Skill-Based Wagering Machine Return-to-Player Control
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Solution Overview
Problem
Gaming regulatory authorities require electronic gaming machines to maintain a minimum return-to-player while ensuring they do not payout more than a maximum return-to-player, which conflicts with providing players with meaningful skill-based decisions that affect their odds of winning.
Innovation Solution
A gaming machine system that includes a credit input mechanism, player interface, and game controller, which increases or decreases a credit balance based on player inputs and randomly selects game screens to ensure a predetermined minimum return-to-player, weighting game states to account for skill-based moves and maintain desired payout ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the game uses a random number generator to determine outcomes, then the return-to-player can be controlled within regulatory limits, but the player loses meaningful skill-based decisions that affect their odds of winning
Solution Approach 1:
The game is divided into two distinct phases: a random phase where the RNG determines the base outcome and ensures regulatory compliance, and a skill phase where player decisions can modify the outcome. This segmentation allows both random control and skill expression to coexist without conflict.
Solution Approach 2:
The game transitions from a static random outcome to a dynamic state where player actions can influence the final result. The skill-based decisions allow players to actively change their odds of winning or the prize amount, creating a dynamic interaction between player agency and regulatory constraints.
2Adaptability or versatility
If the game provides skill-based choices that affect odds of winning, then player engagement increases, but the return-to-player becomes unpredictable and may exceed maximum limits
Solution Approach 1:
The system provides feedback to players about how their skill-based decisions affect their odds and potential payouts. This feedback loop allows players to understand the impact of their choices while the system monitors and adjusts to ensure the overall return-to-player remains within regulatory limits.
Solution Approach 2:
The game allows player decisions to change parameters such as odds of winning and prize amounts, but these changes are bounded by the underlying RNG system that ensures the overall return-to-player remains within regulatory minimum and maximum limits.
3Reliability
If the game ensures a minimum return-to-player through random selection, then regulatory requirements are met, but the ceiling for player winnings is effectively capped
Solution Approach 1:
The game adds a new dimension of player agency above the base random outcome. While the RNG ensures minimum return-to-player compliance, the skill-based phase allows players to potentially exceed the base expected value through strategic decisions, effectively creating an upper dimension of winnings that wasn't present in pure chance games.
Data Source
AI summary
A method, computer readable medium, and game machine are presented, that provide a skill-based game of a wagering machine with a predetermined return-to-player. The method includes constructing, for each initial game state of a plurality of initial game states, a decision tree that includes a root node, intermediary nodes, leaf nodes, and collective leaf nodes that each represents a class of game states and its expected minimum payout. The method further includes determining, based on the decision tree for each initial game state, an expected minimum payout for the respective initial game state; and generating, for the wagering machine, a table that weights each initial game state of the plurality of initial games states based on its respective expected minimum payout to achieve a desired minimum return-to-player.