The preset distribution rules constrain the element's frequency, density, regional restrictions, and random weight in the map space; the preset element attributes represent the element's behavioral logic, interaction methods, visual style, and triggering conditions.

[0021] In one embodiment, map preference settings can be obtained by reading preference configuration parameters from the map editing interface submitted by the user terminal, or by extracting preference patterns from historical map usage data.

[0022] In one embodiment, the method for setting the roguelike elements and their parameters can be: combining and loading elements based on the element template library defined in the game rules engine, and filtering the element set that matches the current settings according to the map type.

[0023] In one embodiment, the preset distribution rules can be represented in the form of multi-dimensional vectors and dynamically corrected in combination with terrain topology analysis results to ensure that the rogue elements have a reasonable layout and playability on the map.

[0024] S120. Generate the basic map framework of the map to be generated based on the map preference settings and the pigeon element parameters.

[0025] In some embodiments, a basic map framework for the map to be generated is produced based on the acquired map preference settings and rogue element parameters. The basic map framework characterizes the initial structure and overall spatial layout of the map, providing a spatial basis and boundary constraints for the subsequent filling and distribution of rogue elements. Map preference settings limit the size range, terrain type, level hierarchy, and spatial connectivity requirements of the map framework; rogue element parameters affect the initial layout requirements of key areas to be reserved in the map framework, such as event trigger areas, monster spawn points, and reward areas. During map generation, procedural generation algorithms, such as Perlin noise, BSP partitioning, and Wave Function Collapse, can be used to construct the basic terrain skeleton, and preference settings can be combined to correct terrain boundaries, generate passage structures, and distribute functional areas.

[0026] In one embodiment, the spatial division of the map frame can be achieved by first using a partitioning algorithm to divide the map into several functional sub-regions, and then assigning roles to each sub-region according to preference settings.

[0027] In one embodiment, the connectivity design of the map framework can be: establishing accessibility relationships between the main path and branch paths based on the graph structure, ensuring that players have controllable exploration paths and a certain degree of randomness in the map.

[0028] In one embodiment, the construction of the map framework can incorporate a dynamic adjustment mechanism to fine-tune the original framework based on the layout requirements of some core roguelike elements, thereby enhancing the map's strategic depth and playability.

[0029] Optionally, Figure 2 A flowchart illustrating the generation of the basic map framework provided in this application's embodiments is given. (Reference) Figure 2 The basic map framework generation method specifically includes: S1201. Extract the map size, terrain preference, and map difficulty of the map to be generated from the map preference settings.

[0030] For example, the map size, terrain preferences, and map difficulty of the map to be generated are extracted from the map preference settings to provide a parameter basis for subsequent map framework generation and element filling. Among them, the map size is used to represent the number of horizontal and vertical grid points or spatial range of the map to be generated, which directly affects the total available space and exploration time of the map; the terrain preference is used to limit the distribution tendency and proportion of terrain types such as mountains, plains, water, and caves in the map, thereby affecting the distribution strategy of traversable areas, interactive areas, and elements; the map difficulty refers to the overall challenge indicators such as the strength level of hostile elements, trap density, and resource abundance in the generated map.

[0031] In one embodiment, the map size can be represented by the number of grid points in both the width and height directions, or it can be preset by area levels and mapped to a specific grid range.

[0032] In one embodiment, terrain preferences can be configured based on player selection or system recommendations, such as favoring "multiple obstacles," "open terrain," or "maze structure," and affect the sampling density and generation distribution of the terrain generation algorithm.

[0033] In one embodiment, map difficulty can be set based on player level, game progress, or challenge mode, and used in subsequent processes to constrain parameters such as the upper limit of enemy element attributes, the probability of special event generation, and the scarcity of key resources.

[0034] S1202. Based on the preset distribution rules and preset element attributes corresponding to each type of pigeon element in the pigeon element parameters, determine the space occupancy requirements of each type of pigeon element.

[0035] For example, based on the preset distribution rules and preset element attributes corresponding to each type of rogue element in the rogue element parameters, the space occupancy requirements of each type of rogue element are determined. This facilitates the rational allocation of spatial resources during map generation, achieving a balance between balanced distribution and diverse gameplay. The preset distribution rules characterize the distribution density, distribution area preference, and mutual exclusion / dependency relationships of a certain type of rogue element on the map. The preset element attributes characterize the element's spatial size, interactive state, generation priority, repeatability, and other characteristics. The space occupancy requirements comprehensively represent the space scale and layout constraints that this type of element needs to reserve in the target map.

[0036] In one embodiment, the distribution rules may include grid-level density factor, edge / center area distribution tendency, distance constraints with other elements, etc., to limit the layout range and spacing relationship of such elements.

[0037] In one embodiment, the spatial size in the preset element attributes can be refined into the number of grid points occupied and the shape structure, such as 1×1, 2×2, L-shaped, cross-shaped, etc., which determines the embedding method of the element in the map; the interactive state indicates whether the element is a triggerable event, an interactive object or a static background element, which affects the distribution priority and dynamic behavior determination.

[0038] In one embodiment, based on the above distribution rules and attribute parameters, a spatial template model of this type of element can be established for arrangement calculation and conflict detection in the subsequent filling stage.

[0039] S1203. Based on the map size, terrain preference, map difficulty, and space requirement, generate the basic map framework of the map to be generated.

[0040] For example, a basic map framework for the map to be generated is created based on map size, terrain preference, map difficulty, and space requirements. This framework provides a basic spatial structure and zoning reference for the subsequent filling and layout of roguelike elements. Specifically, map size represents the overall width, height, and regional resolution of the map, serving as a fundamental parameter for constructing map boundaries; terrain preference represents the overall topographical features of the map, such as prioritizing plains, concentrating obstacles, and creating maze-like paths, guiding spatial morphology construction; map difficulty represents the complexity and challenge level of the map, influencing terrain complexity and accessibility design; and space requirements determine the proportion of reserved space and the feasibility of the distribution for various elements.

[0041] In one embodiment, the map size may include grid-level map size and physical unit size, and serve as the basis for dividing the basic grid system.

[0042] In one embodiment, terrain preferences can be used to form map region outlines by setting different regional landform labels and generating strategies.

[0043] In one embodiment, the map difficulty parameter can be used to control spatial characteristics such as the number of travel paths, branch structure, and dead zone density, and dynamically adjust the terrain complexity in conjunction with the generation rules. For example, a high-difficulty map contains more loops, maze structures, and trap areas.

[0044] In one embodiment, space blocks are reserved for key partitions in the map based on space occupancy requirements, and a preliminary terrain label map is constructed to provide logical structural support for the subsequent random filling of pigeon elements.

[0045] S130. Based on the map preference settings and the preset distribution rules and preset element attributes corresponding to each type of rogue element, a random map is generated by randomly filling various types of rogue elements into the basic map framework.

[0046] In some embodiments, based on map preference settings and preset distribution rules and preset element attributes corresponding to various roguelike elements, a random filling operation of roguelike elements is performed on the constructed basic map framework to generate a random map with high variability and replayability. Map preference settings are used to limit macro-distribution strategies such as overall filling ratio, element sparsity, and priority of special event areas; preset distribution rules refer to the probability of occurrence, positional constraints, and combination generation rules of various roguelike elements in the map space; preset element attributes are used to describe the functional type, level parameters, behavior patterns, or interaction methods of each element.

[0047] In the actual filling process, a combination of random number generation functions and rule-based filtering mechanisms can be used to traverse the spatial grid points or functional areas of the map frame layer by layer, determine whether to place elements and which type of elements to place, and determine their parameter configuration based on element attributes. For example, under a preference for resource scarcity, the distribution probability of rare item-type elements will be significantly reduced; while under a preference for high-intensity combat, high-level enemy-type elements may be filled in multiple partitions.

[0048] In one embodiment, the basic map frame can be divided into functional areas before element filling is performed. The filling boundaries of specific elements can be restricted based on the division results to ensure the functional integrity and playability of the overall structure.

[0049] In one embodiment, the preset distribution rules may include location-dependent rules, such as high-value rewards being generated only in remote areas or areas requiring specific path access.

[0050] In one embodiment, the filling process supports a dynamic conflict detection mechanism to avoid element overlap or unreasonable combinations, and can reselect the filling position or replace the element type based on the detection results.

[0051] Optionally, Figure 3 A flowchart illustrating the random filling of pigeon elements according to an embodiment of this application is provided. (Reference) Figure 3 The method for randomly filling in pigeon elements specifically includes: S1301. Based on the map preference settings, modify the preset distribution rules and preset element attributes of various types of pigeon elements to obtain the preference distribution rules and preference element attributes corresponding to each type of pigeon element.

[0052] For example, firstly, based on map preference settings, the preset distribution rules and preset element attributes of various roguelike elements are modified to generate element configuration strategies that better match player expectations or design goals. The preset distribution rules characterize the spatial distribution characteristics of elements on the map, such as distribution area, density, and proximity relationships; the preset element attributes characterize the basic behavioral characteristics of elements, such as function type, intensity level, and interaction mechanism; the preferred distribution rules and preferred element attributes are the result of adjustments based on the presets and map preferences.

[0053] In one embodiment, map preference settings may include indicators such as element richness, exploration orientation, combat intensity, and resource density, which are used to guide the changing trends of various rogue elements in terms of distribution range, quantity, and characteristics.

[0054] In one embodiment, modifying the preference for a preset distribution rule may include adjusting the frequency of occurrence of a specific element, restricting its generation area, or setting the combination probability of adjacent elements.

[0055] In one embodiment, modifying the preferences for preset element attributes may include increasing the attack power or movement speed of a certain type of enemy, adding a hiding mechanism for resource elements, or setting interactive elements to be triggered only once.

[0056] In one embodiment, the resulting preference distribution rules and preference element attributes will be used as the generation input for the subsequent map filling process to achieve a deep integration of map style and rogue element content.

[0057] S1302. Determine the generation priority of each type of pigeon element according to the preference distribution rules, and determine the generation probability of each type of pigeon element according to the preference distribution rules and preference element attributes.

[0058] For example, the generation priority is first determined based on the preference distribution rules of various types of elements. This priority indicates the order in which different elements are arranged during the random map generation process, ensuring that key elements are prioritized and auxiliary elements are appropriately supplemented. The generation priority characterizes the execution order of various elements during spatial layout; a higher value indicates a higher priority in generation.

[0059] Next, based on the preference distribution rules and attribute of various types of pigeon elements, the corresponding generation probability is determined to control the actual generation frequency of elements on the map, ensuring the randomness and balance of the overall distribution. The generation probability represents the likelihood of each type of element being generated under specific conditions and can be dynamically adjusted based on factors such as its rarity, interaction strength, or strategic value.

[0060] In one embodiment, the method for determining the generation priority may include: prioritizing the allocation of key information nodes, followed by the placement of resource points and battle points, and finally filling in decorative or disruptive elements, in order to ensure the integrity of map functionality and the consistency of player experience.

[0061] In one embodiment, the generation probability can be calculated by fusing parameters such as target density, regional constraints, combinatorial logic, and rarity coefficient and triggering mechanism in the preference element attributes in the preference distribution rules to generate a dynamically adjusted generation probability vector.

[0062] In one embodiment, to further enhance the diversity of generation, a perturbation factor can be introduced to locally perturb the generation probability, avoiding repetitive patterns in the distribution of map elements, thereby improving the map's playability and exploration value.

[0063] Optionally, Figure 4 A flowchart illustrating the priority determination of pigeon element generation according to an embodiment of this application is provided. (Reference) Figure 4 The method for determining the priority of pigeon element generation specifically includes: S13021. Extract the mutual exclusion relationship and the dependency relationship of each element from the preference distribution rules of various types of pigeon elements, and calculate the element restriction index corresponding to each type of pigeon element based on the mutual exclusion relationship and the dependency relationship.

[0064] For example, the mutual exclusion and dependency relationships of each type of rogue element are first extracted from the preference distribution rules of each type of rogue element. Mutual exclusion relationships characterize the constraint logic that a certain type of rogue element should not coexist with other specific elements in the same map or specific area; for example, two strong enemy types cannot appear on the same node simultaneously. Dependency relationships describe that the generation of a certain type of rogue element depends on the prior generation or proximity of another type of element; for example, some treasure chest types need to be attached to specific types of rooms for generation.

[0065] Next, based on the extracted mutual exclusion and dependency relationships of elements, the element constraint index corresponding to each type of pigeon element is calculated to quantitatively describe the strength of the structural constraints on the generation of such elements in the map. The element constraint index can be understood as a negative factor affecting the degree of freedom of generation; the higher the value, the lower the flexibility of the element's arrangement and the stricter the contextual conditions upon which its generation depends.

[0066] In one embodiment, the calculation method of the element restriction index may include: for each type of pigeon element, counting the number of mutually exclusive objects and the mutual exclusion strength involved in its mutual exclusion relationship to obtain the mutual exclusion constraint value; counting the number of dependent objects associated in its dependency relationship and the dependency strength to obtain the dependency constraint value; and weighting and fusing the mutual exclusion constraint value and the dependency constraint value to obtain the final element restriction index.

[0067] In one embodiment, the element restriction index can be used as one of the factors for adjusting the subsequent generation priority and generation probability to avoid layout conflicts or logical breaks, thereby improving the rationality of map generation and gameplay.

[0068] S13022. Sort the various types of pigeon elements based on the element restriction index, and determine the corresponding generation priority according to the sorting results of the various types of pigeon elements.

[0069] For example, all rogue elements are first sorted based on their respective element constraint indices. The element constraint index is used to characterize the constraint strength of each type of rogue element in map generation. The higher the value, the more difficult it is for the element to be reasonably placed in the map. Therefore, during the sorting process, elements with higher element constraint indices are usually placed at the front and given priority in generation planning to avoid the inability to place them due to space or logic limitations in the later stages of generation.

[0070] Based on the element restriction index of various pigeon elements, sort them from high to low or according to the priority strategy set by the system; give higher generation priority to the elements at the top of the sorting results to ensure that they are processed and filled first in the map generation process; give lower generation priority to the elements at the bottom of the sorting results and postpone their arrangement until the spatial and dependency conditions are met.

[0071] In one embodiment, the generation priority can be represented by multi-level labels or numerical weights, such as being divided into three levels: "high priority", "medium priority" and "low priority", or quantified in the form of numerical values ​​from 1 to 10, so that the subsequent generation algorithm can perform the arrangement operation of the pigeon elements in priority order.

[0072] By employing the above methods, element types with stringent logical constraints and complex layout conditions can be prioritized in the map generation process, thereby improving the success rate of map generation and the stability of game operation.

[0073] S1303. Based on the generation priority and generation probability of various types of pigeon elements, randomly fill various types of pigeon elements on the basic map framework.

[0074] For example, firstly, based on the generation priority and probability of each type of rogue element, a random filling operation is performed step by step within the basic map framework. Before filling begins, according to the aforementioned sorting results, all rogue elements are arranged from high to low generation priority. Then, according to the generation probability of each type of element, a certain random strategy is used to try to allocate the position of the element in the map framework in turn, ensuring that the filling process satisfies both logical constraints and has a certain degree of map diversity and randomness.

[0075] In one embodiment, the random filling process includes the following steps: traversing all types of pigeon elements, prioritizing elements with higher generation priority; for the currently processed pigeon element, determining whether to perform a filling operation based on its generation probability, which can be done by comparing a pseudo-random function with a set probability; if it is determined that the element should be filled, then selecting available locations that meet the conditions from the current map frame based on the element's space occupancy requirements, terrain adaptability, mutual exclusion / dependency, etc.; randomly selecting a target location from the set of available locations and placing the current pigeon element at that location; if there is no location that meets the conditions, it is recorded as a placement failure, and a compensation attempt can be made after the subsequent processing of low-priority elements.

[0076] By combining generation priority to control the filling order, combining generation probability to introduce randomness, and constraining the filling position based on terrain and logical rules, this process maximizes the diversity and playability of map content while ensuring map usability.

[0077] Optionally, Figure 5 A flowchart of the pigeon element filling based on element adaptation mapping provided in this application embodiment is given. (Reference) Figure 5 The specific methods for filling elements in a pigeon based on element adaptation mapping include: S13031. Based on the preset element attributes of various types of pigeon elements, match their respective candidate fill areas on the basic map framework.

[0078] For example, firstly, candidate filling areas are matched on the basic map framework based on the preset element attributes of various rogue elements. The preset element attributes of each type of rogue element include, but are not limited to, environmental adaptability, spatial requirements, and interactivity requirements, which are used to limit the area where it can be deployed.

[0079] During the matching process, the basic map frame is scanned, and regions that meet the preset attribute conditions of the current rogue element are marked as candidate fill regions. This process may include: traversing all deployable regions of the map frame; for each map region, checking whether its environmental adaptability matches that of the current rogue element, such as whether the terrain type meets the requirements and whether the lighting is sufficient; determining whether the region has enough continuous free squares and meets specific structural shapes based on spatial requirements; if the rogue element has interactive requirements, further checking whether the region has the corresponding interactive conditions, such as proximity to the main path and accessibility; if all the above conditions are met, the region is marked as a candidate fill region, and relevant location information and available space distribution are recorded.

[0080] In one embodiment, the matching process can be implemented through a rule engine or a multi-dimensional conditional filtering algorithm to support efficient processing of complex attribute combinations and large-scale map spaces. This step provides a feasible deployment basis for subsequent random filling of rogue elements while maintaining the rationality of the map structure.

[0081] S13032. Based on the candidate filling areas corresponding to each type of pigeon element, establish an element adaptation mapping table for each type of pigeon element on the basic map framework.

[0082] For example, firstly, based on the identified candidate fill areas for each type of pigeon element, an element adaptation mapping table is constructed on the basic map framework. This mapping table represents the spatial distribution characteristics and fillability evaluation results of each type of pigeon element in the current map structure, thereby supporting subsequent element filling strategy selection and conflict avoidance.

[0083] The process of constructing an element adaptation mapping table may include: associating and registering each type of pigeon element with all its matching candidate filling regions, recording the spatial coordinates, boundary, capacity, shape adaptability level, etc. of each region; calculating an environmental adaptability score for each candidate filling region based on the degree of matching between the region and the preset element attributes of the corresponding pigeon element, such as terrain matching score, adjacent element conflict index, and interaction requirement support; generating a filling priority order table for the current pigeon element in different candidate regions based on the environmental adaptability score and the aforementioned generation priority, which is used to guide the point selection strategy in the subsequent filling process; marking potential conflict points in the candidate filling regions for the extracted element mutual exclusion relationships, and recording the intersection with other mutual exclusion element candidate regions to avoid logical conflicts in subsequent deployment.

[0084] In one alternative implementation, the element adaptation map is organized using a hash map structure or a two-dimensional coordinate index structure to facilitate fast querying, dynamic updates, and state synchronization across multiple generation processes.

[0085] By establishing a mapping table, a global understanding of the spatial deployment possibilities of various pigeon elements can be achieved, providing structured support for strategic filling, conflict control, and map diversity adjustment in subsequent map generation.

[0086] S13033. Based on the generation priority and generation probability of various types of pigeon elements, randomly fill various types of pigeon elements in the candidate filling areas corresponding to each type of pigeon element according to the element adaptation mapping table.

[0087] For example, firstly, based on the generation priority and generation probability of various types of rogue elements, and combined with an element adaptation mapping table, random filling is performed within the candidate filling areas corresponding to each type of rogue element. Here, generation priority indicates the priority weight of each type of rogue element in the filling order, generation probability indicates the likelihood of each type of rogue element being selected for filling within the candidate filling area, and the element adaptation mapping table indicates the adaptation relationship between each type of rogue element and the candidate filling area, as well as its adaptation score.

[0088] In one embodiment, based on the element adaptation mapping table, various types of pigeon elements are processed in descending order of generation priority, with high-priority elements being filled first.

[0089] In one embodiment, the random filling process includes: selecting a filling position in a weighted random manner within the candidate filling area based on the generation probability, and dynamically adjusting the filling scheme by combining the mutual exclusion and dependency relationships between elements.

[0090] In one embodiment, random filling employs a weighted random sampling algorithm to achieve a balance between the randomness and adaptability of element distribution.

[0091] Optionally, the random filling of various types of pigeon elements onto the basic map framework based on the generation priority and generation probability of different types of pigeon elements includes: Based on the generation priority of various types of pigeon elements, various types of pigeon elements are randomly filled into the basic map framework according to their respective generation probabilities.

[0092] For example, based on the generation priority and generation probability of various types of rogue elements, various rogue elements are randomly filled into the basic map framework. Here, the generation priority indicates the order in which various types of rogue elements are filled, and the generation probability represents the probability of random selection of various types of rogue elements during the filling process.

[0093] In one embodiment, refer to Figure 6This diagram illustrates a random map generated by randomly filling a basic map framework. During the random map filling process, considering the significant dependency constraints between different types of roguelike elements in the terrain space, a dependency modeling and priority ranking mechanism is introduced during map generation. Different elements have spatial association rules; for example, treasure chests usually spawn alongside monsters; slime-type enemies are preferentially distributed near grassland areas; spider-type enemies tend to spawn at the edge of forests; villages need to be located near rivers; and castles and mines need to be placed close to mountains. This dependency relationship guides the layout logic of map elements. Based on the aforementioned spatial dependency characteristics, basic terrain-dependent elements P1 include core terrain features such as mountains and rivers, which serve as anchor points for the generation of other elements and are prioritized for generation to provide spatial reference and constraints. Environment-dependent structures P2, such as villages attached to rivers and castles and mines attached to mountains, require layout based on the positional constraints of P1 elements. Resource and interaction nodes P3, such as treasure chests, supply points, and quest triggering devices, are closely related to player interaction and require reasonable distribution in conjunction with terrain and quest guidance logic. Hostile creature groups P4 include monsters such as slimes and spiders, which are usually generated around resource nodes or environmental boundaries, and their generation requires reference to P2 / P3 elements.

[0094] In one embodiment, the various types of pigeon elements are first processed in descending order of their generation priority.

[0095] In one embodiment, for each type of pigeon element, a suitable location is randomly selected on the basic map framework to fill it based on its corresponding generation probability.

[0096] In one embodiment, the random filling process takes into account both the mutual exclusion and dependency relationships between elements to ensure the rationality and diversity of the generated map.

[0097] Optionally, Figure 7 A flowchart of the random map adjustment provided in an embodiment of this application is given. (Reference) Figure 7 The random map adjustment method specifically includes: S140. Display the random map, and in response to the adjustment operation of the pigeon element in the random map, locate the adjustment area where the adjusted pigeon element is located.

[0098] For example, the generated random map is displayed. The random map includes multiple map regions and corresponding rogue elements, filled based on the generation priority and probability of various rogue elements. Users can view the entirety or a partial area of ​​the random map in the client interface and adjust the rogue elements within it.

[0099] In one embodiment, in response to a user's adjustment operation on a rogue element in a random map, such as moving its position, replacing it, or modifying its attributes, the adjustment behavior is parsed to determine the rogue element being adjusted, and the map location of the rogue element being adjusted is further located, and the local map region corresponding to that location is identified as the adjustment area.

[0100] In one embodiment, the method for locating the adjustment area can be as follows: based on the original location coordinates of the adjusted pigeon element and the adjusted target location coordinates, map tile information containing the coordinate range is determined from the basic map framework, and the related element adaptation mapping table records are extracted, thereby completing the area-level positioning. This adjustment area can subsequently be used for functions such as updating element layout, rebuilding adaptation relationships, or recalculating map scores.

[0101] S150. Extract the adjustment distribution pattern and adjustment element attributes of the adjusted pigeon elements from the adjustment area, and determine the other areas in the random map after removing the adjustment area.

[0102] For example, the distribution status and attribute information of the adjusted pigeon elements within the adjusted area obtained from the positioning are extracted to form the corresponding adjusted distribution pattern and adjusted element attributes. The adjusted distribution pattern refers to the spatial distribution characteristics of the adjusted pigeon elements within the adjusted area, such as concentration, balance, and distance relationships between elements; the adjusted element attributes refer to the attribute parameters that the pigeon element possesses after adjustment, such as element level, functional characteristics, interaction type, or state value.

[0103] In one embodiment, the method for extracting and adjusting the distribution pattern can be as follows: perform spatial statistical analysis on the pigeon elements in the adjustment area in the map coordinate system, and combine the current distribution with a preset distribution model, such as Gaussian distribution, Poisson distribution, grid density, etc., to determine the new distribution pattern parameters.

[0104] In one embodiment, the method for extracting and adjusting element attributes can be: reading the attribute descriptions in the adjusted element settings or default configuration file on the client side to form an updated attribute set.

[0105] In one embodiment, after extracting the adjustment distribution pattern and adjustment element attributes within the adjustment area, all map areas in the random map other than the adjustment area are identified as "other areas". These other areas will be used as reference or target areas in subsequent regeneration, local optimization, or adaptation adjustments, thereby ensuring the coherence of the overall map structure and the effectiveness of local adjustments.

[0106] S160. Based on the adjustment distribution pattern and the adjustment element attributes, randomly fill other areas in the random map with the adjusted pigeon element.

[0107] For example, based on the adjustment distribution pattern and adjustment element attributes extracted from the adjustment area, the refilling operation of the adjusted pigeon elements is performed in the remaining areas after removing the adjustment area in the random map, thereby ensuring the overall... Figure 1 Under the premise of consistency, distribution expansion and structural completion are carried out. The adjustment of distribution patterns characterizes the distribution pattern of the pigeon elements within the adjustment area, which can include clustered, discrete, grid-like, path-dependent, etc. The adjustment of element attributes characterizes parameters such as the type, function, level, state, or interaction characteristics of the pigeon element. Guided by these patterns and attributes, candidate filling positions that meet the spatial structure and attribute requirements are selected in other areas, and the elements are randomly deployed.

[0108] In one embodiment, the random filling method can be as follows: A candidate point set is generated based on the distribution pattern of the adjustment elements. Then, combined with the spatial adaptation conditions in the element attributes, several target positions that meet the layout and functional requirements are selected. Adjusted pigeon elements are then sequentially filled into these positions. To ensure filling quality, a generation probability or penalty function can be introduced to avoid excessive element concentration or conflicts with existing elements.

[0109] In one embodiment, to further improve generation efficiency and map balance, conflict detection and compatibility assessment can be performed during the filling process. If there are structural conflicts, mutually exclusive element relationships, or other situations that do not meet the rules at the filling location, the current filling operation is rolled back and a replacement scheme is attempted, thereby achieving high-fidelity migration of the adjusted regional features.

[0110] Based on the above embodiments, Figure 8 This is a schematic diagram of the structure of the random map generation device based on pigeon elements provided in an embodiment of this application. (Reference) Figure 8 The random map generation device based on pigeon elements provided in this embodiment specifically includes: an acquisition module 21, a frame module 22, and a filling module 23.

[0111] The acquisition module 21 is configured to acquire the map preference settings and rogue element parameters of the map to be generated, wherein the rogue element parameters include several types of rogue elements and their respective preset distribution rules and preset element attributes; the frame module 22 is configured to generate a basic map frame of the map to be generated based on the map preference settings and the rogue element parameters; and the filling module 23 is configured to randomly fill various types of rogue elements on the basic map frame to generate a random map according to the map preference settings and the preset distribution rules and preset element attributes of each type of rogue element.

[0112] Based on the above embodiments, the framework module 22 includes: a preference extraction unit, configured to extract the map size, terrain preference, and map difficulty of the map to be generated from the map preference settings; a space occupancy unit, configured to determine the space occupancy requirements of various types of rogue elements according to the preset distribution rules and preset element attributes corresponding to each type of rogue element in the rogue element parameters; and a map framework unit, configured to generate the basic map framework of the map to be generated based on the map size, terrain preference, map difficulty, and space occupancy requirements.

[0113] Based on the above embodiments, the filling module 23 includes: a preference adjustment unit, configured to modify the preset distribution rules and preset element attributes of various types of rogue elements based on the map preference settings, to obtain the preference distribution rules and preference element attributes corresponding to each type of rogue element; a priority unit, configured to determine the corresponding generation priority of each type of rogue element according to the preference distribution rules; a generation probability unit, configured to determine the corresponding generation probability of each type of rogue element according to the preference distribution rules and preference element attributes; and an element filling unit, configured to randomly fill various types of rogue elements on the basic map framework based on the generation priority and generation probability of various types of rogue elements.

[0114] Based on the above embodiments, the priority unit includes: a restriction index subunit, configured to extract the corresponding mutual exclusion relationship and element dependency relationship from the preference distribution rules of various types of pigeon elements, and calculate the element restriction index corresponding to each type of pigeon element based on the mutual exclusion relationship and the element dependency relationship; and a priority subunit, configured to sort various types of pigeon elements based on the element restriction index, and determine the corresponding generation priority according to the sorting result of various types of pigeon elements.

[0115] Based on the above embodiments, the element filling unit includes: a candidate region subunit, configured to match corresponding candidate filling regions on the basic map framework based on preset element attributes of various types of rogue elements; an element mapping subunit, configured to establish an element adaptation mapping table on the basic map framework based on the candidate filling regions corresponding to each type of rogue element; and an element filling subunit, configured to randomly fill various types of rogue elements in the corresponding candidate filling regions according to the element adaptation mapping table, based on the generation priority and generation probability of various types of rogue elements.

[0116] Based on the above embodiments, the element filling unit further includes: a sequential filling subunit, configured to randomly fill various types of pigeon elements on the basic map frame according to their respective generation probabilities based on the generation priority of various types of pigeon elements.

[0117] Based on the above embodiments, the random map generation device based on pigeon elements further includes: an adjustment area module, configured to display the random map and, in response to an adjustment operation on pigeon elements in the random map, locate the adjustment area where the adjusted pigeon elements are located; an other area module, configured to extract the adjustment distribution pattern and adjustment element attributes of the adjusted pigeon elements from the adjustment area, and determine other areas in the random map after removing the adjustment area; and an adjustment filling module, configured to randomly fill the adjusted pigeon elements in other areas of the random map according to the adjustment distribution pattern and the adjustment element attributes.

[0118] The random map generation device based on pigeon elements provided in this application embodiment achieves intelligent parsing of map preference settings and pigeon element parameters, logical construction of basic map structure, and precise control of element-level priority filling process by constructing a structured component system consisting of multiple functional modules such as an acquisition module, a frame module, and a filling module. Based on the user-defined map preferences and pigeon element parameters, the device automatically extracts map size, terrain preference, map difficulty, element distribution rules, and attribute information, and uses the frame module to construct the basic spatial framework structure of the map. The filling module within the device achieves hierarchical control of the pigeon element filling process by introducing preference adjustment, priority scheduling, generation probability control, and candidate region mapping mechanisms. The device calculates an element constraint index based on the mutual exclusion and dependency relationships between elements, generates a global filling priority table through a sorting mechanism, and combines candidate region matching and mapping table construction techniques to achieve random filling of various elements within logically feasible areas. Furthermore, the device supports sequential filling mode, filling elements according to priority order to ensure the interpretability and strategy depth of the generated map structure. Furthermore, to enhance the adjustability and user interactivity of the generated map, the device integrates an adjustment region module with other region modules. This structure supports dynamic positional adjustments to roguelike elements in the generated map and, based on the distribution patterns and element attributes extracted from the adjusted region, performs differentiated refilling operations in the remaining unadjusted regions, achieving both local area reconstruction and global consistency maintenance. Through this modular structure and intelligent control mechanism, this device effectively replaces the traditional generation method that relies on preset map tiles and static combinations, achieving a high degree of automation, parameter-driven approach, and logical consistency in the roguelike map generation process. This system not only improves the map's playability and randomness but also possesses strong scene adaptability and future expansion potential, providing a higher-quality map building solution for roguelike games.

[0119] The random map generation device based on pigeon elements provided in this application embodiment can be used to execute the random map generation method based on pigeon elements provided in the above embodiment, and has corresponding functions and beneficial effects.

[0120] Figure 9 This is a schematic diagram of the structure of a random map generation device based on pigeon elements provided in an embodiment of this application. (Refer to...) Figure 9 The random map generation device based on pigeon elements includes: a processor 31, a memory 32, a communication device 33, an input device 34, and an output device 35. The number of processors 31 and the number of memories 32 in the random map generation device based on pigeon elements can be one or more. The processor 31, memory 32, communication device 33, input device 34, and output device 35 of the random map generation device based on pigeon elements can be connected via a bus or other means.

[0121] The memory 32, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as program instructions / modules corresponding to the random map generation method based on pigeon elements in any embodiment of this application (e.g., the acquisition module 21, frame module 22, and filling module 23 in the random map generation device based on pigeon elements). The memory 32 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the device, etc. Furthermore, the memory 32 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0122] The communication device 33 is used for data transmission.

[0123] The processor 31 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 32, thereby realizing the above-mentioned random map generation method based on pigeon elements.

[0124] Input device 34 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the device. Output device 35 may include display devices such as a display screen.

[0125] The random map generation device based on pigeon elements provided above can be used to execute the random map generation method based on pigeon elements provided in the above embodiments, and has corresponding functions and beneficial effects.

[0126] This application embodiment also provides a storage medium containing computer-executable instructions. When executed by a computer processor, the computer-executable instructions are used to execute a method for generating random maps based on rogue elements. The method includes: obtaining map preference settings and rogue element parameters of a map to be generated, wherein the rogue element parameters include several types of rogue elements and their respective preset distribution rules and preset element attributes; generating a basic map framework of the map to be generated based on the map preference settings and the rogue element parameters; and randomly filling various types of rogue elements into the basic map framework to generate a random map according to the map preference settings and the preset distribution rules and preset element attributes corresponding to each type of rogue element.

[0127] Storage medium – any type of memory device or storage device. The term “storage medium” is intended to include: mounting media, such as CD-ROM, floppy disk, or magnetic tape devices; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. Storage medium may also include other types of memory or combinations thereof. Furthermore, storage medium may reside in a first computer system in which a program is executed, or it may reside in a different second computer system connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term “storage medium” can include two or more storage media residing in different locations (e.g., in different computer systems connected via a network). Storage medium may store program instructions (e.g., specifically implemented as a computer program) executable by one or more processors.

[0128] Of course, the computer-executable instructions provided in the embodiments of this application are not limited to the random map generation method based on pigeon elements as described above, but can also execute related operations in the random map generation method based on pigeon elements provided in any embodiment of this application.

[0129] The random map generation device, storage medium, and random map generation equipment based on pigeon elements provided in the above embodiments can execute the random map generation method based on pigeon elements provided in any embodiment of this application. For technical details not described in detail in the above embodiments, please refer to the random map generation method based on pigeon elements provided in any embodiment of this application.

[0130] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of this application. The scope of this application is determined by the scope of the claims.

Claims

1. A method for generating random maps based on pigeon elements, characterized in that, include: Obtain the map preference settings and rogue element parameters of the map to be generated. The rogue element parameters include several types of rogue elements and their respective preset distribution rules and preset element attributes. The basic map framework of the map to be generated is generated based on the map preference settings and the pigeon element parameters. Based on the map preference settings and the preset distribution rules and preset element attributes corresponding to each type of rogue element, a random map is generated by randomly filling various rogue elements on the basic map framework. Display the random map, and in response to the adjustment operation of the pigeon element in the random map, locate the adjustment area where the adjusted pigeon element is located; Extract the adjustment distribution pattern and adjustment element attributes of the adjusted pigeon elements from the adjustment area, and determine the other areas in the random map after removing the adjustment area; Based on the adjustment distribution pattern and the adjustment element attributes, the adjusted pigeon element is randomly filled into other areas of the random map; The step of randomly filling the basic map framework with various types of rogue elements according to the map preference settings and the preset distribution rules and preset element attributes corresponding to each type of rogue element includes: Based on the map preference settings, the preset distribution rules and preset element attributes of various types of pigeon elements are modified to obtain the preference distribution rules and preference element attributes corresponding to each type of pigeon element. The generation priority of each type of meat pigeon element is determined according to the preference distribution rules of each type of meat pigeon element, and the generation probability of each type of meat pigeon element is determined according to the preference distribution rules and preference element attributes. Based on the generation priority and generation probability of various types of pigeon elements, various types of pigeon elements are randomly filled on the basic map framework. The step of determining the generation priority of each type of pigeon element according to the preference distribution rules includes: Extract the mutual exclusion and dependency relationships of each type of pigeon element from the preference distribution rules, and calculate the element restriction index corresponding to each type of pigeon element based on the mutual exclusion and dependency relationships. Based on the element restriction index, various types of pigeon elements are sorted, and their respective generation priorities are determined according to the sorting results.

2. The random map generation method based on pigeon elements according to claim 1, characterized in that, The process of generating the basic map framework for the map to be generated based on the map preference settings and the pigeon element parameters includes: Extract the map size, terrain preference, and map difficulty of the map to be generated from the map preference settings; Based on the preset distribution rules and preset element attributes corresponding to each type of pigeon element in the pigeon element parameters, the space occupancy requirements of each type of pigeon element are determined. Based on the map size, terrain preference, map difficulty, and space requirements, a basic map framework for the map to be generated is produced.

3. The random map generation method based on pigeon elements according to claim 1, characterized in that, Based on the generation priority and probability of various types of pigeon elements, various types of pigeon elements are randomly filled into the basic map framework, including: Based on the preset element attributes of various meat pigeon elements, their respective candidate filling areas are matched on the basic map framework. Based on the candidate filling areas corresponding to each type of meat pigeon element, establish an element adaptation mapping table for each type of meat pigeon element on the basic map framework. Based on the generation priority and generation probability of various types of pigeon elements, various types of pigeon elements are randomly filled into the candidate filling areas corresponding to each type of pigeon element according to the element adaptation mapping table.

4. The random map generation method based on pigeon elements according to claim 1, characterized in that, Based on the generation priority and probability of various types of pigeon elements, various types of pigeon elements are randomly filled into the basic map framework, including: Based on the generation priority of various types of pigeon elements, various types of pigeon elements are randomly filled into the basic map framework according to their respective generation probabilities.

5. A random map generation device based on pigeon elements, characterized in that, The random map generation device based on pigeon elements is used to execute the random map generation method based on pigeon elements as described in any one of claims 1-4, wherein the random map generation device based on pigeon elements comprises: The acquisition module is used to acquire the map preference settings and rogue element parameters of the map to be generated. The rogue element parameters include several types of rogue elements and their respective preset distribution rules and preset element attributes. The framework module is used to generate the basic map framework of the map to be generated based on the map preference settings and the rogue element parameters; The fill module is used to randomly fill various types of rogue elements on the basic map framework to generate a random map based on the map preference settings and the preset distribution rules and preset element attributes corresponding to each type of rogue element.

6. A random map generation device based on pigeon elements, characterized in that, include: One or more processors; A memory that stores one or more programs, which, when executed by one or more processors, enable the one or more processors to implement the random map generation method based on pigeon elements as described in any one of claims 1-4.

7. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the random map generation method based on pigeon elements as described in any one of claims 1-4.

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