Dynamic Multiplayer Matchmaking Using Social and Skill Metrics
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Solution Overview
Problem
Conventional multiplayer gaming environments struggle to match players of different skill levels effectively, leading to unbalanced gameplay experiences and lack of social interaction, as they rely on rigid matchmaking criteria that do not account for subjective variables like likeability and cooperation, and fail to dynamically adjust game parameters based on player feedback.
Innovation Solution
A computer-implemented method and system that dynamically adjusts game session parameters based on skill level data, including measurable and subjective traits, to provide a customized degree of difficulty for each player, while also incentivizing cooperation and using social network feedback to tailor game content and matchmaking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If rigid matchmaking criteria based solely on skill level are used, then gameplay balance is improved, but player satisfaction and social interaction are worsened
Solution Approach 1:
The patent applies dynamics by transitioning from static, rigid skill-based matchmaking to a dynamic system that continuously adapts matchmaking criteria. The system incorporates multiple evolving factors including skill level, likeability metrics, cooperation history, and social network data that are regularly updated and weighted differently based on game context and player behavior patterns.
Solution Approach 2:
The patent implements parameter changes by expanding the matchmaking criteria from a single parameter (skill level) to multiple parameters including skill level, likeability scores, cooperation metrics, and social network attributes. The system dynamically adjusts the weight and influence of each parameter based on game type, player preferences, and real-time performance data.
2Adaptability or versatility
If players of different skill levels are matched together, then player enjoyment and social interaction are improved, but gameplay balance deteriorates
Solution Approach 1:
The patent applies local quality by providing customized game parameters and difficulty adjustments for individual players within the same match. Each player experiences tailored game elements such as adjusted enemy difficulty, modified resource availability, or customized objectives based on their skill level, allowing mixed-skill teams to play together while maintaining appropriate challenge levels for each participant.
3Device complexity
If conventional matchmaking systems are used, then system complexity is reduced, but ability to recognize and incentivize cooperation deteriorates
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor player interactions during gameplay, tracking cooperation behaviors such as assists, rescues, and team-based achievements. This feedback is processed to generate cooperation metrics that are stored in player profiles and used to influence future matchmaking decisions and reward distributions.
Solution Approach 2:
The patent introduces an intermediary layer between raw gameplay data and matchmaking decisions. This intermediary processing system analyzes player behaviors, calculates cooperation metrics, and translates complex interaction patterns into simplified matchability scores that can be efficiently used by the matchmaking algorithm.
Data Source
AI summary
Computer-implemented methods and systems for simulating a multiplayer game environment to allow players of different skill levels to concurrently play the same level of a gaming session, to encourage and incentivize cooperative team behavior, to match players based on subjective variables, such as likeability and a general fun factor, and to tailor gaming content based on the social group itself.