Gaming System Probability Adjustment for Sub-Optimal Player Actions
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Solution Overview
Problem
Gaming systems that require players to exercise optimal skill often result in less enjoyment for players who derive pleasure from learning optimal strategies, as skilled players receive greater returns than less skilled ones, leading to a need for an alternative system that compensates players for sub-optimal choices.
Innovation Solution
A method and system that require players to choose between optimal and sub-optimal actions, where the difference in returns is compensated through controlled probability trials, potentially adding lost returns to a progressive jackpot, ensuring all players receive an equivalent expected return.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If optimal play instructions are provided to ensure equal return for all players, then fairness is improved, but player enjoyment is reduced
Solution Approach 1:
The system dynamically changes the probability parameter of award trials based on whether the player's action was optimal or sub-optimal. When a player takes a sub-optimal action, the system increases the probability of award trials to compensate for the lost return, thereby maintaining fairness without requiring optimal play instructions.
2Ease of operation
If the system allows players to exercise skill without optimal play instructions, then player enjoyment is improved, but return fairness deteriorates
Solution Approach 1:
The system provides feedback by monitoring player actions and determining whether they are optimal or sub-optimal. Based on this feedback, the system adjusts the probability of award trials to compensate for sub-optimal play, ensuring that all players receive an equivalent expected return regardless of their skill level or whether they received optimal play instructions.
3Measurement precision
If sub-optimal actions result in lower returns, then skill differentiation is improved, but player satisfaction deteriorates
Solution Approach 1:
The system dynamically adjusts the probability of award trials based on the player's action quality. When a player takes a sub-optimal action, the system increases the probability of compensatory award trials, making the system adaptable to different player skill levels and action qualities, thereby maintaining player satisfaction while still allowing skill differentiation.
Data Source
AI summary
A method of gaming comprising: conducting a game requiring a player to make a choice between at least one optimal action and at least one sub-optimal action having a lower return to player than the optimal action such that the difference between the sub-optimal action and the optimal action represents a lost return to player; receiving a player choice of an action; and conducting a trial for an award in which the probability of success is controlled to provide an expected return to player from the trial that compensates the player for the lost return to player in response to determining that the choice is a sub-optimal action.