Weight-Based Player Assignment for Poker Game Idle Time Reduction
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Solution Overview
Problem
Online wagering games, such as Poker-type games, face issues with player idle time, leading to reduced user experience and inefficient resource utilization, as players often wait for extended periods between game instances.
Innovation Solution
A computer-implemented method that automatically assigns players to new game instances upon cessation of participation in the current game, maintaining connections to both the previous and new game instances, and uses weight-based algorithms to ensure fair and efficient player positioning across multiple game instances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If players are automatically assigned to new game instances as soon as they become inactive, then player idle time is reduced and gaming experience is enhanced, but system resource management becomes more complex and connection management becomes more difficult
Solution Approach 1:
The system performs preliminary actions by maintaining the player's connection to the first game instance until the second game instance is fully established and the player is successfully connected. This prevents connection loss and ensures smooth transition, resolving the contradiction by preparing the transition path in advance while managing connection complexity systematically.
Solution Approach 2:
The system acts as an intermediary by temporarily maintaining both connections (first and second game instances) during the transition period. This intermediary approach allows the player to be smoothly transferred between game instances without losing connection, reducing idle time while managing connection complexity through controlled overlap.
2Productivity
If players are continuously assigned to new game instances, then resource utilization is optimized, but fairness and strategic positioning of players become harder to control
Solution Approach 1:
The system uses feedback mechanisms by evaluating player characteristics, game state, and positioning requirements before assigning players to new game instances. This feedback loop ensures that continuous assignment maintains fairness and strategic positioning by considering multiple factors in the assignment decision, resolving the contradiction between efficiency and fairness.
Solution Approach 2:
The system changes parameters by adjusting player assignment criteria based on game state, player skills, and positioning requirements. By dynamically modifying assignment parameters, the system optimizes resource utilization while maintaining fair and strategically sound player positioning across continuous game instances.
Data Source
AI summary
Disclosed is a computer-implemented method of (and system for) operating instances of a game having a plurality of game positions that can be occupied by players, such as a poker-type game. The method comprises assigning a player a plurality of weights relating to game positions, where each weight indicates a bias towards placement of the player at a game position. When a player has played in a first game at a given position, the weights are updated to indicate an altered bias towards placement at each position. The player is then assigned to a second game based on the updated weights.