Player Classification System for MMOG Resource Allocation

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current massively multiplayer online games (MMOGs) face challenges in effectively matching players for enhanced experiences due to rudimentary player matching systems and lack of adequate security and consistency control in peer-to-peer (P2P) architectures, leading to suboptimal player interactions and resource inefficiencies.

Innovation Solution

A system that employs automated player classification and matching based on behavioral metrics and equipment weighting, allowing for optimized server resource allocation, energy conservation, and personalized gameplay experiences by analyzing player actions and characteristics to recommend suitable games, quests, and interactions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated player classification and matching systems are implemented, then player matching quality and resource allocation efficiency are improved, but system complexity and data processing requirements increase

Engineering Contradiction:

Improveresource allocation efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs preliminary player classification by analyzing behavioral metrics and equipment weighting data before matching players together. Player profiles are pre-generated and stored with key characteristics, allowing the matching system to quickly retrieve and compare preprocessed data rather than analyzing raw data in real-time, thus improving resource allocation efficiency while managing system complexity through advance preparation

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary matching system that acts as a mediator between players and game content. This intermediary layer processes player data, applies classification algorithms, and generates matching recommendations, thereby decoupling the complexity of data analysis from the core game mechanics and enabling efficient resource allocation without directly increasing game system complexity

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If detailed player behavioral analysis is performed, then matching accuracy and personalized recommendations are improved, but data processing time and computational resources increase

Engineering Contradiction:

Improvematching accuracyVSAvoiddata processing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs partial analysis by focusing on key behavioral metrics and equipment weighting data that are most relevant to player matching, rather than analyzing all possible player actions. This selective approach maintains matching accuracy by concentrating on the most discriminative features while reducing overall data processing time and computational resource requirements

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent transforms raw behavioral data into standardized parameters and metrics that can be efficiently processed and compared. By changing the representation of player data from detailed action logs to condensed behavioral metrics and equipment weights, the system achieves high matching accuracy through parameter comparison while significantly reducing the time and resources needed for data processing

Inventive Principle:

Principle #35Parameter changes

3Loss of energy

If server resources are optimized through player aggregation, then energy consumption and operational costs are reduced, but player interaction quality may deteriorate

Engineering Contradiction:

Improveenergy consumptionVSAvoidinteraction quality

Core Design Contradiction:

Loss of energyVSReliability

Solution Approach 1:

The system applies local quality by creating specialized server environments tailored to specific player types and game modes. Instead of uniformly distributing all players across identical server configurations, the patent aggregates players with similar characteristics onto servers optimized for their specific interaction patterns, thereby reducing energy consumption through targeted resource allocation while maintaining high interaction quality through environment specialization

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent segments the player base into distinct classification groups based on behavioral metrics and equipment weighting. This segmentation allows the system to operate multiple specialized server instances for different player segments rather than running a single general-purpose server, achieving energy efficiency through focused resource usage while preserving interaction quality by matching players with similar preferences and play styles together

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS8651961B2Collaborative electronic game play employing player classification and aggregation

Publication Date: 2014.02.18 SOLOCRON ENTERTAINMENT

AI summary

A method and system tracks, analyzes or sorts behaviors of user or players across a network to draw correlations from, or characterizations of, those user or players and identifies similarly characterized or mutually complementary user or players. For example, the method automatically obtains player data regarding interactions by each of multiple players with a multiplayer electronic game via each player's corresponding data processing device connected via the network. The method can then sort, classify or suggest additional activities, games, groups, or other different activities or actions for the players.