Adaptive Game Object Placement via Proximity Detection
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Solution Overview
Problem
Current map-based computer games lack efficient and dynamic adaptation of game objects based on proximity, leading to suboptimal gameplay experiences and performance issues due to unnecessary object updates and complex rule sets.
Innovation Solution
Implement a system that checks for game objects within a predefined proximity to a placed object, using categories and lookup tables to determine necessary adaptations, allowing for recursive updates and efficient adaptation of game objects, including immediate or delayed changes based on proximity to other objects of the same type or category.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional object placement methods are used in map-based games, then implementation is simple, but gameplay experience is suboptimal and lacks dynamic adaptation
Solution Approach 1:
The system segments game objects into categories and uses proximity-based grouping to determine adaptations. By dividing the game world into proximity zones around each object, the system efficiently determines which objects need adaptation without checking all objects globally, thus achieving dynamic adaptation while managing system complexity.
Solution Approach 2:
The system performs preliminary actions by pre-defining categories of game objects and establishing proximity rules beforehand. When an object is placed, the system immediately checks predefined proximity criteria rather than creating complex rules on-the-fly, enabling dynamic adaptation while keeping the system manageable through pre-established frameworks.
2Productivity
If all game objects are updated regardless of proximity, then comprehensive coverage is achieved, but computational load increases and performance decreases
Solution Approach 1:
The system applies local quality by updating only those game objects that are within a predefined proximity distance of a placed object. Instead of uniformly updating all objects, the system locally determines which objects fall within the proximity zone and updates only those, significantly reducing computational load while maintaining update efficiency for affected objects.
Solution Approach 2:
The system performs partial action by checking and updating only a subset of objects that meet the proximity criterion, rather than performing exhaustive updates on all objects. This selective approach reduces unnecessary computational operations while ensuring that all objects that actually need updating are processed, optimizing both productivity and energy efficiency.
3Adaptability or versatility
If complex rule sets are used to determine object adaptations, then comprehensive adaptation rules are covered, but system complexity increases and performance decreases
Solution Approach 1:
The system uses parameter changes by defining adaptations in terms of simple proximity parameters (distance thresholds, object categories) rather than complex rule logic. By changing the approach from complex conditional rules to parameter-based proximity checks, the system achieves comprehensive adaptation coverage while keeping the underlying system simple and performant.
Solution Approach 2:
The system applies universality by creating a general proximity-based adaptation framework that works across all types of game objects. Instead of implementing specific complex rules for each object type, a universal proximity check mechanism handles all objects, simplifying the system while maintaining comprehensive adaptation capabilities through category-based grouping.
4Reliability
If unnecessary object updates are performed, then comprehensive checking is done, but performance decreases due to wasted computational resources
Solution Approach 1:
The system performs preliminary action by pre-establishing proximity thresholds and object categories before runtime. During object placement, it immediately applies these predefined criteria to determine which objects need updating, ensuring accurate updates for relevant objects while avoiding unnecessary processing, thus maintaining both reliability and productivity.
Solution Approach 2:
The system applies dynamics by making the update process adaptive based on real-time proximity conditions. Instead of statically updating all objects, the system dynamically determines which objects fall within the proximity zone of a placed object and updates only those, ensuring update accuracy for affected objects while maximizing processing speed by eliminating redundant updates.
Data Source
AI summary
Disclosed in some examples are systems, methods, and machine readable mediums which allow for efficient and dynamic adaptation of one or more game objects based upon a proximity to another game object. In some examples, placement (or movement) of a game object may trigger a proximity check wherein the game map is checked to determine a set of game objects which are within a predefined proximity to the placed game object which may affect the behavior or appearance of the game object. The appropriate adaptations (if any) may be determined using a lookup table or other rule set where the inputs include the set of game objects and the locations of each of the game objects in the set relative to the placed object.