Game Guidance System for Personalized Player Training
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Solution Overview
Problem
Conventional training content for improving game learning levels is uniform and ineffective in supporting individual player progress based on their experience and skill, lacking personalized guidance to enhance learning efficiency.
Innovation Solution
An information processing device that outputs guiding command information to a game device when a game status approaches a specific phase, reproducing a game status achieved by a player with higher learning skills, allowing for stepwise or continuous guidance towards a reproduced game status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uniform training content is provided to all players, then training can be simplified and implemented easily, but it cannot effectively support improvement in game learning level according to individual experience and skill
Solution Approach 1:
The system provides different training content to different players based on their individual skill levels and experience. By analyzing player data and identifying specific phases where improvement is needed, the system tailors guidance commands to each player's local needs rather than applying uniform training to all players, thus resolving the contradiction between implementation simplicity and individual adaptability
Solution Approach 2:
The training content dynamically adapts to each player's current skill level and progress. The system continuously monitors player performance and adjusts the guidance commands accordingly, transitioning from static uniform training to dynamic personalized training that evolves with each player's development
2Reliability
If detailed personalized training content is created for each player, then learning effectiveness is improved, but system complexity and processing requirements increase
Solution Approach 1:
The system creates simplified copies or representations of ideal player behavior through guidance commands that indicate desired actions rather than providing complete detailed instructions. This copying approach maintains learning effectiveness by showing players what skilled players do, while reducing system complexity by using standardized command structures
Solution Approach 2:
The system pre-processes and analyzes player data to identify specific phases and patterns before generating personalized training content. By performing preliminary analysis to determine which phases need improvement and what guidance is appropriate, the system reduces the complexity of real-time content generation while maintaining high learning effectiveness
Data Source
AI summary
An information processing device includes an output control unit. When a game status approaches a specific phase, the output control unit outputs, to a game device, guiding command information to change a command signal received from a first player in response to the game status approaches the specific phase, wherein the guiding command information is guiding a current game status of the first player to a reproduction game status. In the reproduced game status a specific phase is reproduced in a game status of a second player having higher learning level than the first player.