Analysis of Logistic Map for Pseudorandom Number Generation in Game Development

TL;DR

This paper explores the use of the Logistic Map, a chaotic system, for pseudorandom number generation in game development, enabling both unpredictability and reproducibility of random sequences.

Contribution

It introduces a new pseudorandom sequence generation algorithm based on the Logistic Map, tailored for game development needs.

Findings

Logistic Map can generate viable pseudorandom sequences for games.

The proposed algorithm achieves reproducible randomness.

Experiments on Snake demonstrate practical applicability.

Abstract

Many popular video games use pseudorandom number generators to create randomly distributed locations for game objects as highly unpredictable as possible. Some scenarios like game competition also need reproducible randomness, namely the random results can be reproducible if given the same seed input. Existing random generation methods have limited choices for seed input. To address this limitation, this study analyzes a chaotic map called the Logistic Map for game development. After analyzing the properties of this chaotic map, I developed a pseudorandom sequence generation algorithm and a generation algorithm of random locations of game objects. Experiments on the game of Snake demonstrate that the Logistic Map is viable for game development. The reproducible randomness is also realized with the proposed algorithm.