Virtual Gaming Content Personalization by Player Group Preferences

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Solution Overview

Problem

Conventional intelligent agents in gaming systems lack the ability to evolve and adapt to individual player preferences and behaviors, leading to suboptimal gaming experiences, and there is a need for efficient data processing to support self-evolving AI-based models without excessive computational costs.

Innovation Solution

Implement self-evolving, AI-based content generative models that analyze player preferences and behaviors to generate personalized augmented or virtual reality content, using machine learning techniques to optimize content and object selection based on real-time and historical data, while ensuring security and player consent.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If self-evolving AI-based content generative models are implemented to personalize gaming content, then player engagement and satisfaction are enhanced, but computational costs and processing complexity increase

Engineering Contradiction:

Improvepersonalization capabilityVSAvoidcomputational complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments the gaming environment into multiple zones with different content preferences and requirements. Each zone is independently configured with specific content parameters, allowing the system to apply personalized content generation only where needed rather than across the entire gaming environment, thus reducing overall computational complexity while maintaining personalization capabilities.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system performs preliminary analysis of player preferences and behaviors before generating personalized content. By pre-processing player data and establishing content preference profiles in advance, the system reduces the computational burden during real-time content generation, enabling personalization without excessive processing complexity.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If real-time content generation based on player preferences is implemented, then gaming experience quality improves, but processing latency increases

Engineering Contradiction:

Improvecontent customizationVSAvoidprocessing latency

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system merges the content generation process with the existing gaming environment rendering pipeline. By integrating content generation with the game's natural refresh cycle and combining multiple content delivery operations into single processing passes, the system reduces processing latency while maintaining real-time content customization capabilities.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The system updates personalized content at periodic intervals synchronized with the gaming environment's refresh rate rather than continuously. This periodic update approach maintains content relevance and personalization quality while significantly reducing processing latency compared to continuous real-time generation.

Inventive Principle:

Principle #19Periodic action

3Measurement precision

If comprehensive player data analysis is performed to determine group content preferences, then content personalization accuracy improves, but data processing requirements increase

Engineering Contradiction:

Improvepreference detection accuracyVSAvoiddata processing energy

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system extracts only the essential preference attributes from comprehensive player data that are most relevant to content personalization. By identifying and extracting key preference indicators rather than analyzing all available player data, the system achieves accurate preference detection with reduced data processing energy requirements.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system creates simplified copies or representations of player preference profiles that capture the essential characteristics needed for content personalization. These compressed preference representations enable accurate content matching without requiring processing of the full comprehensive player data set, reducing energy consumption.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20250319394A1Creating and delivering virtual content for gaming objects based on player group content preferences

Publication Date: 2025.10.16 INTERNATIONAL GAME TECHNOLOGY INC

AI summary

The present disclosure relates generally to a gaming system, device, and method that in response to the detected content generation event, generates, from a set of group content preferences, content for presentation by a reality altering device of each player in the group of players, select content in the generated content for presentation by the reality altering device to represent a sensory characteristic of a selected object in a set of objects, determines, relative to a coordinate system, a respective spatial location of each player in the group of players and a respective spatial location of the selected object, and, based on the respective spatial locations of each player relative to the respective spatial location of the selected object, causes a respective portion of the selected content to be presented by the corresponding reality altering device of the player.