ASCII-Seeded Random Number Generator for Non-Deterministic Assignment
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Solution Overview
Problem
Current computer-implemented random number generators, particularly pseudo-random number generators (PRNGs), do not produce truly random numbers as they are based on constant initial conditions and eventually repeat sequences, lacking actual randomness and non-deterministic properties.
Innovation Solution
A method involving the use of ASCII-value representations of user names, combined with dynamic arrangements and calculations, to generate and assign unique random numbers to users, ensuring true randomness and preventing sequence repetition by utilizing continuously changing properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pseudo-random number generators (PRNGs) are used, then the generation process is deterministic and reproducible, but the randomness and authenticity are insufficient and sequences eventually repeat
Solution Approach 1:
The patent applies dynamics by making the seed value dynamic and user-specific rather than static. The seed is computed based on user identity (e.g., username hash) and changes for each user, preventing sequence repetition and enhancing randomness authenticity while maintaining a relatively simple generation process.
Solution Approach 2:
The patent changes the parameter of the seed value from a constant initial condition to a user-specific variable. By computing the seed based on user identity and using it to select from dynamically arranged unassigned numbers, the system achieves true randomness without complex hardware while avoiding sequence repetition.
2Productivity
If constant initial conditions are used in PRNGs, then the generation process is simple and reproducible, but the sequences eventually repeat and lack true randomness
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing user-specific seed values based on user identity before the random number generation process. This allows the generation process to remain simple and fast while ensuring high-quality randomness, as each user's sequence is predetermined to be unique and non-repeating.
Solution Approach 2:
The patent introduces an intermediary computation step where the user's identity (username) is hashed to generate a seed value. This intermediary process transforms simple user input into a high-quality random seed, maintaining fast generation speed while significantly improving randomness quality and preventing sequence repetition.
3Reliability
If user-specific seed values are computed from ASCII representations of names, then true randomness and non-deterministic properties are achieved, but the computational complexity increases
Solution Approach 1:
The patent replaces complex mechanical or hardware-based random number generation with a computational approach using ASCII representation hashing. This substitution achieves true randomness and non-deterministic properties through software-based computation, maintaining simplicity while significantly improving randomness authenticity and user-specific customization.
Data Source
AI summary
A method for assigning a random number to a user in a set of users includes computing a random number assignment seed value based on an ASCII-value representation of the user's name, dividing the random number assignment seed value by a quantity of unassigned numbers available to be assigned to the user to produce a modified random number assignment seed value, rounding the modified random number assignment seed value down to an integer, computing a random number offset value by multiplying the quantity of unassigned numbers by the rounded modified random number assignment seed value, subtracting the random number assignment offset value from the random number assignment seed value to determine a random number assignment lookup number, determining the random number to be assigned to the user based on the random number assignment lookup number, and assigning the determined random number to the user.