Neural Network-Inspired Pseudo-Random Number Generator (PRNG)

This repository contains a simple C implementation of a Neural Network-inspired Pseudo-Random Number Generator (PRNG). The program uses an XORShift-based algorithm to generate random predictions for input strings like "cat" or "dog." The system updates a score based on correct predictions and keeps track of the highest score.

Features

• XORShift PRNG: Utilizes an XORShift transformation to simulate randomness in predictions.
• Simple Neural Network Output Simulation: Generates binary output (0 or 1) based on the input ("cat" or "dog").
• Score Tracking: Maintains and updates current and high scores based on correct predictions.

Code Overview

• xorshift_transform: This function applies the XORShift algorithm to a seed array.
• neural_network_prng: Simulates a neural network-like prediction based on the input string.
• update_scores: Updates the score and high score based on the PRNG’s predictions.
• main: The main function runs an infinite loop that randomly picks an input ("cat" or "dog") and checks the prediction.

Prerequisites

• GCC (or any C compiler)
• Standard C libraries

Compilation

To compile and execute the program, use the following command:

gcc -o neural_prng neural_prng.c 
./neural_prng

How It Works

• The xorshift_transform function applies an XORShift transformation to update the internal state (seed) of the random number generator.
• The neural_network_prng function takes an input string ("cat" or "dog") and generates a pseudo-random output based on the seed.
  • For "cat", it expects a result of 0.
  • For "dog", it expects a result of 1.
• The update_scores function checks if the prediction matches the expected output and adjusts the score and high score accordingly.