Dynamic Game Strength Adjustment via Monte Carlo Tree Search

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Solution Overview

Problem

New participants in online turn-based games face difficulty adapting to the game environment due to the fixed strength of virtual opponents, leading to a decline in interest and performance, which affects team dynamics and operator revenue.

Innovation Solution

A method using a Monte Carlo tree search algorithm to simulate and adjust the probability distribution of game strength, allowing a computer host to dynamically control virtual objects and match their strength to the user's performance, thereby enhancing gameplay experience and adaptability.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If the game strength is fixed, then the game system is simple to operate, but new participants cannot adapt to the game environment

Engineering Contradiction:

Improveadaptability of game strengthVSAvoidcomplexity of game system

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent implements dynamic adjustment of game strength parameters based on real-time player performance data. The system continuously monitors player statistics and automatically modifies opponent capabilities, creating a dynamic rather than static game environment that adapts to individual player needs and skill levels.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes key parameters of virtual opponents (such as attack power, defense, speed) based on player performance metrics. By adjusting these parameters dynamically, the game maintains appropriate difficulty levels without requiring complex structural changes to the overall game system.

Inventive Principle:

Principle #35Parameter changes

2Duration of action of moving object

If virtual opponents are added to enable continuous play, then player engagement improves, but the game becomes less challenging for experienced players

Engineering Contradiction:

Improveduration of player engagementVSAvoidchallenge level for experienced players

Core Design Contradiction:

Duration of action of moving objectVSAdaptability or versatility

Solution Approach 1:

The system incorporates feedback mechanisms that continuously monitor player performance against virtual opponents and use this information to adjust future matchings. Player win rates, kill deaths ratios, and other performance metrics feed into an algorithm that dynamically recalibrates opponent strength, ensuring experienced players continue to face appropriate challenges.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary analysis of player statistics before matching players with virtual opponents. By pre-calculating appropriate opponent strengths based on historical performance data, the system prepares customized challenge levels in advance, preventing boredom before it occurs.

Inventive Principle:

Principle #10Preliminary action

3Reliability

If new participants are matched with strong opponents, then competitive balance is maintained, but new participants lose interest and abandon the game

Engineering Contradiction:

Improvecompetitive balanceVSAvoidease of game enjoyment

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system applies different matching strategies to different player segments based on their experience levels. New players receive customized opponent configurations with adjusted difficulty parameters, while experienced players face standard or enhanced challenges. This localized approach to match quality ensures each player group experiences appropriate difficulty without compromising overall competitive balance.

Inventive Principle:

Principle #3Local quality

4Productivity

If the game system is improved to retain players, then player retention increases, but development load and costs increase

Engineering Contradiction:

Improveplayer retention rateVSAvoiddevelopment load

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system implements self-service functionality where the game automatically adjusts difficulty and matches players without requiring manual intervention from developers. The automated matching algorithm and dynamic parameter adjustment run autonomously based on collected player data, eliminating the need for continuous manual game balancing and reducing development workload.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS11247128B2Method for adjusting the strength of turn-based game automatically

Publication Date: 2022.02.15 NAT YANG MING CHIAO TUNG UNIV

AI summary

The present invention relates to a method for adjusting the strength of turn-based game automatically. The method provides a search algorithm for inquiry and giving decision results. The decision results can be used for filtering and giving filtered results. Then a probability distribution result can be provided to control the virtual node inside the computer host. Furthermore, the game result can be used for adjusting the performance of the virtual node in the game. Thereby, the client node can evaluate its performance in the game conveniently.