Dynamic Action Pattern Generation for Game Boss Characters
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Solution Overview
Problem
Existing games face challenges in maintaining the difficulty and variety of boss character action patterns, leading to predictable encounters and increased development costs due to the need for numerous action pattern data sets, even when characters are of the same type across different stages.
Innovation Solution
A game system that generates and controls action patterns for characters by selecting and modifying action pattern routines based on predetermined conditions, allowing for dynamic changes in action patterns during gameplay, thereby diversifying character actions without significantly increasing data quantity or development costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate action pattern data is produced for each character and stage, then the action pattern variety is maintained, but the data quantity and development cost increase significantly
Solution Approach 1:
The patent creates a universal action pattern data structure where a single set of action pattern data can be applied across multiple characters and stages. The action pattern information is designed to be character-type-based rather than character-instance-based, allowing the same action patterns to serve multiple boss characters of the same type throughout the game, thereby reducing overall data quantity while maintaining variety through selective application.
Solution Approach 2:
The patent applies local quality by allowing different action pattern configurations for different character types and stages. Instead of creating entirely separate data sets for each character, the system selectively applies or modifies specific action pattern elements based on the character type and stage context, maintaining local variety while using a global data structure.
2Ease of manufacture
If the same boss character type appears across multiple stages, then development cost is reduced, but the action pattern becomes predictable and loses variety
Solution Approach 1:
The patent introduces dynamics by allowing action pattern data to be selectively applied or modified based on stage and character type. The system can dynamically choose which action patterns to apply, modify certain parameters, or combine different action pattern elements, making the same boss character type behave differently across stages without requiring separate data sets for each instance.
Solution Approach 2:
The patent utilizes parameter changes by allowing modification of action pattern parameters based on stage and character type. Specific parameters within the action pattern data can be adjusted, such as timing, intensity, or sequence of actions, enabling the same base action pattern to produce varied gameplay experiences across different stages while maintaining data efficiency.
3Ease of manufacture
If action pattern data is reused across characters and stages, then development cost decreases, but the degree of difficulty may decrease due to predictability
Solution Approach 1:
The patent applies local quality by allowing selective modification of action pattern parameters for specific stages or character types. This enables the system to maintain the efficiency of data reuse while introducing local variations that preserve challenge and unpredictability. For example, certain action patterns can be intensified or modified in later stages to maintain difficulty levels.
Data Source
AI summary
The disclosure describes a game system equipped with a game space generating unit generating a virtual game space where the character acts, displays on a display unit connected to a game system together with the character acting in the game space, a character control unit which controls the character's action in the game space, a storing unit which stores a plurality of action pattern routines providing a predetermined action pattern of the character; and an action pattern set generating unit which generates an action pattern set of the character by reading a plurality of action pattern routines from the storing unit and selects more than two action pattern routine from the plurality of action pattern routines determining the order to perform and determining an action modification condition to modify the action pattern routine to be exercised from the selected action pattern routine from more than two action pattern routines.