Dynamic Card Dealing System with Probabilistic Distribution Control
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Solution Overview
Problem
Current card dealing algorithms in electronic chess and card games fail to dynamically control the probability of various card combinations over multiple rounds or games, leading to inefficiencies and limited configurability, making it difficult to maintain consistent gameplay experience.
Innovation Solution
A method and system that generate card distribution configurations using a table defined by meld types and their occurrence probabilities, allowing for random selection and distribution of card combinations based on normal distribution functions, enabling dynamic adjustment and reconfiguration of card dealing strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed set of card configurations is used to control good card combinations, then the appearance of good card combinations can be controlled, but the ability to control the probability of particular card combinations is limited and the system cannot be dynamically reconfigured
Solution Approach 1:
The patent implements dynamic card dealing by replacing fixed configurations with a probabilistic system that can adapt to different game scenarios. The card dealing algorithm now uses probability distributions and statistical parameters that can be adjusted in real-time based on game state, player performance, and strategic requirements, transforming a static system into a dynamic one that responds to changing conditions
Solution Approach 2:
The patent changes the fundamental parameters of card dealing from fixed configuration counts to probabilistic parameters including occurrence probabilities, expected values, and variance controls. This allows the system to control card distribution through statistical parameters rather than rigid fixed configurations, enabling fine-grained control over deal outcomes while maintaining system flexibility
2Ease of operation
If random card dealing is used, then the system is simple, but the distribution of cards into meaningful combinations cannot be controlled and the probability of getting a good hand is small
Solution Approach 1:
The patent introduces an intermediary layer between random card generation and final deal distribution. This intermediary probabilistic control system uses statistical models to guide the random dealing process, ensuring that while individual deals remain unpredictable, the overall distribution achieves desired quality metrics through controlled probability management
Solution Approach 2:
The patent implements feedback mechanisms that monitor card distribution outcomes and adjust dealing parameters accordingly. By tracking the frequency and quality of dealt hands, the system can refine its probabilistic models to maintain optimal distribution quality, creating a closed-loop system that continuously improves based on observed results
3Adaptability or versatility
If card dealing strategy is modified on the backend server, then the card dealing algorithm can be updated, but the efficiency is low due to required backend updates for each modification
Solution Approach 1:
The patent performs preliminary calculations of probability distributions, expected values, and statistical parameters during system initialization or pre-processing phases. By pre-computing these statistical characteristics and storing them as lookup tables or configuration data, the system enables rapid strategy modifications without requiring time-consuming backend recalculations during active gameplay
Solution Approach 2:
The patent uses probabilistic models and statistical parameters as abstract representations (copies) of the actual card dealing process. These mathematical models can be modified and tested independently from the core dealing logic, allowing strategy changes to be implemented by updating parameter sets rather than rewriting the entire dealing algorithm, thereby improving modification efficiency
Data Source
AI summary
In one aspect, a method for dealing cards includes: selecting a respective card distribution configuration from a plurality card distribution configurations stored in a card distribution configuration table, each card distribution configuration being defined by a respective set of meld types and a respective number of occurrences for each of the set of meld types, the respective number of occurrences specifying a total number of times that card combinations matching the meld type occur in a game round; according to the respective number of occurrences for each meld type in the selected card distribution configuration, randomly selecting from a deck of cards a corresponding number of card combinations matching the meld type; distributing the selected card combinations for all of the meld types in the respective card distribution configuration to a plurality of game roles; and distributing a remainder of cards in the deck to the plurality of game roles.


