75 results about "Game design" patented technology

The invention provides a dynamic game difficulty self-adaptive adjustment method and system based on user behavior feedback, and relates to the technical field of game design, the method comprises the following steps: carrying out dynamic weighting calculation based on a difficulty adaptation index, generating a dynamic difficulty correction coefficient in combination with user real-time physiological feedback data, and adjusting the dynamic game difficulty according to the dynamic difficulty correction coefficient; the dynamic difficulty correction coefficient comprises a scene complexity adjustment parameter and an interaction response threshold adjustment parameter; inputting the user feedback parameter set into an image feature weight distributor, dynamically adjusting weight distribution of image retrieval feature vectors according to user attention distribution data and operation delay parameters, and generating an optimized scene element retrieval strategy; and performing feature space mapping on the dynamic difficulty correction coefficient and the optimized scene element retrieval strategy, and generating a final game difficulty control instruction set through nonlinear superposition. Game design can be optimized, and game adaptability and flexibility are enhanced.

Systems and methods for developing a game of chance. The game of chance being at least partially developed using specialized artificial intelligence (AI) game design systems or specialized artificial intelligence game design system modules or components which may include different types of machine learning or training techniques, including supervised, unsupervised, reinforced, deep learning and artificial neural networks and / or similar and may include analyzing past game performance utilizing full, partial or estimated prior game performance data for developing game math models, game mechanics and associated game programming, game art and graphics, game animations, game sound effects, partial or full game development, game computer code, game quality assurance diagnosis and editing, game analytics, compliance, help screens, and predictive models, etc.

The invention belongs to the technical field of game design, and discloses a method for applying an AI agent generation task system to a scenic spot script killer system, which comprises the following steps: generating an evaluation mode according to the type of the script killer, evaluating the related ability of a player under the type, generating a player portrait, sensing the current environment state, and generating an environment portrait; an initial task is allocated for each player, multi-agent simulation is performed by using an MARL model, narrative and scheduling targets are formulated through a strategic layer, the strategic layer is decomposed into specific tasks, personalized tasks are generated in combination with a reward function and a plot security guard mechanism, and difficulty coefficients of the players are dynamically adjusted; and the execution module receives the output of the dynamic decision module, forms a final task through assembly and rendering, and issues the final task to a player terminal, players receive the task and interact, automatically verify the task completion state, and feed back the task completion state to the multi-mode environment sensing module, so that circulation is formed, and dynamic generation of the scenic spot script killing task is realized.

The invention provides a text-driven 3D model generation method and system for game development, and the method comprises the steps: obtaining a target text description set of a game design scene, extracting key information to obtain a scene feature set, building a correlation mapping relation between scene features and 3D model elements, calling a preset model generation frame to generate initial 3D model data, and carrying out the recognition of the initial 3D model data. According to the method, the initial 3D model data is subjected to structure adjustment according to the model adaptation constraint condition of game development, a final 3D model output result meeting the development requirement is obtained, automatic generation from complex text description to a high-quality 3D model is achieved, the generation efficiency and quality of the 3D model in game development are remarkably improved, the development cost is reduced, and the development efficiency is improved. And a convenient and efficient 3D model generation solution is provided for game developers.

The invention belongs to the field of adaptive analysis design of confrontation game difficulty, and discloses an action game design analysis method, system and device and a storage medium. By constructing the behavior feature data set and evaluating the habitual confidence, the behavior habits of the player in the confrontation process can be accurately grasped, a reliable basis is provided for subsequent difficulty adjustment, and the problem of insufficient player behavior analysis in the prior art is solved. According to the method, the confrontation action-difficulty mapping relation is constructed based on a large amount of test data and objective division logic, so that difficulty division better conforms to actual feelings of players, and the defect that existing difficulty division is not scientific is overcome. According to the method, autonomous adjustment of the difficulty of the simulated role confrontation action is achieved by evaluating the adaptability of the player, the adjustment reasonability is analyzed, it is ensured that the difficulty adjustment is suitable for the player, the playability of the game and the game experience of the player are improved, and the defect that tactical adjustment lacks autonomy and reasonability evaluation in the prior art is overcome.

The invention discloses a game commodity price information configuration method and device, equipment and a storage medium, and relates to the technical field of game design. The method comprises the following steps: acquiring a preset commodity price template; determining a to-be-set payment channel of a current to-be-configured game commodity, and positioning a matched price level corresponding to the to-be-set payment channel in a plurality of price levels of the commodity price template; and querying a channel support region of the to-be-set payment channel, obtaining a commodity region price corresponding to the channel support region in the matched price level in the commodity price template as a channel region price, and configuring the channel region price as a commodity channel price of the to-be-set payment channel of the game commodity. According to the scheme, through the automatic commodity price information configuration method, the consistency of price information configuration of each channel and region of the game commodity is realized, and the efficiency and the accuracy of the price information configuration of the game commodity are improved.

Systems and methods for developing a game of chance. The game of chance being at least partially developed using specialized artificial intelligence (AI) game design systems or specialized artificial intelligence game design system modules or components which may include different types of machine learning or training techniques, including supervised, unsupervised, reinforced, deep learning and artificial neural networks and / or similar and may include analyzing past game performance utilizing full, partial or estimated prior game performance data for developing slot machine game math models, slot machine game mechanics and associated game programming, slot machine game art and graphics, slot machine animations, slot machine game sound effects, partial or full slot machine game development, slot machine computer code, slot machine game quality assurance diagnosis and editing, slot machine game analytics, slot machine compliance, slot machine help screens, and slot game predictive models, etc.

1. The name of the design product: toy (magnetic sensory strategy game design 2). 2. The use of the design product: for toys, with stress-relieving effect. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The application discloses an AI-driven game 3D asset modular generation and multi-terminal intelligent adaptation method and system. The method comprises the following steps: firstly, a multi-task deep learning model integrating semantic segmentation and graph convolution network is used to perform structural feature recognition and disassembly on an input 2D game design drawing, and a structured descriptor containing component semantics, key points and topological relations is generated. Secondly, a generative AI model is used to generate a parameterized 3D geometric body based on the descriptor, and the parameterized 3D geometric body is encapsulated into an independent asset module with a standardized connection interface to construct a searchable modular asset library. Finally, according to a target terminal performance knowledge graph, a reinforcement learning-based adaptation agent is used to automatically optimize the rendering parameters of the modular assets, and a closed-loop verification of performance and visual consistency is performed in a simulation environment, and an adapted asset package is output.

This application discloses a method, system, device, and medium for generating game parameters, relating to the technical field of game design. The method includes: performing correlation mining on the multidimensional behavioral data to obtain an emotional state feature sequence; constructing a personalized emotional response model for the target player based on the emotional state feature sequence, and generating a target emotional state feature trajectory for the target player based on an emotional change template and the personalized emotional response model; acquiring historical game interaction data and constructing an emotional state prediction model based on the historical game interaction data; calling the emotional state prediction model and searching in the game plot parameter space using a Bayesian algorithm to generate target game plot parameters, such that the emotional state feature prediction sequence corresponding to the target game plot parameters matches the target emotional state feature trajectory. This application has the effect of enhancing the personalized immersive experience of players in the game plot.

1. Name of the designed product: toy (magnetic sensory strategy game design 1). 2. Use of the designed product: for toys, with stress-relieving effect. 3. Design points of the designed product: in shape. 4. Picture or photo that best indicates the design points: design 1 perspective view 1. 5. Design 1 is designated as the basic design.

The article relating to the present design consists of a 3x3 grid. The field area has a concave boundary to avoid obstructing the movement of pieces, and the entire field is recessed lower than the surrounding area to prevent pieces from falling out. The periphery of the game board is provided with notches into which coin-shaped pieces can be fitted.

The invention discloses a block chain-based game design data production and detection method and system, and the method comprises the steps: obtaining various types of game design data related to a game generated in a game design process, and obtaining a data detection chain obtained according to the various types of game design data; establishing a block chain network, and respectively storing the various game design data and the data detection chain under the chain and on the chain of the block chain network; when various game design data under the chain needs to be read, various current game design data are obtained from the storage under the chain, and a verification data detection chain is obtained according to the various game design data. And reading the data detection chain stored on the chain from the block chain network, comparing the data detection chain with the verification data detection chain, and if the data detection chain is consistent with the verification data detection chain, judging that the various game design data are not tampered. The problem that the safety of game design data storage produced in the prior art is low is solved.

System, process and device configurations are provided for analyzing video data, such as electronic game data, and generating scoring data for video data. Processes and device configurations include training a video data analysis model to generate scoring parameters, and for an evaluation tool for video data. Highly viewed and popular videos may be used as training input to the video analysis model. At least one score parameter may be determined for scoring videos. For electronic games, at least one score may be associated with a game scene, gameplay storylines, and for scoring video data in general. Analysis of game titles and game design may be performed during design to ensure that game scenes will have a high likelihood of user interest. Embodiments may also include modifying gameplay and gameplay storylines, and evaluating game promotional videos.

1. The name of the design product: toy (magnetic sensory strategy game design 4). 2. The use of the design product: for toys, with stress-relieving effect. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

A system and a method of producing a curative game by at least one processor may include obtaining a brain map data structure, associating specific brain regions with respective, audiovisual stimuli; receiving an expert diagnosis of a neurological impairment of a subject; based on the expert diagnosis, prompting the subject to engage in at least one evaluation activity that corresponds to the neurological impairment, via a user interface (UI); assessing a functionality of one or more brain regions of the subject based on the evaluation activity; selecting one or more brain regions based on the assessed functionality; and creating at least one audiovisual, curative game designed to stimulate the selected brain region based on the brain map data structure.

This invention discloses a method and system for optimizing the dynamic loading efficiency of ultra-large scenes in 3D engines, belonging to the field of computer game design technology. It aims to solve problems such as high computational overhead, resource lag, and fragmented video memory in existing scene loading methods. The method includes: constructing a dynamic sparse octree index to achieve ordered spatial data organization; predicting future positions based on viewpoint motion vectors and constructing pre-loaded view frustums; establishing a multi-threaded asynchronous I / O scheduling mechanism to read and convert data in parallel according to priority; implementing video memory pooling management and reference counting strategies to achieve resource reclamation and reuse by page blocks; and using a time-weighted linear interpolation algorithm to achieve smooth switching between multiple levels of detail. The system includes corresponding index construction, state prediction, streaming scheduling, pooling management, and dynamic update modules. Through the above solutions, this invention significantly improves the real-time performance of data loading and hardware utilization, effectively eliminating screen stuttering, white models, and visual jump phenomena.

The invention provides a game testing method and device and electronic equipment, and the method comprises the steps: controlling at least one electronic equipment to load a specified game function module, and collecting test data generated when an artificial intelligence (AI) virtual role executes a game task included in game content corresponding to the specified game function module in the specified game function module; performing rule verification on the test data based on a pre-generated game design rule; performing comparison verification on the test data based on the historical test data passing the verification; and generating a test result of the target game based on the abnormal test data and the normal test data determined by the rule verification and the comparison verification. According to the method, a corresponding test script does not need to be written for each game task, and the AI virtual character is used for carrying out random running test, so that each function point in the game with high degree of freedom can be covered.

The application is suitable for the computer technology field, and provides a game chat data analysis method based on batch accumulation, which comprises the following steps: acquiring chat data of a game system in real time, preprocessing the chat data; constructing a data storage tree, storing the chat data to the data storage tree, and classifying the chat data; batch processing data of the same classification, generating a batch accumulation queue, and monitoring batch accumulation conditions; when the batch accumulation conditions are triggered, data analysis is performed on the data in the batch accumulation queue, the data in the batch accumulation queue is analyzed when the batch accumulation conditions are triggered, potential rules and trends in the data can be mined, and the method is helpful for understanding the behavior patterns of players, optimizing game design, improving game experience and the like.

The invention provides a driving engine design method and system based on a 3D game vehicle, and belongs to the technical field of 3D game design, and the method comprises the steps: respectively determining the three-dimensional coordinates of each driving position point of a target vehicle in a sub-scene based on different view azimuth angles, midline azimuth angles and viewpoints under vehicle deformation contour combinations; according to the standard visualization range of each viewpoint under the same scene point and the behavior operation list of the corresponding viewpoint, sequentially determining a static presentation vector of each first presentation point in the standard visualization range under each behavior operation in the behavior operation list; according to the dynamic association component list of the first presentation point, determining a dynamic presentation vector corresponding to the first presentation point under each dynamic association component combination; and in combination with the linear distance between the first presentation point and the viewpoint and the game permission of the target vehicle, determining a rendering mode of each first presentation point and carrying out driving rendering. And an operation feedback chain of the real world is restored, and high-immersion 3D vehicle driving experience is created.

The objective of the present invention is to provide a comprehensive game content development research method for developing and researching game content in which the design or appearance characteristics of suitable characters in computer games or mobile games are important factors determining the success or failure of the game. The composition of the present invention is characterized by including a subculture content and character design research stage for researching subculture worldviews and character designs, a high-quality animation and cinematic direction research stage, and a game design and user experience innovation research stage.

The invention discloses a shared farmland management system and method based on virtual-real closed loop and gamification excitation of intelligent hardware linkage, and relates to the technical field of shared farmland and digital interaction. The system comprises a reality end intelligent hardware suite, a virtual end interaction management platform and a data linkage module, hardware such as a soil monitoring terminal, an intelligent irrigation valve, an intelligent camera and an intelligent tool box is deployed at a reality end, and real-time collection and remote control of farmland data are achieved; the virtual end is a mobile phone APP and comprises a gamification farming task module, an incentive social module, a remote monitoring module and an agricultural product delivery module, tasks of irrigation, fertilization, weeding and the like are generated based on hardware acquisition data, and a virtual-real closed loop of data acquisition, task (result) pushing, instruction issuing (autonomous or entrusting) and execution result feedback is configured. According to the method, through the steps of hardware deployment and data linkage, task triggering and pushing, user operation execution, effect feedback excitation, harvesting and delivery and the like, and in combination with gamification designs such as a growth level, a ranking list and a virtual medal, the problems that an existing shared farmland is single in participation form, insufficient in intelligence and weak in user stickiness are solved; the interestingness, convenience and flexibility of farming activities are improved, and integration of shared farmland management, remote control and agricultural product delivery is realized.

This application relates to determining a quality of an electronic game based at least in part on the time spent by a game designer designing the electronic game. The number of actions performed using a game development tool counts towards a plurality of time ranges while operating the game development tool during the game design process. If the number of actions for any particular time range meets a threshold of the number of actions, then the duration of that time range is added to a value of a total development time of the electronic game. Other time ranges, where the number of actions fails to meet the threshold, do not have their time range durations added to the value of the total development time. Higher quality ratings correspond to longer total development times.

This invention belongs to the field of adaptive difficulty analysis and design for competitive games, and discloses a method, system, device, and storage medium for designing and analyzing action games. By constructing a behavioral feature dataset and evaluating habitual confidence levels, this invention can accurately grasp players' behavioral habits during combat, providing a reliable basis for subsequent difficulty adjustments and solving the problem of insufficient player behavior analysis in existing technologies. Based on a large amount of test data and objective classification logic, this invention constructs a mapping relationship between competitive actions and difficulty, making the difficulty classification more consistent with players' actual experiences and overcoming the shortcomings of unscientific difficulty classification in existing technologies. This invention achieves autonomous adjustment of the difficulty of simulated character combat actions by evaluating player adaptability and analyzes the rationality of the adjustment to ensure that the difficulty adjustment is suitable for players, improving game playability and player experience, and making up for the lack of autonomy and rationality evaluation in tactical adjustments in existing technologies.

The application discloses a virtual object control method and device, computer equipment and a readable storage medium, and relates to the technical field of game design. In the environment of an open-world multiplayer network synchronization game, the amount of data for synchronization is reduced under the premise of ensuring smooth game and complete functions, the design of the skill of the virtual object in the open-world network game is avoided from being limited, and novel game experience is brought to players. The method comprises the following steps: in response to a virtual object sinking skill release instruction, a sinking area is generated in a virtual scene; a sinking calculation result from a server is received, the sinking calculation result being determined by the server according to at least one or both of a control instruction of the virtual object and real-time physical collision detection results of the virtual object and the sinking area; and a sinking animation performance of the virtual object in the sinking area is displayed according to the sinking calculation result.

The invention relates to the technical field of intelligent production of cartoon games, in particular to an intelligent production and management method and system for cartoon games. The method comprises the following steps: acquiring animation game design data and animation game plot data; performing design element feature extraction according to the animation game design data so as to generate design element feature data, and performing plot emotion feature extraction and role positioning feature extraction according to the animation game plot data so as to generate plot emotion feature data and role positioning feature data; and constructing a role generation model according to the design element feature data so as to construct a cartoon game role generation model, and performing generation calculation on the cartoon game role generation model by utilizing the plot emotion feature data and the role positioning feature data so as to generate cartoon game role data. According to the method, the roles with various appearances and capabilities are generated by utilizing the design element features and the plot emotion features, so that the user experience is improved.

A single policy may be trained to cope with user selection of parameters across a predetermined range for each component of an artificial intelligence agent within a domain. The agent may be trained across multiple weights within a desired range for each component. These weights determine how many reward portions for each component should be considered by the agent during training. Therefore, for a UVFA-like target based on a compositional reward function parameterized by the weights of its components, an improved formulated expression can be achieved. Further, for the field of autonomous racing games, a set of reward components is determined that, when combined with an improved UVFA formulation expression, allows training of a single racing agent that is generalized in multiple dimensions in continuous behavior. This can be used by a game designer to adjust the skill and personality of the trained agent.

A single policy can be trained to handle the user selection of parameters across a predetermined range for each component of an artificial intelligent agent within a domain. The agent can be trained across a number of weights within the desired range for each component. These weights determine how much of a reward portion for each component should be considered by the agent during training. Thus, an improved formulation can be realized for UVFA-like goals based on compositional reward functions parameterized by their components' weights. Additionally, a set of reward components has been determined for the domain of autonomous racing games that, when combined with the improved UVFA formulation, allows training a single racing agent that generalizes over continuous behaviors in multiple dimensions. This can be used by game designers to tune the skill and personality of a trained agent.

The application relates to an AI-based multi-modal game generation method and a generation system, obtains associated information groups for generating games, analyzes and generates a structured initial game design list, revises the initial game design list based on requirements, calls multi-modal agent groups to generate corresponding game component images under each classification in the revised list, repeatedly cross-checks the multi-modal agent groups, coordinates until the requirements are met, fuses all generated game component images according to the associated information groups, and generates games; the generation system comprises a list generation module, a multi-modal generation module and a fusion output module. The application reduces the requirement of game design on the professionalism of users, expands the applicable population, simultaneously reduces the difficulty of game design for developers, improves the efficiency of game design, and effectively reduces the game design cost; the generated game product can be commercially used without repeated modification, the game is systematically fused in the whole process, the operation is simple, and the game is easy to use.

The invention discloses an AI-based game design scheme generation method and a terminal, and the method comprises the steps: collecting excellent historical game design schemes with design scores higher than a first score threshold value and design templates thereof, and learning the generation process of the excellent design schemes, so as to obtain an AI model used for the generation of excellent schemes; the conditions of design errors are reduced; after a game design demand is received, functional modules are divided, and design templates are matched according to the divided functional modules to generate an initial scheme, so that the initial scheme can cover functions required by the game design demand, and the situation of design omission is reduced; afterwards, the initial scheme and the game design requirement are substituted into an AI model, and a final game design scheme is generated. In this way, the game design scheme can be automatically generated according to the game design requirement, and the situation of design omission or design errors is reduced.