Online Gaming Disruptive Behavior Detection and Room Selection
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Solution Overview
Problem
The video game industry faces challenges in managing disruptive player behavior in online multiplayer games, which can detract from the gaming experience and require significant resources to identify and monitor, leading to inefficiencies in player engagement and game operation.
Innovation Solution
A method and system for processing disruptive behavior in online gaming systems, involving identifying disruptive behavior events, verifying responsible players, applying behavioral designations, generating real-time player behavior data, and displaying this data to players for informed game room selection, thereby enabling better control over the gaming environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional methods are used to identify and monitor disruptive players, then disruptive behavior can be detected, but significant computing resources, human resources, energy resources, and data communication bandwidth are consumed
Solution Approach 1:
The system pre-generates behavioral indicators and demographic data for game rooms before players select them. By preparing this information in advance, the system avoids the need for intensive real-time analysis when players need to make room selections, thereby reducing on-demand computing and communication resources while maintaining reliable disruptive behavior detection
Solution Approach 2:
The patent introduces behavioral indicators and demographic data as intermediary elements that mediate between the complex disruptive behavior detection system and the player's room selection decision. These intermediaries summarize complex behavioral patterns into digestible metrics, reducing the computational burden on both the server and player devices while preserving detection accuracy
2Measurement precision
If real-time monitoring of all players is implemented, then disruptive behavior can be identified accurately, but data communication bandwidth and processing power increase significantly
Solution Approach 1:
The system extracts only the essential behavioral information needed for room selection into compact demographic indicators. By separating and extracting only the critical behavioral metrics from the full player behavior data, the system reduces data communication bandwidth requirements while maintaining sufficient measurement precision for players to make informed room selections
Solution Approach 2:
The system implements partial monitoring by focusing computational resources on generating aggregate behavioral demographics for game rooms rather than monitoring every individual player action in real-time. This partial action approach provides sufficient behavioral analysis accuracy for room selection while significantly reducing data communication bandwidth and processing power requirements
3Adaptability or versatility
If players are provided with behavioral information to make informed room selections, then player engagement improves, but system complexity increases
Solution Approach 1:
The system changes the parameter representation of player behavior from complex, multi-dimensional behavioral data to simplified demographic indicators and statistics. By transforming behavioral data into different parameter forms (aggregate counts, percentages, ratings), the system enhances player engagement through informative room selection while managing system complexity through data abstraction and aggregation
Data Source
AI summary
Disruptive behavior events are identified within an online gaming system. Players responsible for the identified disruptive behavior events are verified. A behavioral designation is applied to players in the online gaming system. The behavioral designation indicates whether or not a player is verified as responsible for one or more of the identified disruptive behavior events. Current real-time player behavior demographic data is generated for a specified game space using the behavioral designations applied to players associated with the specified game space. The generated current real-time player behavior demographic data for the specified game space is displayed to players associated with the specified game space. Using current real-time player behavior demographic data generated and displayed for different game spaces, a player is enabled to make a behavior-informed selection of a game space in which to enter for game play. Also, player behavioral profiles enable tracking of player-specific behavior preferences and events.